Literature DB >> 30393474

Prevalence of childhood and adolescent overweight and obesity in Asian countries: a systematic review and meta-analysis.

Mohsen Mazidi1, Maciej Banach2,3, Andre Pascal Kengne4.   

Abstract

INTRODUCTION: We conducted a systematic review and meta-analysis to estimate the prevalence of overweight and obesity in children (aged 5-12 years) and adolescents (aged 12-19 years) in Asian countries. Study design: Systematic review and meta-analysis.
MATERIAL AND METHODS: We comprehensively searched specialised databases for relevant studies conducted in Asian countries between January 1, 1999, and May 30, 2017. Random effects models (using the DerSimonian-Laird method) and generic inverse variance methods were used for quantitative data synthesis. Sensitivity analysis was conducted using the 'leave-one-out' method. Heterogeneity was quantitatively assessed using the I2 index. Systematic review registration: CRD42016033061.
RESULTS: Among 22,286 identified citations, 41 studies met the inclusion criteria with n = 71,998 and n = 353,513 for children and adolescents. The pooled prevalence (overall, boys and girls) was 5.8% (n = 4175), 7.0% (n = 2631) and 4.8% (n = 1651) for obesity in children aged 5-11 years; 8.6% (n = 30,402), 10.1% (n = 17,990) and 6.2% (n = 10,874) for obesity in adolescents age 12-19 years. For overweight in children the values for overall, boys and girls were 11.2% (n = 7900), 11.7% (n = 4280) and 10.9% (n = 3698) respectively; and for overweight in adolescents, 14.6% (n = 46,886), 15.9% (27,183), and 13.7% (20,574). These findings were robust in sensitivity analyses. In children and adolescents a higher percentage of boys than girls are obese (children = 7.0 vs. 4.8%, adolescents = 10.1 vs. 6.2%, p < 0.001, respectively). Furthermore, in children and adolescents a higher percentage of boys than girls are overweight (children = 11.7 vs. 10.9%, adolescents = 15.9 vs. 13.7%, p < 0.001, respectively).
CONCLUSIONS: In view of the number of children who are overweight or obese, the associated detrimental effects on health, and the cost to health-care systems, implementation of programmes to monitor and prevent unhealthy weight gain in children and adolescents is needed throughout Asian countries.

Entities:  

Keywords:  adolescent; childhood; obesity; overweight

Year:  2018        PMID: 30393474      PMCID: PMC6209725          DOI: 10.5114/aoms.2018.79001

Source DB:  PubMed          Journal:  Arch Med Sci        ISSN: 1734-1922            Impact factor:   3.318


Introduction

The worldwide prevalence of overweight and obesity in children and adolescents has increased in recent decades [1]. An estimated 170 million children under 18 years of age were overweight or obese in 2008, and it has been projected that approximately 30% of all children will be affected by these conditions by 2030 [2, 3]. The prevalence of a body mass index (BMI) at or higher than the 95th percentile among children between the ages of 6 and 11 years in the United States increased from 4.2% in 1963–1965 to 15.3% in 1999–2000, before plateauing during the first decade of the 21st century [4, 5]. The overall prevalence of overweight, including obesity, in school children in European countries was estimated at 20.5%: 15.6% for overweight and 4.9% for obesity. The proportion of overweight and obesity was 24.5% in Eastern Asia countries and 11.9% in the Western Asia regions [6]. The World Health Organization (WHO) has estimated that the majority of overweight or obese children live in developing countries, where the rates are increasing faster than in developed countries [7]. A comparative study across developing countries reported that prevalence rates of obesity in adolescents in Asia are highest [8]. Furthermore, there are large within and between countries variations across Asia: 3.5% in rural Bangladesh to over 65% in the Maldives [9], 30% in Iran and Saudi Arabia and approximately 12.5% for Chinese children [10]. Obesity in early life is a precursor to obesity in adulthood [2], and excess weight in adults is associated with many adverse health outcomes including type 2 diabetes, hypertension, dyslipidaemia, cardiovascular diseases and type of cancers [2]. The current increasing prevalence of childhood overweight and obesity will therefore adversely affect the burden of obesity-related diseases and their consequences on families and health systems in the near future [11]. The etiological factors for childhood obesity include genetic, metabolic, and behavioural components [12]. In spite of the demonstrated genetic influence, a strong obesogenic environment is essential for its phenotypic expression of overweight and obesity [11, 13]. However, environmental modulators of the energy intake and expenditure (the imbalance of which leads to overweight and obesity) vary across regions. Studies in the Middle East have reported that among all of the lifestyle factors, overweight and obesity exhibited significant associations with less frequent vigorous physical activity, consumption of breakfast, vegetables and frequent sugar-sweetened beverage consumption [13]. Although there are some profound differences among Asian countries including socio-economic status, diversity of the cultures, races and genetics, the main contributors to the increasing burden of obesity and overweight among children and adolescents in Asia are very similar [13]. Childhood and adolescence is a short-term, but important, window of opportunity for the prevention management and control of obesity and related health consequences. In this regard, reliable data on the burden are a solid foundation of such prevention efforts. Regarding the size and diversity of the population of Asia and its high number of developing countries, the population of children and adolescents in Asia represents a relatively large proportion of the global population of children and adolescents in developing countries. We performed a systematic review and meta-analysis to determine the prevalence of childhood and adolescent overweight and obesity in Asian countries, with a view to providing accurate data for monitoring future trends.

