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      The Prevalence of Obesity Among Children With Type 2 Diabetes : A Systematic Review and Meta-analysis

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          Key Points

          Question

          What is the prevalence of obesity in pediatric patients with type 2 diabetes (T2D)?

          Findings

          This systematic review and meta-analysis of 53 studies including 8942 participants found that 75.27% of children with T2D had obesity, and 77.24% had obesity at diagnosis. Male participants had significantly higher odds of obesity than female participants, and Asian participants had the lowest prevalence of obesity compared with other racial groups.

          Meaning

          In this study, not all pediatric patients with T2D had obesity; further studies are needed to elucidate the mechanisms beyond obesity driving this condition in children.

          Abstract

          This systematic review and meta-analysis evaluates the global prevalence of obesity in pediatric type 2 diabetes, examines the association of sex and race with obesity risk, and assesses the association of obesity with glycemic control and dyslipidemia.

          Abstract

          Importance

          The childhood obesity epidemic is presumed to drive pediatric type 2 diabetes (T2D); however, the global scale of obesity in children with T2D is unknown.

          Objectives

          To evaluate the global prevalence of obesity in pediatric T2D, examine the association of sex and race with obesity risk, and assess the association of obesity with glycemic control and dyslipidemia.

          Data Sources

          MEDLINE, Embase, CINAHL, Cochrane Library, and Web of Science were searched from database inception to June 16, 2022.

          Study Selection

          Observational studies with at least 10 participants reporting the prevalence of obesity in patients with pediatric T2D were included.

          Data Extraction and Synthesis

          Following the Meta-analysis of Observational Studies in Epidemiology reporting guideline, 2 independent reviewers in teams performed data extraction and risk of bias and level of evidence analyses. The meta-analysis was conducted using a random-effects model.

          Main Outcomes and Measures

          The primary outcomes included the pooled prevalence rates of obesity in children with T2D. The secondary outcomes assessed pooled prevalence rates by sex and race and associations between obesity and glycemic control and dyslipidemia.

          Results

          Of 57 articles included in the systematic review, 53 articles, with 8942 participants, were included in the meta-analysis. The overall prevalence of obesity among pediatric patients with T2D was 75.27% (95% CI, 70.47%-79.78%), and the prevalence of obesity at diabetes diagnosis among 4688 participants was 77.24% (95% CI, 70.55%-83.34%). While male participants had higher odds of obesity than female participants (odds ratio, 2.10; 95% CI, 1.33-3.31), Asian participants had the lowest prevalence of obesity (64.50%; 95% CI, 53.28%-74.99%), and White participants had the highest prevalence of obesity (89.86%; 95% CI, 71.50%-99.74%) compared with other racial groups. High heterogeneity across studies and varying degrees of glycemic control and dyslipidemia were noted.

          Conclusions and Relevance

          The findings of this systematic review and meta-analysis suggest that obesity is not a universal phenotype in children with T2D. Further studies are needed to consider the role of obesity and other mechanisms in diabetes genesis in this population.

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          Most cited references130

          • Record: found
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          Conducting Meta-Analyses inRwith themetaforPackage

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            Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group.

            Because of the pressure for timely, informed decisions in public health and clinical practice and the explosion of information in the scientific literature, research results must be synthesized. Meta-analyses are increasingly used to address this problem, and they often evaluate observational studies. A workshop was held in Atlanta, Ga, in April 1997, to examine the reporting of meta-analyses of observational studies and to make recommendations to aid authors, reviewers, editors, and readers. Twenty-seven participants were selected by a steering committee, based on expertise in clinical practice, trials, statistics, epidemiology, social sciences, and biomedical editing. Deliberations of the workshop were open to other interested scientists. Funding for this activity was provided by the Centers for Disease Control and Prevention. We conducted a systematic review of the published literature on the conduct and reporting of meta-analyses in observational studies using MEDLINE, Educational Research Information Center (ERIC), PsycLIT, and the Current Index to Statistics. We also examined reference lists of the 32 studies retrieved and contacted experts in the field. Participants were assigned to small-group discussions on the subjects of bias, searching and abstracting, heterogeneity, study categorization, and statistical methods. From the material presented at the workshop, the authors developed a checklist summarizing recommendations for reporting meta-analyses of observational studies. The checklist and supporting evidence were circulated to all conference attendees and additional experts. All suggestions for revisions were addressed. The proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion. Use of the checklist should improve the usefulness of meta-analyses for authors, reviewers, editors, readers, and decision makers. An evaluation plan is suggested and research areas are explored.
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              A basic introduction to fixed-effect and random-effects models for meta-analysis.

