Background: Obesity and periodontitis are linked through inflammatory and metabolic pathways, and the oral microbiota may mediate this interaction. Age-related changes in immunity, salivary function, and cumulative exposure may modify obesity-associated periodontal dysbiosis. Objective: We sought to synthesize the potential for age-related differences in the oral microbiota of adult obese patients with periodontitis and assess the strength of current literature in supporting age-specific interpretations. Methods: A systematic search of PubMed/MEDLINE, Scopus, and Embase identified 1088 records. After screening and full-text assessment, 50 studies that met the criteria for focused qualitative synthesis remained. Within that review corpus, 10 representative adult human studies provided the most direct evidence linking obesity or overweight, periodontal phenotype, oral microbiota, and age-relevant interpretation. Risk of bias was appraised with the Newcastle–Ottawa Scale. Results: Direct head-to-head microbiome comparisons between younger and older obese adults with periodontitis are rare. Direct evidence links obesity to greater periodontal inflammatory burden, enrichment of classical periopathogens and bridging taxa, and shifts in community structure. Contextual aging studies have suggested that older adults may more often harbor lower-diversity, persistence-oriented communities enriched in stress-tolerant, proteolytic, or opportunistic taxa, whereas younger obese adults more often show inflammation-amplifying consortia enriched in classical periopathogens and bridging taxa. However, these patterns remain largely hypothesis-generating because the evidence base is heterogeneous and predominantly cross-sectional. Conclusions: Age likely modifies the obesity–periodontitis–microbiota axis, but direct comparative evidence on adults remains limited. The current literature supports cautious age-aware interpretation within a systematic review framework rather than definitive age-specific microbial signatures or treatment algorithms.
Beresescu et al. (Thu,) studied this question.