Material and methods

Literature search

This systematic review is reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement [14]. The study protocol was registered with the International Prospective Register of Systematic Reviews, PROSPERO (registration no: CRD42016033061). We aimed to identify prevalence studies in Asian countries published from Jan 1, 1999, to May 30, 2017. A combination of words from the dictionary Medical Subject Heading Terms (MeSH) descriptors, and Boolean operators were used to search PUBMED, EMBASE, Web of Science, SCOPUS and Gray Literature sources with a range of search terms (Tables I and II). An expert librarian helped in designing the search strategy framework and implementing searches. Websites of relevant agencies such as the International Association for the Study of Obesity (IASO), the International Obesity Task Force, the Global School-based Student Health Survey and World Health Organization (WHO) were browsed. Additionally, we performed a manual search for other articles and references of published articles, and sent email requests to corresponding authors for additional data where relevant. To further minimize the effect of any publication bias, a snowball method, characterized by manual checking of references from retrieved articles, was applied. We also searched grey literature databases including the Virtual Library for Public Health and the System for Information on Grey Literature.
Table I

Full search terms and strategy used for systematically reviewing the articles indexed in PubMed and Scopus

No.ConceptSearch terms
1Childhood and adolescenceChild [Text Word] OR Child [MeSH terms] Children [Text Word] OR childhood [Text Word] OR adolescent [MeSH terms] OR adolescent [Text Word] OR adolescent* [Text Word] OR pediatric [Text Word] OR teens [Text Word] OR teen [Text Word] OR Teenage* [Text Word] OR Youth* [Text Word] OR Infan*[Text Word]
2Obesity and overweight“Obesity” [MeSH Terms] OR “Obesity” [All Fields] OR “Obese” [MeSH Terms] OR “Obese” [All Fields] OR “Overweight” [MeSH Terms] OR “Overweight” [All Fields] OR “body-mass index “ [MeSH Terms] OR “body-mass index “ [All Fields] OR “BMI” [All Fields] OR “Weight” [MeSH Terms] OR “Weight” [All Fields]
3Prevalence“Epidemiology” [Subheading] OR “Prevalence” [All Fields] OR “epidemiology” [All Fields] OR “prevalence” [MeSH Terms] OR “Proportion “ [All Fields] OR “Survey” [All Fields]
4Asian countries“Asia” [MeSH Terms] OR (Afghanistan [Text Word]) OR Bahrain [Text Word] OR Bangladesh [Text Word] OR Bhutan [Text Word] OR Brunei [Text Word] OR Cambodia [Text Word] OR China [Text Word] OR Hong Kong [Text Word] OR India [Text Word] OR Indonesia [Text Word] OR Iran [Text Word] OR Iraq [Text Word] OR Israel [Text Word] OR Japan [Text Word] OR Jordan [Text Word] OR Kazakhstan [Text Word] OR Kuwait [Text Word] OR Kyrgyzstan [Text Word] OR Laos [Text Word] OR Lebanon [Text Word] OR Malaysia [Text Word] OR Maldives [Text Word] OR Mongolia [Text Word] OR Myanmar [Text Word] OR Nepal [Text Word] OR North Korea [Text Word] OR Oman [Text Word] OR Pakistan [Text Word] OR Philippines [Text Word] OR Qatar [Text Word] OR Saudi Arabia [Text Word] OR Singapore [Text Word] OR South Korea [Text Word] OR Sri Lanka [Text Word] OR Syria [Text Word] OR Taiwan [Text Word] OR Tajikistan [Text Word] OR Thailand [Text Word] OR Timor-Leste [Text Word] OR Turkmenistan [Text Word] OR United Arab Emirates [Text Word] OR Uzbekistan [Text Word] OR Vietnam [Text Word] OR Yemen [Text Word]
5Combination1 AND 2 AND 3 AND 4
Table II

Full search terms and strategy used for systematically reviewing the articles published in EMBASE, Web of Science and Open Grey

No.ConceptSearch terms
1Childhood and adolescenceChild or youth or childhood or adolescent
2Obesity and overweightObesity or overweight
3PrevalencePrevalence OR epidemiology
4Asian countries“Asia” OR Afghanistan OR Bahrain OR Bangladesh OR Bhutan OR Brunei OR Cambodia OR China OR Hong Kong OR India OR Indonesia OR Iran OR Iraq OR Israel OR Japan OR Jordan OR Kazakhstan OR Kuwait OR Kyrgyzstan OR Laos OR Lebanon OR Malaysia OR Maldives OR Mongolia OR Myanmar OR Nepal OR North Korea OR Oman OR Pakistan OR Philippines OR Qatar OR Saudi Arabia OR Singapore OR South Korea OR Sri Lanka OR Syria OR Taiwan OR Tajikistan OR Thailand OR Timor-Leste OR Turkmenistan OR United Arab Emirates OR Uzbekistan OR Vietnam OR Yemen
5Combination1 AND 2 AND 3 AND 4
Full search terms and strategy used for systematically reviewing the articles indexed in PubMed and Scopus Full search terms and strategy used for systematically reviewing the articles published in EMBASE, Web of Science and Open Grey To be included in this systematic review, primary studies had to meet these criteria: 1) population-based cross-sectional or cohort studies reporting the prevalence of overweight and obesity in children and adolescents, 2) studies conducted in Asians after 1999 and published between January 1999 and May 30, 2017, 3) age of the participants ranging between 5 and 19 years, with 5–11 years defining children and 12–19 years defining adolescents, 4) original studies containing a minimum of information necessary to calculate pooled analysis of prevalence (number of subjects, sample size), 5) articles with at least the abstract in English language, 6) obesity and overweight defined using directly measured anthropometries and not based on self-report, 7) participants residing in Asian countries, irrespective of ethnic, socioeconomic, and educational backgrounds. Studies were excluded if: 1) they were done in clinical settings and/or in participants with special medical conditions, 2) they were conducted in Asians living outside Asia, 3) they were based on self-reported weight or height, 4) were narrative reviews, commentaries, opinion pieces, methodological, editorials, letters or any other publications lacking primary data and/or explicit method descriptions, 5) they did not report the prevalence of obesity or overweight separately for children and adolescents. When authors presented the results of the same study in more than one paper, the most recent and most comprehensive paper was included.

