Abstract: Objective To analyze the patterns and determinants of diagnostic delays among pulmonary tuberculosis (PTB) patients in Zibo City from 2005 to 2023, providing evidence for improving case detection efficiency. Methods Data were extracted from the Infectious Disease Surveillance System of China Disease Control and Prevention Information System, encompassing 24, 792 PTB cases registered in Zibo City (2005~2023). Variables included demographic characteristics, diagnostic results, treatment classification, patient source, initial diagnosis location, registration date, and key time intervals (symptom onset, first medical consultation, and confirmed diagnosis). Temporal trends in delay rates were analyzed using curve regression. Univariate comparisons and multivariable logistic regression identified factors associated with diagnostic delays. Results The median total delay interval was 40 (IQR: 20~77) days, predominantly attributable to patient-related delays (76.95%). The annual delay rate averaged 65.87%, exhibiting an initial rise followed by a decline (Cubic regression: R²=0.787, F=18.501, P<0.001), with sustained reductions post-2020. Multivariate logistic regression analysis showed that age 45~<65 years (OR=1.115), farmers/fishermen/migrant workers(OR=1.412), industrial workers (OR=1.299), unemployed/retired individuals (OR=1.581), tracking source (OR=2.677), local county (OR=1.360) and other counties (OR=2.208), initial treatment(OR=1.290) and pathogen positivity (OR=1.086) are risk factors for delayed diagnostic delays.While the protective factors are age <45 years (OR=0.839, 0.879), with sources of health check-up (OR=0.177), active screening (OR=0.328), referrals (OR=0.632), and clinician-initiated transfers (OR=0.757). Conclusions Diagnostic delays among PTB patients in Zibo remain prevalent and severe, primarily driven by prolonged intervals to first medical consultation. Targeted interventions—particularly health education and active case-finding strategies for high-risk populations—are urgently needed to enhance healthcare-seeking behavior and reduce delays.

Key words: Tuberculosis, pulmonary, Patient delay, Delayed diagnosis, Factor analysis