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

Author

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  • Luqi Wang

    (Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China)

  • Weibing Wang

    (Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
    Key laboratory of Public Health Safety, School of Public Health, Fudan University, Ministry of Education, Shanghai 200032, China)

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.

Suggested Citation

  • Luqi Wang & Weibing Wang, 2021. "Temporal Trends in Notification and Mortality of Tuberculosis in China, 2004–2019: A Joinpoint and Age–Period–Cohort Analysis," IJERPH, MDPI, vol. 18(11), pages 1-11, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:5607-:d:561175
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    References listed on IDEAS

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    1. Yiran Cui & Hui Shen & Fang Wang & Haoyu Wen & Zixin Zeng & Yafeng Wang & Chuanhua Yu, 2020. "A Long-Term Trend Study of Tuberculosis Incidence in China, India and United States 1992–2017: A Joinpoint and Age–Period–Cohort Analysis," IJERPH, MDPI, vol. 17(9), pages 1-19, May.
    2. I-Shiang Tzeng & Kuo-Hu Chen & Yungling L. Lee & Wen-Shan Yang, 2019. "Trends and Age-Period-Cohort Effects of Fertility Rate: Analysis of 26,224 Married Women in Taiwan," IJERPH, MDPI, vol. 16(24), pages 1-12, December.
    3. Fang Wang & Sumaira Mubarik & Yu Zhang & Lu Wang & Yafeng Wang & Chuanhua Yu & Hao Li, 2019. "Long-Term Trends of Liver Cancer Incidence and Mortality in China 1990–2017: A Joinpoint and Age–Period–Cohort Analysis," IJERPH, MDPI, vol. 16(16), pages 1-13, August.
    4. Fletcher, Jason M., 2018. "The effects of in utero exposure to the 1918 influenza pandemic on family formation," Economics & Human Biology, Elsevier, vol. 30(C), pages 59-68.
    5. Liying Luo, 2013. "Assessing Validity and Application Scope of the Intrinsic Estimator Approach to the Age-Period-Cohort Problem," Demography, Springer;Population Association of America (PAA), vol. 50(6), pages 1945-1967, December.
    6. Jason M. Fletcher, 2018. "New Evidence on the Impacts of Early Exposure to the 1918 Influenza Pandemic on Old-Age Mortality," Working Papers 18-06, Center for Economic Studies, U.S. Census Bureau.
    7. Haoyu Wen & Cong Xie & Lu Wang & Fang Wang & Yafeng Wang & Xiaoxue Liu & Chuanhua Yu, 2019. "Difference in Long-Term Trends in COPD Mortality between China and the U.S., 1992–2017: An Age–Period–Cohort Analysis," IJERPH, MDPI, vol. 16(9), pages 1-15, April.
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    1. Lele Deng & Yajun Han & Jinlong Wang & Haican Liu & Guilian Li & Dayan Wang & Guangxue He, 2023. "Epidemiological Characteristics of Notifiable Respiratory Infectious Diseases in Mainland China from 2010 to 2018," IJERPH, MDPI, vol. 20(5), pages 1-16, February.

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