Selecting studies for inclusion

We started with the removal of duplicates; next, two reviewers excluded some papers based on titles and abstracts only. Then eligibility was further assessed via the full text (Figure 1). Disagreements between reviewers were resolved by consensus.
Figure 1

Overall prevalence of obesity in children

Overall prevalence of obesity in children

Assessment of the methodological quality of included studies

We assessed the methodological quality of included studies in terms of internal validity, external validity, response rate, and generalizability of study results. We used the ten-item rating system developed by Hoy et al. [15] and modified by Werfalli et al. [16] (Table III) to assess sampling, the sampling frame and size, outcome measures, outcome assessment, response rate, and statistical reporting [15]. Each item was assigned a score of 1 (yes) or 0 (no), and scores were summed across items to generate an overall quality score that ranged from 0 to 10. Each study was rated as having a low, moderate, or high risk of bias depending on the number of questions answered as “yes (low risk)”: studies at low risk of bias had scores higher than 8, moderate a score of 6–8, and high a score of 5 or lower [15]. Risk of selection and attrition biases were assessed according to the Cochrane guidelines, in Review Manager version 5.2. Two reviewers (MM and PR) independently assessed study quality, with disagreements being resolved by consensus.
Table III

Quality assessment criteria for prevalence studies

ItemsQuality score
External validity
 1. Was the study’s target population a close representation of the national population in relation to relevant variables?(1 point)
 2. Was the sampling frame a true or close representation of the target population?(1 point)
 3. Was some form of random selection used to select the sample, OR was a census undertaken?(1 point)
 4. Was the likelihood of non-response bias minimal?(1 point)
Total (4 points)
Internal validity
 1. Were data collected directly from the participants (as opposed to a proxy)?(1 point)
 2. Was an acceptable case definition used in the study?(1 point)
 3. Was the study instrument that measured the parameter of interest shown to have validity and reliability?(1 point)
 4. Was the same mode of data collection used for all participants? (1 point)(1 point)
 5. Was the length of the shortest prevalence period for the parameter of interest appropriate?(1 point)
 6. Were the numerator(s) and denominator(s) for the parameter of interest appropriate?(1 point)
Total (6 points)
Quality assessment criteria for prevalence studies

Data extraction and management

Two reviewers extracted data onto a purpose-designed data extraction form and independently summarized what they considered to be the most important results from each study. These summaries were compared and disagreements resolved by discussion and consultation with a third reviewer. Any further calculations on study data considered necessary were conducted by the first reviewer and checked by the second reviewer. Study characteristics including prevalence of obesity and/or overweight, country where the study was conducted, year of publication, study population, age range, sex (boys, girls, or combined), response rate, study design, criteria for sample selection and sample size, diagnostic criteria, results and notes/comments are presented in Table IV. When a study did not present the mean age of the subjects in each age group we assumed the mid-point of the age interval. When an age group also included subjects older than 19 years (e.g. age group 17–22 years), we computed the mid-point and excluded the data if the mid-point year was higher than 19 years old. Data for age ranges that covered more than one age group were not extracted.
Table IV

International overweight and obesity classification methods for children and adolescents

ClassificationIndicatorRisk of overweightOverweight*ObesityAge range [years]
WHO 2007(23)BMI/age> 1 SD and ≤ 2 SD> 2 SD5–19
IOTF 2000 (97)BMI/ageAge-specific and sex-specific BMI cut-off points for overweight and obesity that track with BMI values of 25 at 18 years of ageAge-specific and sex-specific BMI cut-off points for overweight and obesity that track with BMI values of 30 at 18 years of age2–18
CDC 2000 (98)BMI/age≥ p85 < p95≥ p952–19
NCHS/WHOBMI/age≥ p85 < p95≥ p9510–19
1979 (99)W/H2 SD< 10

W/H – weight-for-height, SD – standard deviation, IOTF – International Obesity Task Force, CDC – Centers for Disease Control and Prevention, NCHS – National Center for Health Statistics, p85 – 85th percentile, p95 – 95th percentile.

In children younger than 5 years, overweight is currently defined as risk of overweight, and obesity as overweight, according to the WHO 2006 norms and for CDC 2000 reference since 2007.

For children younger than 2 years, the indicator is weight-for-length, referred to here and in the text as weight-for-height.

International overweight and obesity classification methods for children and adolescents W/H – weight-for-height, SD – standard deviation, IOTF – International Obesity Task Force, CDC – Centers for Disease Control and Prevention, NCHS – National Center for Health Statistics, p85 – 85th percentile, p95 – 95th percentile. In children younger than 5 years, overweight is currently defined as risk of overweight, and obesity as overweight, according to the WHO 2006 norms and for CDC 2000 reference since 2007. For children younger than 2 years, the indicator is weight-for-length, referred to here and in the text as weight-for-height.

Diagnosis of obesity and overweight in included studies

In the case of diagnosis of obesity in school-age children and adolescents (5–19 years) the International Obesity Task Force (IOTF) [17] and the WHO 2007 methods [18] were used. Different classification methods used different cut-off points and reference populations. For school-age children and adolescents (5–19 years), the two most widely used classification methods were the IOTF [17] and the WHO 2007 methods [18], both using BMI. WHO criteria were used for overweight and obesity in adults [18].

