Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide, and atherosclerosis is the key factor promoting its development. Carotid intima-media thickening and the presence of carotid plaques are important indices of cardiovascular risk. In addition, inflammation is a major and complex factor in the development of atherosclerosis. The relationships between carotid atherosclerosis and certain inflammatory markers have rarely been studied in healthy individuals. Therefore, we aimed to investigate the associations between subclinical carotid atherosclerosis and various inflammatory biomarkers in a large Caucasian population free of evident CVD. In addition to recording study participants' demographic characteristics, anthropometric characteristics, and atherosclerotic risk factors, laboratory tests were performed to measure levels of hemoglobin A1c (HbA1c), high-sensitivity C-reactive protein, and inflammatory cytokines/chemokines, including interleukin (IL)-1β, IL-6, IL-8, IL-10, IL-12p70, IL-17A, IL-18, IL-23, IL-33, interferon (IFN)-α2, IFN-γ, tumor necrosis factor-α, and monocyte chemoattractant protein (MCP)-1. This study included 264 asymptomatic individuals with a median age of 61.7 years (interquartile range, 54.5-67.5 years); 45.7% of participants were male. Participants were divided into two groups according to their carotid status: the normal carotid group, comprising 120 participants; and the pathological carotid group, comprising 144 participants. Compared with the normal carotid group, hypertension and diabetes mellitus were significantly more common and serum levels of HbA1c, IL-8, and MCP-1 were significantly higher in the pathological carotid group. Multivariate regression analysis revealed significant positive associations between pathological carotid findings and serum levels of IL-8 (highest tertile, OR: 2.4, p = 0.030) and MCP-1 (highest tertile, OR: 2.4, p = 0.040). Our results suggest that IL-8 and MCP-1 may serve as early indicators of subclinical atherosclerosis, thereby helping to identify individuals at increased risk of CVD before the onset of clinical symptoms.