A systematic review and meta‐analysis estimating the population prevalence of comorbidities in children and adolescents aged 5 to 18 years. (24th July 2019)

• Record Type: Journal Article
• Authors: Sharma, Vishal; Coleman, Susanne; Nixon, Jane; Sharples, Linda; Hamilton‐Shield, Julian; Rutter, Harry; Bryant, Maria
• Is Part Of: Obesity reviews. Volume 20:Number 10(2019)
• Page Start: 1341
• Page End: 1349
• Publication Date: 2019-07-24
• Subjects: childhood obesity -- comorbidities -- population prevalence -- systematic review; Obesity -- Periodicals; 616.398005
• DOI: 10.1111/obr.12904
• Languages: English
• ISSNs: 1467-7881

Abstract

Summary: Evidence for the health impact of obesity has largely focussed on adults. We estimated the population prevalence and prevalence ratio of obesity‐associated comorbidities in children and adolescents aged 5 to 18 years. Five databases were searched from inception to 14 January 2018. Population‐based observational studies reporting comorbidity prevalence by weight category (healthy weight/overweight/obese) in children and adolescents aged 5 to 18 years from any country were eligible. Comorbidity prevalence, stratified by weight category, was extracted and prevalence ratios (relative to healthy weight) estimated using random effects meta‐analyses. Of 9183 abstracts, 52 eligible studies (1 553 683 participants) reported prevalence of eight comorbidities or risk markers including diabetes and nonalcoholic fatty liver disease (NAFLD). Evidence for psychological comorbidities was lacking. Meta‐analyses suggested prevalence ratio for prediabetes (fasting glucose ≥ 100 mg/dL) for those with obesity relative to those of a healthy weight was 1.4 (95% confidence interval [CI], 1.2‐1.6) and for NAFLD 26.1 (9.4‐72.3). In the general population, children and adolescents with overweight/obesity have a higher prevalence of comorbidities relative to those of a healthy weight. This review provides clinicians with information when assessing children and researchers a foundation upon which to build a comprehensive dataset to understand the health consequences of childhood obesity.