Data synthesis and analysis

Data extraction and synthesis was based on Cochrane Handbook recommendations [19]. We used a random-effects meta-analysis model to aggregate prevalence estimates across studies while accounting for the between-study variability [20]. Heterogeneity between studies was assessed with Cochran’s χ2 test based on a 10% level of significance cut-off (due to the low power of the test) and the I2 statistic where values of 25%, 50% and 75% reflect low, medium and high heterogeneity, respectively [14]. We explored sources of heterogeneity by comparing obesity and overweight prevalence between subgroups defined by several study level characteristics. In order to evaluate the influence of each study on the overall effect size, sensitivity analysis was conducted using the leave-one-out method, i.e. removing one study each time and repeating the analysis [21-23]. Potential publication bias was explored using visual inspection of Begg’s funnel plot asymmetry, Begg’s rank correlation and Egger’s weighted regression tests. Duval and Tweedie ‘trim and fill’ and ‘fail-safe N’ methods were used to adjust the analysis for the effects of publication bias [24]. Meta-analysis was conducted using Comprehensive Meta-Analysis (CMA) V3 software (Biostat, NJ) [25].

Results

Summary of searches and study selection process

The searches identified 22,286 citations. After screening of titles and abstracts, and removal of duplicates, 12,635 studies were selected for further scrutiny, of which 210 were selected for full-text review. Of these, 47 studies (n = 71,998 and 353,513 for children and adolescents, respectively) met the inclusion criteria and were included in this systematic review (Figure 2).
Figure 2

PRISMA Flow chart for the studies selection

PRISMA Flow chart for the studies selection

Methodological quality of included studies

From all the studies, 30 of them were considered as having a “low risk of bias” while the rest of them had a “moderate risk of bias”. Six surveys did not report how subjects were selected; 26 studies mentioned random selection as a selection technique while 12 surveys reported a non-random sampling method. Nineteen studies stated the response rates, which ranged from 71.1% to 100% (median: 85.5%).

Characteristics of included studies

The characteristics of the included studies are summarized in Table V. Of the 44 countries of the Asian continent, 15 were represented in this systematic review: five studies from India [26-30], eight from Iran [31-38], seven from Saudi Arabia [13, 39–43], three from Kuwait [44-46], four from Taiwan [47-50], four from China [51-54], two from the United Arab Emirates [55, 56], four from Jordan [57-60], two from Bahrain [61, 62], two from Japan [63, 64] and one from Singapore [65], Thailand [66], Malaysia [67], Israel [68], Pakistan [69] and Turkey [70]. Two studies conducted in Israel and Thailand [66, 68] had national coverage while the remainder were subnational. Different diagnosis criteria for obesity and overweight were applied across studies including the CDC criteria in 7 studies [31, 33, 35, 37, 38, 41, 57], IOTF criteria in 11 studies [29, 42, 45, 50, 52, 58, 63–65, 71, 72], NCHC criteria in 2 studies [44, 46], WHO criteria in 16 studies [28, 32, 36, 39, 42, 49, 54, 56, 59, 62, 66–69, 73, 74], NHANES criteria in 1 study [55], Cole criteria in 6 studies [27, 30, 43, 53, 60, 75] and the Chinese index in 1 study [51], Table IV. These studies were published between 1994 and 2015. Participants in two studies were only female, while the proportion of men in other studies ranged from 34% [66] to 100% [43]. Participants’ age ranged from 2 years [54] to 25 years [67].
Table V

National prevalence of overweight and obesity in children and adolescents from cross-sectional surveys in Asian countries

