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Spiga F, Davies AL, Tomlinson E, Moore TH, Dawson S, Breheny K, Savović J, Gao Y, Phillips SM, Hillier-Brown F, Hodder RK, Wolfenden L, Higgins JP, Summerbell CD. Interventions to prevent obesity in children aged 5 to 11 years old. Cochrane Database Syst Rev 2024; 5:CD015328. [PMID: 38763517 PMCID: PMC11102828 DOI: 10.1002/14651858.cd015328.pub2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/21/2024]
Abstract
BACKGROUND Prevention of obesity in children is an international public health priority given the prevalence of the condition (and its significant impact on health, development and well-being). Interventions that aim to prevent obesity involve behavioural change strategies that promote healthy eating or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective and numerous new studies have been published over the last five years, since the previous version of this Cochrane review. OBJECTIVES To assess the effects of interventions that aim to prevent obesity in children by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events. SEARCH METHODS We used standard, extensive Cochrane search methods. The latest search date was February 2023. SELECTION CRITERIA Randomised controlled trials in children (mean age 5 years and above but less than 12 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance. DATA COLLECTION AND ANALYSIS We used standard Cochrane methods. Our outcomes were body mass index (BMI), zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome. MAIN RESULTS This review includes 172 studies (189,707 participants); 149 studies (160,267 participants) were included in meta-analyses. One hundred forty-six studies were based in high-income countries. The main setting for intervention delivery was schools (111 studies), followed by the community (15 studies), the home (eight studies) and a clinical setting (seven studies); one intervention was conducted by telehealth and 31 studies were conducted in more than one setting. Eighty-six interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over four years. Non-industry funding was declared by 132 studies; 24 studies were funded in part or wholly by industry. Dietary interventions versus control Dietary interventions, compared with control, may have little to no effect on BMI at short-term follow-up (mean difference (MD) 0, 95% confidence interval (CI) -0.10 to 0.10; 5 studies, 2107 participants; low-certainty evidence) and at medium-term follow-up (MD -0.01, 95% CI -0.15 to 0.12; 9 studies, 6815 participants; low-certainty evidence) or zBMI at long-term follow-up (MD -0.05, 95% CI -0.10 to 0.01; 7 studies, 5285 participants; low-certainty evidence). Dietary interventions, compared with control, probably have little to no effect on BMI at long-term follow-up (MD -0.17, 95% CI -0.48 to 0.13; 2 studies, 945 participants; moderate-certainty evidence) and zBMI at short- or medium-term follow-up (MD -0.06, 95% CI -0.13 to 0.01; 8 studies, 3695 participants; MD -0.04, 95% CI -0.10 to 0.02; 9 studies, 7048 participants; moderate-certainty evidence). Five studies (1913 participants; very low-certainty evidence) reported data on serious adverse events: one reported serious adverse events (e.g. allergy, behavioural problems and abdominal discomfort) that may have occurred as a result of the intervention; four reported no effect. Activity interventions versus control Activity interventions, compared with control, may have little to no effect on BMI and zBMI at short-term or long-term follow-up (BMI short-term: MD -0.02, 95% CI -0.17 to 0.13; 14 studies, 4069 participants; zBMI short-term: MD -0.02, 95% CI -0.07 to 0.02; 6 studies, 3580 participants; low-certainty evidence; BMI long-term: MD -0.07, 95% CI -0.24 to 0.10; 8 studies, 8302 participants; zBMI long-term: MD -0.02, 95% CI -0.09 to 0.04; 6 studies, 6940 participants; low-certainty evidence). Activity interventions likely result in a slight reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.18 to -0.05; 16 studies, 21,286 participants; zBMI: MD -0.05, 95% CI -0.09 to -0.02; 13 studies, 20,600 participants; moderate-certainty evidence). Eleven studies (21,278 participants; low-certainty evidence) reported data on serious adverse events; one study reported two minor ankle sprains and one study reported the incident rate of adverse events (e.g. musculoskeletal injuries) that may have occurred as a result of the intervention; nine studies reported no effect. