Temporal Trends in Notification and Mortality of Tuberculosis in China, 2004–2019: A Joinpoint and Age–Period–Cohort Analysis

Abstract

Tuberculosis (TB) remains a major public health problem in China and worldwide. In this article, we used a joinpoint regression model to calculate the average annual percent change (AAPC) of TB notification and mortality in China from 2004 to 2019. We also used an age–period–cohort (APC) model based on the intrinsic estimator (IE) method to simultaneously distinguish the age, period and cohort effects on TB notification and mortality in China. A statistically downward trend was observed in TB notification and mortality over the period, with AAPCs of −4.2% * (−4.9%, −3.4%) and −5.8% (−7.5%, −4.0%), respectively. A bimodal pattern of the age effect was observed, peaking in the young adult (aged 15–34) and elderly (aged 50–84) groups. More specifically, the TB notification risk populations were people aged 20–24 years and 70–74 years; the TB mortality risk population was adults over the age of 60. The period effect suggested that TB notification and mortality risks were nearly stable over the past 15 years. The cohort effect on both TB notification and mortality presented a continuously decreasing trend, and it was no longer a risk factor after 1978. All in all, the age effect should be paid more attention.

Age–period–cohort analysis of pulmonary tuberculosis reported incidence, China, 2006–2020

“…However, after controlling for period and cohort effects, the risk was similar in young and older people. Consistent with Wang’s conclusion [ 16 ], it was even slightly higher in younger adults. It also had come to similar conclusions in Argentina and India [ 13 ].…”

“…Groups born in different generations might have different cohort effects due to the interaction of biological factors, demographic changes, intergenerational effects, and exposure to social events [ 37 ]. The risk was highest in the early cohort in China (especially in eastern), and the later the birth, the lower the risk, consistent with previous studies [ 16 ]. It was mainly due to the early experience of social unrest, frequent wars, economic depression, and other social events.…”

“…Age-period-cohort (APC) is a quantitative analysis model often used in epidemiology and sociology [8,9]. There were few studies on the application of APC in TB [7,[10][11][12][13][14][15][16], and only two at the national level in China [13,16]. We collected PTB data reported to the China Tuberculosis Management Information System (TBIMS) in China, which has more comprehensive information and revised the onset date, but has not been used for such analysis.…”

Trends in incidence and mortality of esophageal cancer in China 1990−2019: A joinpoint and age-period-cohort analysis

“…Age, period, and cohort effects affect the risks of disease incidence and mortality in specific ways, and this analysis can provide information about the underlying causes of cancer incidence and death ( 14 ). There have been several studies using APCM to analyze the incidence or mortality of GBD diseases ( 5 – 8 , 10 , 14 ). Our study found that the RR remarkably increased with advancing age; specifically, the RR began to increase in the 35–39 age group, continued to rise until age 80–84 in females and 85–89 in males, when it began to decline.…”

“…Because the data of EC patients under the age of 20 years old was zero, we excluded this part of the data. The APCM analysis requires five-year intervals for each age group ( 10 ), and we excluded groups 95 years old and older.…”