First author surname, date of publicationSample designDate of fieldworkSample size (% male)Age rangeClassification methodUrban or ruralPrevalence of overweightPrevalence of obesityCombined prevalence of overweight and obesityResponse rate
Baker, 2010 [3]Cluster randomMay 2007.1355 (44.4%)13 to 16 yearsBased on CDCBoth (urban 29.2% and rural 70.8%)15.7%8.7%24.4%98.9%
Aggarwal, 2008 [10]RandomNot known1000 (50%)12 to 18 yearsWHOUrban15% (male)10.2% (female)3.4% (male)3.4% (female)18.4%13.6%Not known
Ahmed, 2013 [12]RandomJanuary 2008 to June 2009501 (50.8%)6 to 10 yearsBased on WHOUrban8%12%20%99.4%
Akbulut, 2013 [13]RandomNot known1348 (50.4%)10 to 14 yearsBased on Cole et al.Urban57%15%72%79% to 90%
Al Alwan, 2013 [14]Multistage cluster randomJanuary to June 20061212 (42.2%)6 to 16 yearsBased on WHOUrban21.1%12.7%33.8%97.5%
AlHazza, 2014 [24]A random multistage stratified cluster-sampling2009–20102908 (48.1%)14 to 19 yearsBased on IOTFUrban40.3%38.1%78.4%Not known
AlHazza, 2007 [25]RandomApril to May 2006224 (48.6%)4 to 6 yearsBased on CDCUrban20.6%10.8%31.4%75%
Huda, 2003 [26]Not knownOctober 1998 to April 1999898 (females)11–18 yearsBased on NHANESUrban14%9%23%Not known
Al Isa, 2004 [27]Multistage stratified randomOctober 1999 to April 200014659 (49.1%)10 to 14 yearsBased on NCHSUrban61.8%27.8%89.6%Not known
Al Sendi, 2003 [30]Multistage stratified randomSeptember to November 2000506 (49.2%)12 to 17 yearsBased on WHO, Must et al. and Cole et al.Urban11.9% (WHO), 32% (Must et al.), and 39.8% (Cole et al.)56.7% (WHO), 36.7% (Must et al.), and 32.8% (Cole et al.)68.6% (WHO), 68.7% (Must et al.), and 72.6% (Cole et al.)93.7%
Amin, 2008 [31]Multistage stratified randomNot known1139 (100%)10 to 14 yearsBased on Cole et al.Urban/rural14.2%9.7%23.9%88.8%
Ayatollahi, 2006 [32]Random2002–20032397 (52.8%)6.5 to 11.5 yearsBased on CDCUrban10.6%9.4%20%91.5%
Dayan, 2005 [37]Not knownNot known76 732 (57.8%)17 yearsNot knownUrban23.8%7.4%31.2%Not known
Chen, 2008 [52]RandomNot known883 (51%)12 to 16 yearsNot knownUrban and rural38.4%12.3%50.7%Not known
Chen, 2012 [53]Random2007 and 201050912839≤ 9 to ≥ 13 yearsBased on WHOUrban32.5% (2007)32% (2010)18.3% (2007)15.9% (2010)50.8 (2007)47.9 (2010)86.5%75.5%
Chu, 2007 [62]Stratified, multistaged, and clustered20012405 (53.6%)6 to 13 yearsBased on Nutrition and Health Survey inTaiwan (WHO)Urban15.5% (male)14.4% (female)14.7% (male)9.1% (female)30.2% (male)23.5% (female)Not known
El Bayoumy, 2009 [80]RandomJanuary to July 20065402 (49.18%)10 to 14 yearsBased on NCHSUrban30.7%14.6%45.3%Not known
Fu, 2003 [85]RandomNot known623 (51.5%)6 to 11 yearsBased on IOTF and PWHUrbanNot known6.9% (IOTF) and (PWH) 16.4%Not knownNot known
Hamaideh, 2010 [99]Cluster randomNot known824 (51.4%)14 to 17 yearsBased on IOTFUrban and rural19.1%6.3%25.4%84%
Jagadesan, 2014 [114]Not knownNot known18 955 (56.2%)6 to 17 yearsBased on IOTF and Khadilkar’s criteriaUrban13.5% (IOFT) and 19.9% (Khadilkar’s criteria)3.4% (IOFT) and 9.4% (Khadilkar’s criteria)Not known95.3%
Khader, 2009 [126]Cluster randomMarch to May 20062131 (49.3%)6 to 12 yearsBased on Cole et al.Urban and rural19.4%5.6%25%94.2%
Xinhua, 2010 [135]ClusterMarch to June 20056288 (52.5%)6 to 9 yearsBased on IOTFUrban10.1%3.5%13.6%100%
Liou, 2010 [136]Three-stage stratified cluster2006 and 20078640 (51.7%)13 to 16 yearsBased on IOTFUrban16.1%7.2%23.3%86.3
Ma, 2011 [138]Random2008 to 20098 653 (51.9%)2 to 7 yearsBased on WHO, IOTF and CDCUrban10.9% (WHO), 10.9% (IOTF) and 11.2% (CDC)13.8% (WHO), 6.08% (IOTF) and 11.7% (CDC)24.7% (WHO), 17.7% (IOTF) and 22.9% (CDC)89.4%
Maddah, 2010 [139]RandomOctober 2006 to March 20072577 (female)12 to 17 yearsBased on IOTFUrban18.6%5.9%24.5%98.7%
Nakano, 2010 [150]Not known2001 to 200716245 (51.8%)6 to 14 yearsBased on IOTFUrban30% –14%6% – 11%36% – 25%71.1%
Ramachandran, 2002 [159]Not knownNot known4700 (50.7%)13 to 18 yearsNot knownUrban33.6%6.5%40.1%Not known
Sun, 2009 [168]Not knownJune to July 20105753 (49.4%)12 to 13 yearsBased on IOTFUrban16.4%Not knownNot known91.6%
Tabesh, 2014 [169]Random2012–20135811 (49.9%)7 to 11 yearsBased on WHOUrban21.4%5.5%26.8%Not known
Taheri, 2013 [170]ClusterNovember to February 20121541 (44.7%)6 to 11 yearsBased on CDCUrban9.6%9.2%18.8%93.5%
Zaal, 2011 [181]RandomNot known661 (49%)12 to 17 yearsBased on WHOUrban15.7%21.3%37%Not known
Bose, 2007 [195]Cross-sectionalJanuary to March 20024316 to 9 yearsNot knownNot known17.63%5.10%Not knownNot known
Gopalakrishnan, 2012 [199]Cross sectionalNot known290 (45.2%)19 to 25 yearsNot knownNot knownMale; 13.7%Female; 15.7%Total; 14.8%Male; 9.2%;Female 1.2%;Total 5.2%Not knownNot known
Ibrahim, 2007 [201]RandomFrom March 2006 to September 20061695 (49.6%)3 to 6 yearsBased on data provided at the website of Jordanian Ministry of Education for the academic year 2005/2006Urban and semi-urbanMale; 3.8%Female; 7.2%Male 20.8%;Female 19.1%Not knownNot known
Maddah, 2006 [206]Cross-sectionalDecember 2004 and April2005105414 to 17 yearsBased on IOTFUrban21.9%5.3%Not knownNot known
Montazerifar, 2009 [209]Cross-sectional2005–200675214 to 18 yearsBased on IOTF, NHANES I and CDCUrban8.6% (CDC)8.8% (IOTF)8.4% (NHANES I)1.5% (CDC)1.5% (IOTF)1.5% (NHANES I)Not knownNot known
Pwint, 2013 [213]Cross-sectionalMay 2006 to November 20083009 (52.2%)6 to 72 monthsBased on IOTF, CDC and NHGPUrban8.1% (CDC)7.6% (IOTF)7.5% (NHGP)7.1% (CDC)3.9% (IOTF)5.3% (NHGP)Not known72.3%
Ghada, 2009Random2009698 (50.0%)4 to 6 years (male)2 to 4 years (female)WHOBoth8.4% (male)12.3% (female)7.2% (male)8.4% (female)15.6% (male)20.7% (female)Not known
Zekavat, 2014Random20091158 (50.6%)7 to 13 yearsCDCUrban9.9% (male)10.0% (female)5.1% (male)4.9% (female)15% (male)14.9% (female)Not known
Cao, 2012Sampling201288974 (49.6%)12 to 17 yearsChinese indexUrban14.6% (male)8.6% (female)7% (male)2.9% (female)21.6% (male)11.5% (female)Not known
Al-Almaie, 2005Random20011766 (38.2%)14 to 18 yearsIOTFUrban10.2% (male)17.2% (female)19.3% (male)11.8% (female)29.5% (male)29% (female)Not known
Hajian Tilaki, 2008Population-based cross-sectional20061000 (45.0%)7 to 12 yearsCDCUrban12.5% (male)12.2% (female)8.8% (male)3.8% (female)21.3% (male)16% (female)
Al-Rukban, 2003Cross-sectional study2001–2002894 (100%)12 to 20 yearsWHOUrban13.8%20.5%34.3%
Goyal, 2010Random11328 (50%)12 to 18 yearsWHOUrban and Rural14.3% (male)9.2% (female)2.9% (male)1.5% (female)17.2% (male)10.7% (female)
Alenazi, 2015Cross-sectional study2012523 (100%)15.5 to 17.5 yearsCDCUrban17.2%30.4%47.6%
Allafi, 2013Cross-sectional study2009906 (51.0%)14 to 19 yearsIOTF-WHOUrban25.1% (male)25.3% (female)25.5% (male)21.3% (female)50.6% (male)46.6% (female)
Seubsman, 2010A National Cohort Study200529065 (34%)15 to 25 yearsWHOUrban10.4% (male)5.9% (female)
National prevalence of overweight and obesity in children and adolescents from cross-sectional surveys in Asian countries