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, may result in a slight reduction in BMI and zBMI at short-term follow-up (BMI: MD -0.11, 95% CI -0.21 to -0.01; 27 studies, 16,066 participants; zBMI: MD -0.03, 95% CI -0.06 to 0.00; 26 studies, 12,784 participants; low-certainty evidence) and likely result in a reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.21 to 0.00; 21 studies, 17,547 participants; zBMI: MD -0.05, 95% CI -0.07 to -0.02; 24 studies, 20,998 participants; moderate-certainty evidence). Dietary and activity interventions compared with control may result in little to no difference in BMI and zBMI at long-term follow-up (BMI: MD 0.03, 95% CI -0.11 to 0.16; 16 studies, 22,098 participants; zBMI: MD -0.02, 95% CI -0.06 to 0.01; 22 studies, 23,594 participants; low-certainty evidence). Nineteen studies (27,882 participants; low-certainty evidence) reported data on serious adverse events: four studies reported occurrence of serious adverse events (e.g. injuries, low levels of extreme dieting behaviour); 15 studies reported no effect. Heterogeneity was apparent in the results for all outcomes at the three follow-up times, which could not be explained by the main setting of the interventions (school, home, school and home, other), country income status (high-income versus non-high-income), participants' socioeconomic status (low versus mixed) and duration of the intervention. Most studies excluded children with a mental or physical disability. AUTHORS' CONCLUSIONS The body of evidence in this review demonstrates that a range of school-based 'activity' interventions, alone or in combination with dietary interventions, may have a modest beneficial effect on obesity in childhood at short- and medium-term, but not at long-term follow-up. Dietary interventions alone may result in little to no difference. Limited evidence of low quality was identified on the effect of dietary and/or activity interventions on severe adverse events and health inequalities; exploratory analyses of these data suggest no meaningful impact. We identified a dearth of evidence for home and community-based settings (e.g. delivered through local youth groups), for children living with disabilities and indicators of health inequities.
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Affiliation(s)
- Francesca Spiga
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Annabel L Davies
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Eve Tomlinson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Theresa Hm Moore
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Sarah Dawson
- NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Katie Breheny
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jelena Savović
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Yang Gao
- Department of Sport, Physical Education and Health, Hong Kong Baptist University, Kowloon, Hong Kong
| | - Sophie M Phillips
- Department of Sport and Exercise Science, Durham University, Durham, UK
- Fuse - Centre for Translational Research in Public Health, Newcastle upon Tyne, UK
- Child Health and Physical Activity Laboratory, School of Occupational Therapy, Western University, London, Ontario, Canada
| | - Frances Hillier-Brown
- Fuse - Centre for Translational Research in Public Health, Newcastle upon Tyne, UK
- Human Nutrition Research Centre and Population Health Sciences Institute, University of Newcastle, Newcastle, UK
| | - Rebecca K Hodder
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, The University of Newcastle, Callaghan, Australia
| | - Luke Wolfenden
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- School of Medicine and Public Health, The University of Newcastle, Callaghan, Australia
| | - Julian Pt Higgins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
- NIHR Bristol Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Carolyn D Summerbell
- Department of Sport and Exercise Science, Durham University, Durham, UK
- Fuse - Centre for Translational Research in Public Health, Newcastle upon Tyne, UK
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Wilson OWA, Thai M, Williams L, Nutter S, Myre M, Russell-Mayhew S. A scoping review of school-based anthropometric measurement. Obes Rev 2023; 24:e13610. [PMID: 37653624 DOI: 10.1111/obr.13610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 05/15/2023] [Accepted: 05/21/2023] [Indexed: 09/02/2023]
Abstract
Though anthropometric measurement (AM) frequently occurs in school settings, it is not without risks to child wellbeing. The aim of this scoping review was to examine how AM in school settings takes place and is reported on to make recommendations on best practices. We identified and extracted data from 440 studies published since 2005 that conducted AM in school (pre-school through secondary/high school) settings. Privacy and sensitivity of AM were unclear in over 90% of studies. Thirty-one studies (7.0%) reported protecting student privacy, while nine (2.0%) reported public measurement. Only five studies reported sensitivity regarding AM (1.1%). Exactly who conducted AM was not specified in 201 studies (45.7%). Sixty-nine studies did not provide a weight status criteria citation (19.2%), and 10 used an incorrect citation (2.7%). In summary, serious shortcomings in the reporting of how AM is conducted and by whom, along with details concerning weight status classification, are evident. There is considerable room for improvement regarding the reporting of key methodological details. We propose best practices for AM in school settings, which also double as conditions that should be met before AM takes place in school settings.
