Abstract
BACKGROUND: Numerous systematic reviews and meta-analyses have been published that evaluate the association between periodontal disease and systemic diseases, many of which address similar topics. Moreover, their quality requires assessment. Therefore, we performed a cross-sectional analysis to examine the evidence on the relationship between periodontal disease and systemic diseases. METHODS: The PubMed, Embase, Web of Science, and the Cochrane Library databases were systematically searched to identify relevant systematic reviews and meta-analyses. Only studies that considered periodontal disease as the exposure factor and various systemic diseases as the outcome were included. The basic characteristics and pertinent data from the selected studies were extracted. The modified version of A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) was employed for quality assessment, while R software was used for statistical analysis. RESULTS: Among the 212 relevant systematic reviews and meta-analyses, 57 were finally included in our analysis. These studies involved 75 diseases and 81 disease-related outcomes, with cancer (19/81) being the most frequently addressed topic. Of the 81 outcomes, 67 demonstrated a significant association. Notably, the highest risk estimate was found for head and neck cancer [odds ratio (OR) = 3.17, 95% confidence interval (CI) 1.78 - 5.64], while the lowest was observed for premature rupture of the amniotic sac [relative risk (RR) = 1.10, 95% CI 1.08 - 1.12]. The methodological quality ratings indicated that approximately 71.93% of included studies were classified as "Critically low", with another 17.54% rated as "Low", and only about 10.53% categorized as "Moderate". CONCLUSIONS: Periodontal disease significantly elevates the risks associated with 15 cancer-related, 8 cardiovascular-related, 8 metabolic-related, and 5 neurological-related outcomes. However, the overall methodological quality of existing systematic reviews and meta-analyses is generally suboptimal and requires enhancement to generate higher-quality evidence in the future.