IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i11p5607-d561175.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/11/5607/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/11/5607/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chang, Grace & Favara, Marta & Novella, Rafael, 2022. "The origins of cognitive skills and non-cognitive skills: The long-term effect of in-utero rainfall shocks in India," Economics & Human Biology, Elsevier, vol. 44(C).
    2. Turner, Alex J. & Fichera, Eleonora & Sutton, Matt, 2021. "The effects of in-utero exposure to influenza on mental health and mortality risk throughout the life-course," Economics & Human Biology, Elsevier, vol. 43(C).
    3. Arthi, Vellore & Parman, John, 2021. "Disease, downturns, and wellbeing: Economic history and the long-run impacts of COVID-19," Explorations in Economic History, Elsevier, vol. 79(C).
    4. Okoampah, Sarah, 2016. "Cohort size effects on wages, working status, and work time," Ruhr Economic Papers 629, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Ryan Masters & Robert Hummer & Daniel Powers & Audrey Beck & Shih-Fan Lin & Brian Finch, 2014. "Long-Term Trends in Adult Mortality for U.S. Blacks and Whites: An Examination of Period- and Cohort-Based Changes," Demography, Springer;Population Association of America (PAA), vol. 51(6), pages 2047-2073, December.
    6. Ryan K. Masters & Daniel A. Powers & Robert A. Hummer & Audrey Beck & Shih-Fan Lin & Brian Karl Finch, 2016. "Fitting Age-Period-Cohort Models Using the Intrinsic Estimator: Assumptions and Misapplications," Demography, Springer;Population Association of America (PAA), vol. 53(4), pages 1253-1259, August.
    7. Yan Guo & Jianjun Bai & Xiaoxia Zhang & Qiman Jin & Yijun Liu & Chuanhua Yu, 2022. "Secular Trends of Mortality and Years of Life Lost Due to Chronic Obstructive Pulmonary Disease in Wuhan, China from 2010 to 2019: Age-Period-Cohort Analysis," IJERPH, MDPI, vol. 19(17), pages 1-11, August.
    8. Jason M. Fletcher, 2019. "Environmental bottlenecks in children’s genetic potential for adult socio-economic attainments: Evidence from a health shock," Population Studies, Taylor & Francis Journals, vol. 73(1), pages 139-148, January.
    9. 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.
    10. Hamid Noghanibehambari & Farzaneh Noghani, 2023. "Long‐run intergenerational health benefits of women empowerment: Evidence from suffrage movements in the US," Health Economics, John Wiley & Sons, Ltd., vol. 32(11), pages 2583-2631, November.
    11. Maarten J. Bijlsma & Rhian M. Daniel & Fanny Janssen & Bianca L. De Stavola, 2017. "An Assessment and Extension of the Mechanism-Based Approach to the Identification of Age-Period-Cohort Models," Demography, Springer;Population Association of America (PAA), vol. 54(2), pages 721-743, April.
    12. Doyeon An & Sang-Lim Lee & Hyekyung Woo, 2022. "Marriage Intention among Korean Young Adults: Trends and Influencing Factors," IJERPH, MDPI, vol. 19(14), pages 1-14, July.
    13. Enrique Acosta & Alain Gagnon & Nadine Ouellette & Robert R. Bourbeau & Marilia R. Nepomuceno & Alyson A. van Raalte, 2020. "The boomer penalty: excess mortality among baby boomers in Canada and the United States," MPIDR Working Papers WP-2020-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    14. Bent Nielsen, 2014. "Deviance analysis of age-period-cohort models," Economics Papers 2014-W03, Economics Group, Nuffield College, University of Oxford.
    15. Noghanibehambari, Hamid & Engelman, Michal, 2022. "Social insurance programs and later-life mortality: Evidence from new deal relief spending," Journal of Health Economics, Elsevier, vol. 86(C).
    16. Clay, Karen & Lewis, Joshua & Severnini, Edson, 2019. "What explains cross-city variation in mortality during the 1918 influenza pandemic? Evidence from 438 U.S. cities," Economics & Human Biology, Elsevier, vol. 35(C), pages 42-50.
    17. Louis Chauvel & Martin Schr der, 2015. "Inequality between birth cohorts of the 20th century in West Germany, France and the US," LIS Working papers 628, LIS Cross-National Data Center in Luxembourg.
    18. Andrew Bell & Kelvyn Jones, 2015. "Bayesian informative priors with Yang and Land’s hierarchical age–period–cohort model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 255-266, January.
    19. Chengyu Liu & Jing Wu & Zheng Chang, 2021. "Trends and Age-Period-Cohort Effects on the Prevalence, Incidence and Mortality of Hepatocellular Carcinoma from 2008 to 2017 in Tianjin, China," IJERPH, MDPI, vol. 18(11), pages 1-14, June.
    20. Manfred Grotenhuis & Ben Pelzer & Liying Luo & Alexander W. Schmidt-Catran, 2016. "The Intrinsic Estimator, Alternative Estimates, and Predictions of Mortality Trends: A Comment on Masters, Hummer, Powers, Beck, Lin, and Finch," Demography, Springer;Population Association of America (PAA), vol. 53(4), pages 1245-1252, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:5607-:d:561175. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.