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Affiliation(s)
- Oliver W A Wilson
- Werklund School of Education, University of Calgary, Calgary, Alberta, Canada
- Te Hau Kori, Te Wāhanga Tātai Hauora Faculty of Health, Te Herenga Waka, Victoria University of Wellington, Wellington, New Zealand
| | - Michella Thai
- Werklund School of Education, University of Calgary, Calgary, Alberta, Canada
| | - Lindsay Williams
- Werklund School of Education, University of Calgary, Calgary, Alberta, Canada
| | - Sarah Nutter
- Department of Educational Psychology and Leadership Studies, University of Victoria, Victoria, British Columbia, Canada
| | - Maxine Myre
- Werklund School of Education, University of Calgary, Calgary, Alberta, Canada
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Gao L, Zhu J, Wang L, Wen LM, Chen Z, Zhao B, Wang W, Wang Y. Interactions between Self-Perceived Weight Status and Lifestyle Behaviors and Their Associations with Childhood Obesity: Results from the Childhood Obesity Study in China Mega-Cities. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:9921. [PMID: 36011552 PMCID: PMC9408598 DOI: 10.3390/ijerph19169921] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/03/2022] [Accepted: 08/09/2022] [Indexed: 06/15/2023]
Abstract
This study investigated the interactions between self-perceived weight status and lifestyle behaviors, and their associations with childhood obesity among school children. Methods: Cross-sectional study data from a nationwide sample of 3258 participants (aged 8-15 years old) during 2015-2017 were used. Self-perceived weight status and lifestyle factors (dietary intake and physical activity) were assessed using self-administered questionnaires. Multivariable mixed-effects models tested the effect of interactions between weight self-perception and behavioral factors on overweight and obesity (ow/ob). Results: Overall ow/ob prevalence based on BMI was 30.9% (38.5% for boys, 23.0% for girls). Based on self-perceived weight status, ow/ob prevalence was 37.7% (35.8% for boys, 39.7% for girls). 41.2% of boys and 25.9% of girls underestimated their actual weight status. The interaction between self-perceived weight status and meat consumption was associated with ow/ob in boys, while the interaction between self-assessed weight status and protein foods and sedentary lifestyle were associated with ow/ob in girls. The attributable proportions of these three factors were 39.8%, 48.2%, and 34.6%, respectively. Conclusions: The self-perceived weight status was different from their actual weight status in children. The interactions between self-perceived weight status and lifestyle behaviors were associated with ow/ob. Health promotion programs that empower children to have appropriate self-awareness of weight status, eating, and physical activity behaviors need to be developed and implemented.
