Overweight and obesity prevalence in individuals with Down syndrome reaches 22% across mixed-age cohortsOverweight and Obesity Rates are High Among People with Down Syndrome

Objective. This systematic review and meta-analysis synthesised the global prevalence of overweight and obesity in people with Down syndrome (DS) across the lifespan, characterised determinants of excess adiposity, and examined associations with adverse cardiometabolic outcomes. Methods. Six databases were searched without date or language restriction. Two independent reviewers screened studies, extracted data, and assessed quality using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. Prevalence was pooled using a random-effects logit model. A pre-specified subgroup analysis by age band was conducted. Publication bias was assessed with Egger's test and certainty of evidence with Grading of Recommendations Assessment, Development and Evaluation (GRADE). Results. Twenty-six studies (7,840 individuals; 14 countries) were included. The pooled prevalence was 18% (95% CI 15-22%) in children and adolescents, 36% (95% CI 26-47%) in adults, and 30% (95% CI 20-43%) in mixed-age cohorts; the test for subgroup differences was significant. The overall pooled prevalence was 22% (95% CI 18-26%; prediction interval 7-53%; I^2 = 95.3%). No publication bias was detected (Egger's t = 0.39, p = 0.6964). DS-specific growth charts yielded estimates 14-37 percentage points lower than general-population references applied to the same cohorts. Obesity more than doubled obstructive sleep apnea risk (RR 2.4; 95% CI 1.34-4.34) and non-alcoholic fatty liver disease was present in 82% of obese versus 45% of non-obese children with DS. GRADE certainty was Moderate for prevalence estimates. Conclusions. Overweight and obesity in DS are highly prevalent, age-progressive, and substantially exceed general-population rates at every life stage. Roughly one in five people with DS is affected overall, rising to more than one in three adults. The reference chart applied is the single largest source of heterogeneity in reported estimates. Cardiometabolic surveillance, adapted lifestyle interventions, and primary prevalence research from low- and middle-income countries are the highest-priority gaps.