Acute appendicitis (AA) remains a leading surgical emergency, yet specific intraluminal dietary triggers influencing appendiceal inflammation are poorly understood (1). Composite indices like the Dietary Guideline Index (DGI), derived from the CSIRO Short Food Frequency Questionnaire (SFFQ), are widely used to measure overall diet quality (2,3). However, aggregate diet scales fail to show individual dietary risks, hiding the distinct localized triggers that cause acute appendiceal inflammation (1,2). A cross-sectional case-control study using a modified 14-indicator DGI framework, investigated covariate relationships between the risk of developing AA and the overall diet quality, specific food groups, and socio-demographic parameters within an Australian metropolitan cohort. It was hypothesized that patients with clinical AA would exhibit significantly distinct dietary patterns compared to healthy controls. Clinical patients with histopathologically confirmed AA (n = 87) were matched against healthy community controls without a history of the disease (n = 93) in South-East Queensland. We quantified 12-month dietary intakes using face-to-face CSIRO Short Food Frequency Questionnaires (SFFQ). Diet quality was scored using the Diet Quality Index (DGI) framework, excluding discretionary salt due to questionnaire design constraints. Mann-Whitney U tests evaluated group variances for continuous composite scores. Individual item-level components meeting national thresholds were analysed using Pearson's chi-square or Fisher's exact tests to measure categorical independence. Multivariable linear regression examined baseline socio-demographic predictors of total DGI performance, while fully adjusted binary logistic regression models assessed independent AA risk adjustments. Total composite DGI scores were statistically indistinguishable between AA cases and healthy controls (9.37 ± 1.78 vs 9.46 ± 1.74; p = 0.534). However, demographic stratification unmasked distinct dietary differences. Male AA cases consumed significantly more added sugar than male controls (5.3 ± 0.7 vs 7.4 ± 0.7; p = 0.034). Conversely, female AA cases had a significantly higher alcohol intake than female controls (8.2 ± 0.6 vs 9.8 ± 0.1; p = 0.005). Among non-Caucasian participants, AA cases had a significantly lower intake of core grains and cereals than healthy controls (4.3 ± 0.7 vs 5.8 ± 0.4; p = 0.044). In conclusion, AA risk is driven by specific, sex- and ethnic-linked dietary hazards rather than overall diet quality. A higher risk of AA is directly associated with elevated added sugar intake in males, increased alcohol consumption in females, and low core grain intake in non-Caucasian populations than in demographic-matched healthy controls. Targeted prevention strategies must focus on these specific food-level hazards within distinct demographic groups.