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Affiliation(s)
- Liwang Gao
- Center for Non-Communicable Disease Management, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing 100045, China
- Global Health Institute, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
| | - Jiang Zhu
- Global Health Institute, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
| | - Liang Wang
- Department of Public Health, Robbins College of Health and Human Sciences, Baylor University, Waco, TX 76798, USA
| | - Li Ming Wen
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney 2006, Australia
| | - Zhuo Chen
- Department of Health Policy and Management, College of Public Health, University of Georgia, Athens, GA 30602, USA
- School of Economics, Faculty of Humanities and Social Sciences, University of Nottingham Ningbo, Ningbo 315199, China
| | - Bingtong Zhao
- Global Health Institute, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
| | - Weidong Wang
- Department of Sociology, School of Sociology and Population Studies, Renmin University of China, Beijing 100034, China
| | - Youfa Wang
- Global Health Institute, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
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The effects of a one year school-based comprehensive lifestyle intervention among Chinese kids against obesity (CLICK-obesity) in Nanjing, China. J Public Health (Oxf) 2021. [DOI: 10.1007/s10389-021-01646-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Liu W, He MZ, Wang Y, Wang Y, Zhou Y, Wu M, Tang Z, Dai Y, Yuan B, Zhen S, Cheskin LJ. Differences in health-related behaviors between middle school, high school, and college students in Jiangsu province, China. Asia Pac J Clin Nutr 2017; 26:731-737. [PMID: 28582827 PMCID: PMC6548715 DOI: 10.6133/apjcn.072016.06] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
BACKGROUND AND OBJECTIVES Increasing rates of obesity among Chinese adolescents has become a major public health concern in recent years. Studies have shown that factors such as food choices, physical activity, and screen time play important roles in fostering obesity. We examined a number of biological and social determinants that influence these factors. To determine whether dietary behavior, physical activity, and screen time varied among students in different stages of their education. METHODS AND STUDY DESIGN Students in 13 cities across Jiangsu Province completed an anonymous survey assessing demographics and various health-related behaviors in a controlled setting. The survey population ranged from middle school students to undergraduates. 55,361 surveys were returned, and 46,611 (84.2%) were usable for the analysis. Multiple linear regression models were used to investigate the relationship between four behavioral factors (dietary behavior, screen time, physical activity, and moderate exercise) and seven predictors (gender, age, BMI, mother's education, nearsightedness, allowance, and geographic region). RESULTS Baseline characteristics of the survey population analyzed by education level (middle school, high school, college and beyond) showed moderate differences in demographics among the three groups. Physical activity, moderate exercise, and dietary behavior decreased with educational level, while screen time increased. All predictors in the four considered regression models were statistically significant. CONCLUSIONS This unique, large-scale survey of Chinese students in a region of contrasting economic development revealed numerous relationships between health-related diet and physical-activity, region, and education level. These findings can inform the development of measures to counteract the rise of obesity in China.
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Affiliation(s)
- Weina Liu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Mike Z He
- Columbia University Mailman School of Public Health, New York, USA
| | - Yunle Wang
- University of Washington - Seattle School of Public Health, Seattle, Washington, USA
| | - Yan Wang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yonglin Zhou
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Ming Wu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Zhen Tang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yue Dai
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Baojun Yuan
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Shiqi Zhen
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China. ;
| | - Lawrence J Cheskin
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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de Villiers A, Steyn NP, Draper CE, Hill J, Gwebushe N, Lambert EV, Lombard C. Primary School Children's Nutrition Knowledge, Self-Efficacy, and Behavior, after a Three-Year Healthy Lifestyle Intervention (HealthKick). Ethn Dis 2016; 26:171-80. [PMID: 27103767 DOI: 10.18865/ed.26.2.171] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVE This study aimed to evaluate the effects of HealthKick(HK), a healthy lifestyle intervention, on nutrition knowledge, behavior, and dietary self-efficacy of school children in the Western Cape Province of South Africa. DESIGN A three-year cluster randomized control trial at primary schools in low socioeconomic settings with a baseline study in 2009 and follow-up in 2010 and 2011. PARTICIPANTS Participants were Grade four children (n=500) at eight schools in the intervention group and at eight schools in the control group (n=498). METHODS An action planning process was followed with educators whereby they identified their own school health priorities and ways to address them. Schools were provided with nutrition resources, including curriculum guidelines and the South African food-based dietary guidelines. Children completed a questionnaire comprising nutrition knowledge, self-efficacy and behavioral items. RESULTS The intervention significantly improved the knowledge of the intervention group at the first (mean difference =1.88, 95%CI: .32 to 3.43, P=.021) and second follow-up (mean difference=1.92, 95%CI: .24 to 3.60, P=.031) compared with the control group. The intervention effect for self-efficacy was not significant at the first follow-up (mean difference=.32, 95%CI: -.029 to .94, P=.281) whereas a significant effect was observed at the second follow-up (mean difference=.71, 95%CI: .04 to 1.38, P=.039). There were no significant differences between the intervention and control groups for nutritional behavior scores at any of the follow-up time points. CONCLUSIONS The HK intervention improved nutrition knowledge and self-efficacy significantly in primary schoolchildren; however, it did not improve their eating behavior.