              There are two popular statistical models for meta-analysis, the fixed-effect model and the random-effects model. The fact that these two models employ similar sets of formulas to compute statistics, and sometimes yield similar estimates for the various parameters, may lead people to believe that the models are interchangeable. In fact, though, the models represent fundamentally different assumptions about the data. The selection of the appropriate model is important to ensure that the various statistics are estimated correctly. Additionally, and more fundamentally, the model serves to place the analysis in context. It provides a framework for the goals of the analysis as well as for the interpretation of the statistics. In this paper we explain the key assumptions of each model, and then outline the differences between the models. We conclude with a discussion of factors to consider when choosing between the two models. Copyright © 2010 John Wiley & Sons, Ltd. Copyright © 2010 John Wiley & Sons, Ltd.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                15 December 2022
                December 2022
                15 December 2022
                : 5
                : 12
                : e2247186
                Affiliations
                [1 ]Department of Pediatrics, McMaster University, Hamilton, Ontario, Canada
                [2 ]Division of Pediatric Endocrinology, McMaster Children’s Hospital, Hamilton, Ontario, Canada
                [3 ]Michael G. De Groote School of Medicine, McMaster University, Hamilton, Ontario, Canada
                [4 ]Health Sciences Library, McMaster University, Hamilton, Ontario, Canada
                [5 ]Health Science University, Zeynep Kamil Maternity and Children Hospital, Pediatric Endocrinology Clinic, Istanbul, Turkey
                [6 ]College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Division of Endocrinology, Department of Pediatrics, Ministry of the National Guard Health Affairs, Riyadh, Saudi Arabia
                [7 ]Division of Pediatric Endocrinology, Department of Pediatrics, King Abdullah bin Abdulaziz University Hospital, Princess Noura University, Riyadh, Saudi Arabia
                [8 ]Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
                [9 ]Department of Anesthesia, McMaster University, Hamilton, Ontario, Canada
                [10 ]Centre for Evaluation of Medicines, St Joseph’s Healthcare, Hamilton, Ontario, Canada
                [11 ]Biostatistics Unit, St Joseph’s Healthcare, Hamilton, Ontario, Canada
                Author notes
                Article Information
                Accepted for Publication: October 30, 2022.
                Published: December 15, 2022. doi:10.1001/jamanetworkopen.2022.47186
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Cioana M et al. JAMA Network Open.
                Corresponding Author: M. Constantine Samaan, MD, MSc, Division of Pediatric Endocrinology, McMaster Children’s Hospital, 1280 Main St W, 3A-57, Hamilton, Ontario L8S 4K1, Canada ( samaanc@ 123456mcmaster.ca ).
                Author Contributions: Ms Cioana and Dr Samaan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Cioana, Chen, Rivas, Banfield, Thabane, Samaan.
                Acquisition, analysis, or interpretation of data: Cioana, Deng, Nadarajah, Hou, Qiu, Chen, Banfield, Toor, Zhou, Guven, Alfaraidi, Alotaibi, Thabane, Samaan.
                Drafting of the manuscript: Cioana, Nadarajah, Rivas, Guven, Alfaraidi, Samaan.
                Critical revision of the manuscript for important intellectual content: Cioana, Deng, Nadarajah, Hou, Qiu, Chen, Banfield, Toor, Zhou, Alfaraidi, Alotaibi, Thabane, Samaan.
                Statistical analysis: Cioana, Deng, Nadarajah, Thabane, Samaan.
                Administrative, technical, or material support: Nadarajah, Qiu, Rivas, Banfield, Guven, Alotaibi, Samaan.
                Supervision: Banfield, Alfaraidi, Thabane, Samaan.
                Conflict of Interest Disclosures: None reported.
                Data Sharing Statement: See Supplement 2.
                Meeting Presentation: Data were presented as a poster at the Diabetes Canada Meeting; October 28 to 30, 2020; virtual.
                Article
                zoi221332
                10.1001/jamanetworkopen.2022.47186
                9856349
                36520430
                ac77ecea-4f6b-492f-9d47-2328b233810d
                Copyright 2022 Cioana M et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 19 July 2022
                : 30 October 2022
                Categories
                Research
                Original Investigation
                Online Only
                Diabetes and Endocrinology

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