**Background:** Periodontal disease affects the supporting tissues of teeth and can lead to tooth loss if untreated. While classic risk factors include periodontal pathogens, smoking, and poor oral hygiene, diet quality is increasingly recognized as a modifiable factor influencing periodontal health through inflammatory and immune pathways. However, studies specifically targeting middle-aged and older adults (≥40 years), in whom both chronic disease and periodontal disease prevalence increase, are lacking. This study aimed to evaluate the relationship between diet quality, measured by the Korea Healthy Eating Index (KHEI), and periodontal disease in this population.
**Methods:** Data were drawn from the 7th Korea National Health and Nutrition Examination Survey (KNHANES, 2016–2018), a nationally representative cross-sectional survey using two-step stratified cluster sampling. From 16,489 total participants, 6,954 aged <40 years were excluded, along with 508 without periodontal examination and 1,092 without KHEI data, yielding a final sample of 7,935 individuals. Diet quality was assessed using the KHEI, which comprises 14 items across three domains: recommended food and adequacy evaluation (8 items, max 50 points), moderation evaluation (3 items, max 30 points), and energy intake balance evaluation (3 items, max 15 points), for a total possible score of 100. Periodontal disease was defined as a Community Periodontal Index (CPI) score ≥3 (periodontal pocket depth ≥4 mm). Covariates included sociodemographic characteristics, oral health behaviors, and health status (hypertension, diabetes, obesity). Complex samples chi-square tests, t-tests, and logistic regression were performed. Model I was unadjusted; Model II adjusted for sex, age, household income, education level, marital status, tooth brushing frequency, use of oral hygiene devices, dental examination within one year, smoking, hypertension, diabetes, and obesity.
**Key Results:** In both sexes, periodontal disease prevalence was higher among those aged 60–69 and ≥70, with lower household income, lower education, widowed/divorced status, brushing <3 times/day, not using oral hygiene devices, no dental exam within one year, current smoking, and having hypertension or diabetes (all p<0.05). Obesity was associated with higher periodontal disease prevalence only in females (p<0.001). In males, those with periodontal disease had significantly lower mean scores for total fruit intake (2.05 vs 2.27, p=0.021), vegetable intake excluding kimchi/pickles (3.32 vs 3.53, p=0.002), and meat/fish/eggs/legumes intake (6.90 vs 7.29, p=0.002), and a higher saturated fatty acid score (8.49 vs 8.07, p=0.001). In females, those with periodontal disease had lower total KHEI scores (66.28 vs 67.69, p=0.004), lower meat/fish/eggs/legumes (6.47 vs 6.79, p=0.012), lower milk/dairy (2.92 vs 3.52, p<0.001), and lower carbohydrate and fat energy intake ratio scores (1.92 vs 2.40 and 2.72 vs 3.25, both p<0.001). In logistic regression Model I, low total KHEI (<67) was associated with 1.21 times higher odds of periodontal disease (95% CI 1.08–1.36, p=0.001), low adequacy score (<34) with 1.20 times higher odds (95% CI 1.07–1.36, p=0.002), and low energy intake balance score (<9) with 1.39 times higher odds (95% CI 1.25–1.54, p<0.001). In the fully adjusted Model II, only low energy intake balance score remained significant (AOR 1.15, 95% CI 1.02–1.29, p=0.019).
**Clinical Implications:** This study demonstrates that poor diet quality, particularly imbalanced energy intake from carbohydrates and fats, is independently associated with a modestly increased risk of periodontal disease in adults aged ≥40 years, even after adjusting for sociodemographic factors, oral health behaviors, and comorbidities. The findings support the role of dietary counseling as part of comprehensive periodontal care. Dental professionals should assess patients' dietary patterns and provide guidance on balanced macronutrient intake to support periodontal health. However, given the cross-sectional design, causal inference is limited, and the use of CPI alone (without clinical attachment loss measurement) may lead to misclassification. Future longitudinal studies are needed to confirm these associations.