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Affiliation(s)
- Anniza de Villiers
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town
| | - Nelia P Steyn
- Division of Nutrition, Faculty of Health Sciences, University of Cape Town, Cape Town
| | - Catherine E Draper
- Division of Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, University of Cape Town
| | - Jillian Hill
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town
| | - Nomonde Gwebushe
- Biostatistics Unit, South African Medical Research Council, Cape Town
| | - Estelle V Lambert
- Division of Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, University of Cape Town
| | - Carl Lombard
- Biostatistics Unit, South African Medical Research Council, Cape Town
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Effectiveness of a Randomized Controlled Lifestyle Intervention to Prevent Obesity among Chinese Primary School Students: CLICK-Obesity Study. PLoS One 2015; 10:e0141421. [PMID: 26510135 PMCID: PMC4625022 DOI: 10.1371/journal.pone.0141421] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2014] [Accepted: 10/04/2015] [Indexed: 01/21/2023] Open
Abstract
Background Childhood obesity has been increasing rapidly worldwide. There is limited evidence for effective lifestyle interventions to prevent childhood obesity worldwide, especially in developing countries like China. The objective of this study was to assess the effectiveness of a school-based multi-component lifestyle childhood obesity prevention program (the CLICK-Obesity study) in Mainland China. Methods A cluster randomized controlled trial was developed among grade 4 students from 8 urban primary schools (638 students in intervention, 544 as control) in Nanjing City, China. Students were randomly allocated to the control or intervention group at school-level. A one-year multi-component intervention program (classroom curriculum, school environment support, family involvement and fun programs/events) together with routine health education was provided to the intervention group, while the control group received routine health education only. The main outcome variables assessed were changes in body mass index, obesity occurrence, obesity-related lifestyle behaviors and knowledge. Results Overall, 1108 (93.7%) of the 1182 enrolled students completed the intervention study. The intervention group had a larger marginal reduction than did the control group in overall mean BMI value (-0.32±1.36 vs. -0.29±1.40, p = 0.09), although this was not significant. Compared with the control group, the intervention group was more likely to decrease their BMI (OR = 1.44, 95%CI = 1.10, 1.87) by 0.5 kg/m2 or above, increase the frequency of jogging/running (OR = 1.55, 95%CI = 1.18, 2.02), decrease the frequency of TV/computer use (OR = 1.41, 95%CI = 1.09, 1.84) and of red meat consumption (OR = 1.50, 95%CI = 1.15, 1.95), change commuting mode to/from school from sedentary to active mode (OR = 2.24, 95%CI = 1.47, 3.40), and be aware of the harm of selected obesity risk factors. Conclusions The school-based lifestyle intervention program was practical and effective in improving health behaviors and obesity-related knowledge for children in China. This study provides important policy implications on school-based intervention programs for modifications of obesity-related lifestyles. Trial Registration Chinese Clinical Trial Registry ChiCTR-ERC-11001819
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He F, Liu J. Prevalence of obesity among primary students from 2009 to 2014 in China: an update meta-analysis. Int J Clin Exp Med 2014; 7:5348-5352. [PMID: 25664042 PMCID: PMC4307489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2014] [Accepted: 09/20/2014] [Indexed: 06/04/2023]
Abstract
In recent years, obesity has become the major public health problems worldwide. The aim of the meta-analysis is to estimate the overall prevalence of obesity among children and adolescents in China, Publications between 2009 and 2014 on the obesity prevalence among primary school students in China were retrieved from PubMed, CNKI and Wanfang databases. After evaluation of the quality of the articles, 20 papers were finally included in our study. Meta-analysis findings showed that the pooled prevalence of obesity in primary school students is 10.4% (95% CI: 7.8%-13.8%). Our results indicated that the obesity prevalence status in China was still troublesome, effective and practical measures should be taken to control the the situation.
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Affiliation(s)
- Falin He
- Natiinal Center for Clinical Laboratories, Beijing Hospital, Ministry of HealthBeijing 100730, China
| | - Jialin Liu
- Daxing Maternal & Child Care HospitalBeijing 100730, China
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