Prevalence by age, sex, region, and type of residence

Overall prevalence of obesity

The overall prevalence of obesity was 5.8% (n = 4175) (95% CI: 4.6–7.3; 43 studies, heterogeneity p = 0.214; I2 = 6.3%) in children (Figure 1) and 8.6% (n = 30,402) (95% CI: 7.2–10.2; 47 studies, heterogeneity p = 0.318; I2 = 4.1%) in adolescents (Figure 3). The prevalence of obesity in children by diagnostic criteria was 6.7% (95% CI: 6.1–7.5; 7 studies, heterogeneity p = 0.091; I2 = 4.2%) for CDC, 3.1% (95% CI: 2.8–3.3; 14 studies, heterogeneity p = 0.122; I2 = 6.9%) for IOTF, 12.1% (95% CI: 11.0–12.9; 14 studies, heterogeneity p = 0.213; I2 1.3%) for WHO and 12.8% (95% CI: 12.3–13.4; 8 studies, heterogeneity p = 0.203; I2 = 4.6%) for Cole criteria; p < 0.001 for the difference in the prevalence of obesity across criteria in children.
Figure 3

Overall prevalence of obesity in adolescents

Overall prevalence of obesity in adolescents The prevalence of obesity in adolescents by diagnostic criteria was 15.3% (95% CI: 13.7–17.1; 4 studies, heterogeneity p = 0.412; I2 = 6.3%) for CDC, 8.9% (95% CI: 8.4–9.3; 10 studies, heterogeneity p = 0.124; I2 = 2.1%) for IOTF, 14.1% (95% CI: 13.7–14.6; 4 studies, heterogeneity p = 0.532; I2 = 9.6%) for NCHC, 8.8% (95% CI: 8.7–8.9; 23 studies, heterogeneity p = 0.421; I2 = 8.3%) for WHO, 9.0% (95% CI: 7.3–11.1; 1 study, heterogeneity p = 0.100; I2 = 0.0%) for NHANES, 4.4% (95% CI: 3.9–5.0; 3 studies, heterogeneity p = 0.632; I2 = 1.2%) for Cole and 5.4% (95% CI: 5.2–5.6; 2 studies, heterogeneity p = 0.100; I2 = 0.0%) for the Chinese index; p < 0.001 for the difference in the prevalence of obesity across criteria in adolescents.

Overall prevalence of overweight

The overall prevalence of overweight was 11.2% (n = 7902) (95% CI: 9.3–13.4; 39 studies, heterogeneity p = 0.183; I2 = 6.4%) in children (Figure 4) and 14.6% (n = 46,886) (95% CI: 12.5–17.1; 51 studies, heterogeneity p = 0.128; I2 = 9.7%) in adolescents (Figure 5). The prevalence of overweight in children by diagnostic criteria was 8.8% (95% CI: 8.1–9.6; 7 studies, heterogeneity p = 0.421; I2 = 4.6%) for CDC, 10.8% (95% CI: 10.5–11.2; 12 studies, heterogeneity p = 0.692; I2 = 4.1%) for IOTF, 15.5% (95% CI: 15.0–16.0; 12 studies, heterogeneity p = 0.158; I2 = 3.1%) for WHO and 23.7% (95% CI: 23.0–24.3; 8 studies, heterogeneity p = 0.782; I2 = 9.6%) for Cole criteria; p < 0.001 for the difference in the prevalence of obesity across criteria in children.
Figure 4

Overall prevalence of overweight in children

Figure 5

Overall prevalence of overweight in adolescents

Overall prevalence of overweight in children Overall prevalence of overweight in adolescents The prevalence of overweight in adolescents by diagnostic criteria was 14.6% (95% CI: 13.3–16.0; 4 studies, heterogeneity p = 0.084; I2 = 6.5%) for CDC, 17.0% (95% CI: 16.5–17.4; 14 studies, heterogeneity p = 0.142; I2 = 4.2%) for IOTF, 30.9% (95% CI: 30.2–31.5; 4 studies, heterogeneity p = 0.823; I2 = 4.2%) for NCHC, 9.8% (95% CI: 9.7–10.0; 22 studies, heterogeneity p = 0.961; I2 = 2.8%) for WHO and 17.4% (95% CI: 16.4–18.4; 4 studies, heterogeneity p = 0.635; I2 = 1.4%) for Cole criteria; p < 0.001 for the difference in the prevalence of obesity across criteria in adolescents.

