Trend in risk of delay in diagnosis of new pulmonary tuberculosis in Northwest China from 2008 to 2017

BACKGROUND: With great changes over the past 10 years in China, especially the rapid economic development, population mobility, urbanization and aging, dynamic change on risk of delay, to our knowledge, has not been well studied in China. The study was to explore risk of delay in diagnosis of new pulmonary tuberculosis (PTB) and dynamic changes in risk of delay in Northwest China. METHODS: From January 1, 2008 to December 31, 2017, a total of 13,603 people with new PTB registered in Yulin city of Shaanxi province were included. The median delay time was estimated by Kaplan-Meier survival curve. Time delay curves of year-, gender-year-, age-year- and smear-year specific were examined using log-rank test. Two-level mixed-effects survival model was used to calculate the hazard ratio (HR) and 95% confidence interval (95%CI) for factors associated with diagnostic delay. Time delay was defined as time interval between the onset of PTB symptoms and being diagnosed. The outcome variable of interest was defined as “being diagnosed” in survival analysis. RESULTS: The 10-year delay time was 33 days (Interquartile Range, 16–65). Annual median delay time gradually decreased from 60 days to 33 days during the past 10 years. The probability that individuals were diagnosed since onset of PTB symptoms increased by 1.29 times in 2017 when compared to 2008. Female (Hazard Ratio (HR), 95%CI, 0.95(0.91–0.99)), age>45 years (HR, 95%CI, 0.87(0.82–0.93)) and smear positive (HR, 95%CI, 0.86(0.78–0.95)) were associated with increased risk of diagnostic delay over 10-year timespan. However, Age>45 years and smear positive showed trend to be protective factors in the past 5 years. CONCLUSIONS: Time and risk of delay in diagnosis of new PTB had declined over the past 10 years. However, more attentions should be paid to the fact that female still suffered from higher risk of diagnostic delay. We noted a potential reversal in traditional risk factors such as age>45 and smear positive. Those dynamic changes deserved further attention.