The association between obesity and triple-negative breast cancer (TNBC) prognosis has been equivocal, with considerable heterogeneity between and within studies. Recent meta-analyses report adverse associations with overall survival (OS) and disease-free survival (DFS) in TNBC. We update this evidence and examine study- and disease-specific sources of heterogeneity. A systematic search of four databases was conducted until February 22, 2023. Random-effects meta-analyses were used to pool hazard ratios (HR) for OS, DFS, and breast cancer-specific mortality (BCSM). Subgroup analyses examined sources of study heterogeneity. In meta-analyses of included studies (n = 33), significant associations were observed between excess body weight and worse OS (n = 24; HR = 1.20; 95%CI 1.20-1.34), DFS (n = 26; HR = 1.15; 1.05-1.27), and BCSM (n = 9; HR = 1.13; 1.00-1.27). In subgroup meta-analyses, significant inter-study survival differences were observed for study location (OS, DFS), time period of diagnoses (DFS), menopausal status (OS), and body mass index cut points examined (OS). Asian and European studies reported significant associations with OS (HR = 1.31; 1.11-1.54 and HR = 1.38; 1.00-1.89, respectively) and DFS (HR = 1.28; 1.07-1.54 and HR = 1.44; 1.13-1.84, respectively); however, no association was observed between obesity and TNBC prognosis in North American studies (OS: HR = 1.03; 0.89-1.19; DFS: HR = 1.05; 0.95-1.15). Location subgroup differences remained robust after excluding poor-quality studies. Post hoc analysis in the subset of studies reporting predominantly (≥ 70%) White sample showed no statistically significant associations for OS (HR = 1.13; 95%CI 0.96, 1.34), DFS (HR = 1.03; 95%CI 0.86, 1.23), or BCSM (HR = 1.08; 95%CI 0.91, 1.27). This study further confirms that obesity is associated with poor prognosis in TNBC and identified subgroups at higher risk. Ethnic differences in the association between excess body weight and TNBC are reported. Further exploration of study and patient characteristics is needed to properly understand the populations most at risk.