Prevalence of obesity and overweight by sex

The overall prevalence of obesity in children by gender was 7.0% (n = 2631) (95% CI: 5.0–9.6; 21 studies, heterogeneity p = 0.262; I2 = 6.9%) in boys and 4.8% (n = 1561) (95% CI: 3.4–6.8; 21 studies, heterogeneity p = 0.102; I2 = 2.1%) in girls; p < 0.001 for the difference by gender. The overall prevalence of obesity in adolescents by gender was 10.1% (n = 17,989) (95% CI: 8.0–12.6; 24 studies, heterogeneity p = 0.832; I2 = 1.4%) in boys and 6.2% (n = 10,872) (95% CI: 4.6–8.2; 25 studies, heterogeneity p = 0.209; I2 = 9.2%) in girls; p < 0.001 for the difference by gender. The overall prevalence of overweight in children by gender was 11.7% (n = 4296) (95% CI: 8.8–15.3; 19 studies, heterogeneity p = 0.965; I2 = 7.1%) in boys and 10.9% (n = 3694) (95% CI: 8.4–14.1; 19 studies, heterogeneity p = 0.101; I2 = 3.4%) in girls; p < 0.001 for the difference by gender. The overall prevalence of overweight in adolescents by gender was 15.9% (n = 27,183) (95% CI: 12.8–19.7; 24 studies, heterogeneity p = 0.321; I2 = 8.9%) in boys and 13.7% (n = 20,574) (95% CI: 10.6–17.6; 26 studies, heterogeneity p = 0.215; I2 = 3.3%) in girls; p < 0.001 for the difference by gender.

Prevalence of obesity and overweight by region

Childhood obesity prevalence in urban boys and girls was 6.6% (95% CI: 4.3–9.9; heterogeneity p = 0.425; I2 = 6.2%) and 4.6% (95% CI: 3.1–6.7; heterogeneity p = 0.329; I2 = 8.3%), and for overweight it was 12.6% (95% CI: 8.9–17.6; heterogeneity p = 0.211; I2 = 2.1%) and 10.8% (95% CI: 7.8–14.8; heterogeneity p = 0.159; I2 = 1.4%) respectively. The prevalence of obesity in urban adolescent boys and girls was 10.3% (95% CI: 7.7–13.7; heterogeneity p = 0.825; I2 = 2.1%) and 6.6% (95% CI: 4.8–9.0; heterogeneity p = 0.742; I2 = 6.3%) and for overweight it was 17.1% (95% CI: 14.3–20.1; heterogeneity p = 0.269; I2 = 1.3%) and 14.8% (95% CI: 11.7–18.6; heterogeneity p = 0.867; I2 = 8.6%) respectively.

Sensitivity analysis

In leave-one-out sensitivity analyses, the pooled effect estimates remained similar across all studies and within specific subgroups (Table VI). This stability confirmed that the significant difference between the studied groups is the overall effect from all included studies.
Table VI

Sensitivity analysis across all studies

VariablesResult of the leave-one-out sensitivity analyses
Total obesity in children5.8% (95% CI: 4.6–7.3)
Total obesity in adolescents8.6% (95% CI: 7.2–10.2)
Obesity in children:
 CDC6.7% (95% CI: 6.1–7.5)
 WHO3.1% (95% CI: 2.8–3.3)
 Cole12.8% (95% CI: 12.3–13.4)
Obesity in adolescents:
 CDC15.3% (95% CI: 13.7–17.1)
 IOTF8.9% (95% CI: 8.4–9.3)
 NCHC14.1% (95% CI: 13.7–14.6)
 WHO8.8% (95% CI: 8.7–8.9)
 NHANES9.0% (95% CI: 7.3–11.1)
 Cole4.4% (95% CI: 3.9–5.0)
 Chinese index5.4% (95% CI: 5.2–5.6)
Total overweight in children11.2% (95% CI: 9.3–13.4)
Total overweight in adolescents14.6% (95% CI: 12.5–17.1)
Overweight in children:
 CDC10.8% (95% CI: 10.5–11.2)
 WHO15.5% (95% CI: 15.0–16.0)
 Cole23.7% (95% CI: 23.0–24.3)
Overweight in adolescents:
 CDC14.6% (95% CI: 13.3–16.0)
 IOTF17.0% (95% CI: 16.5–17.4)
 NCHC30.9% (95% CI: 30.2–31.5)
 WHO9.8% (95% CI: 9.7–10.0)
 Cole17.4% (95% CI: 16.4–18.4)
Sensitivity analysis across all studies

Publication bias

Visual inspection of funnel plot symmetry suggested no potential publication bias for the overall prevalence of obesity in children and adolescents (Figures 6 and 7). The presence of publication bias was also not suggested by Begg’s rank correlation test (Kendall’s τ with continuity correction = –0.17, z = 1.61, p = 0.107 in children and –0.13, z = 1.30, p = 0.192 in adolescents). After adjustment of effect sizes for potential publication bias using the ‘trim and fill’ correction, no potentially missing studies were imputed in the funnel plot (Figures 8 and 9). The ‘fail-safe N’ test showed that 7525 studies (in children) and 8070 studies (in adolescents) would be needed to bring the result to a non-significant (p > 0.05) value.
Figure 6

Funnel plots for publication bias for the overall prevalence of obesity in children. Open circles represent observed published studies; open diamond represents observed effect size

Figure 7

Funnel plots for publication bias for the overall prevalence of obesity in adolescents. Open circles represent observed published studies; open diamond represents observed effect size

Figure 8

Trim and fill method to impute potentially missing studies (prevalence of obesity in children). No potentially missing study was imputed in the funnel plot. Open circles represent observed published studies; open diamond represents observed effect size; closed diamond represents imputed effect size

Figure 9

Trim and fill method to impute potentially missing studies (prevalence of obesity in adolescents). No potentially missing study was imputed in the funnel plot. Open circles represent observed published studies; open diamond represents observed effect size; closed diamond represents imputed effect size

Funnel plots for publication bias for the overall prevalence of obesity in children. Open circles represent observed published studies; open diamond represents observed effect size Funnel plots for publication bias for the overall prevalence of obesity in adolescents. Open circles represent observed published studies; open diamond represents observed effect size Trim and fill method to impute potentially missing studies (prevalence of obesity in children). No potentially missing study was imputed in the funnel plot. Open circles represent observed published studies; open diamond represents observed effect size; closed diamond represents imputed effect size Trim and fill method to impute potentially missing studies (prevalence of obesity in adolescents). No potentially missing study was imputed in the funnel plot. Open circles represent observed published studies; open diamond represents observed effect size; closed diamond represents imputed effect size

Discussion

This study has systematically evaluated the scientific literature to provide robust estimates for obesity and overweight prevalence by age group, sex and setting in children and adolescents in Asian countries. The overall prevalence of obesity was 5.8% in Asian children and 8.6% in adolescents. Equivalents for overweight were 11.2% in children and 14.6% in adolescents. The overall prevalence by gender was 7.0% and 4.8% in boys and girls for obesity in children, and 11.7% and 10.9% in boys and girls respectively for overweight in children. Furthermore, according to our findings, childhood obesity prevalence in urban boys and girls was 6.6% and 4.6% and for overweight it was 12.6 and 10.8% respectively, and the prevalence of obesity in urban adolescent boys and girls was 10.3% and 6.6%, while for overweight it was 17.1% and 14.8% respectively. In line with our findings, some systematic reviews have reported on growing prevalence of obesity and overweight among children and adolescents. The Global Burden of Disease Study estimated that the prevalence of obesity/overweight in children and adolescents in developing countries was 12.9% for boys and 13.4% for girls in 2013 [76]. A meta-analysis concluded that the prevalence of obesity in children and adolescents aged 2 to 19 years in the United States in 2011–2014 was 17.0%, while the prevalence of extreme obesity was 5.8% [77]. The combined prevalence of overweight and obesity in European children below the age of 10 ranged from > 40% in southern Europe to < 10% in northern Europe [78]. These findings confirm the high prevalence of overweight and obesity in children and adolescents worldwide. In another study in which worldwide trends in mean BMI in children and adolescents were estimated, they reported that the rising trends in children’s and adolescents’ BMI have plateaued in many high-income countries, albeit at high levels, but have accelerated in parts of Asia [79]. Different definitions have been used for childhood and adolescent obesity; thus, it is difficult to make meaningful comparisons across countries and studies. According to the cut-off point references when used to compare the obesity status in this meta-analysis, we found that compared with the CDC criteria, the IOTF, WHO and Cole definitions tend to underestimate the prevalence of obesity and overestimate the prevalence of overweight among Asian children and adolescents. The WHO reported that childhood overweight and obesity could be the results of the changing life style including consuming high energy-dense diets that are high in fat content and carbohydrate but low in vitamins and minerals, and doing less physical activity because of the sedentary lifestyles [80]. Asian investigations have reported epidemiologic transition along with a notable nutrition transition in the Asian child and adolescent population, and suggested that urbanization in most parts of Asia is associated with increased sedentary behaviour and lack of physical activity [28, 81], due to a lack of play areas, both in the community and in schools, as well as increasing time spent watching television and playing computer games [82, 83]. Additionally, due to more recent widespread availability of fast food shops in Asian countries, increasing consumption of junk foods has also contributed to dietary changes [83]. Furthermore, it has been reported that socioeconomic status (SES) influences the prevalence of childhood overweight and obesity [84]. National studies have confirmed a diet with higher energy-dense, animal-based foods in childhood with a high SES, and desire in city children to have a lower intake of fruit and vegetables [85]. It has been reported that urban families spend more time watching television, have less sleep and digital playing. Moreover, compared to rural area, subjects in urban areas have easier access to cars, which could be a contributing factor [86]. In our study the prevalence of obesity and overweight differed by sex. We found that girls had a lower prevalence of obesity than boys, and this ratio in adolescents was higher in boys compared to girls. It could be due to differences in body fat composition or physical activity, or the fact that girls care more about their appearance and pay higher attention to their body image than boys [87]. Boys and girls differ in several factors such as body composition, hormone biology and susceptibility to certain social, patterns of weight gain, ethnic, genetic, and environmental factors, which can explain gender differences [88]. The alarmingly high rate of overweight/obesity in Asian children and adolescents warrants immediate intervention: raising awareness among children, adolescents and their families about the health consequences of obesity and its related diseases including diabetes and cardiovascular diseases, teaching community members to encourage lifestyle changes including in diet and physical activity, national and international monitoring programmes in order to decrease the rate of overweight and obesity in the community in order to avoid an obesity epidemic in the future generation. The comparisons of overweight and obesity prevalence need to be interpreted with caution due to the differences in survey sampling methods, sample sizes, age range of subjects, quality of data in terms of height and weight measurement. Moreover, like most meta-analyses, we pooled together studies conducted under different circumstances in different parts of Asian countries among different population groups. In addition, a specific limitation of our meta-analysis is related to the difficulty of combining studies that used four different diagnostic criteria to assess overweight/obesity. This is directly related to the lack of consensus about the diagnostic criteria for overweight/obesity. In order to evaluate the sources of bias in the review, we performed subgroup analyses. Important strengths of the present study include the use of meta-analytic techniques to derive the pooled estimates, and the application of sensitivity analyses to confirm the robustness of our findings. In conclusion, from our findings it was revealed that in regard of the number of children who are overweight or obese, relevant health authorities should review the obesity preventive strategies and, using public health interventions, reduce the rate of obesity throughout Asian countries.
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