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A Long-Term Trend Study of Tuberculosis Incidence in China, India and United States 1992–2017: A Joinpoint and Age–Period–Cohort Analysis

Author

Listed:
  • Yiran Cui

    (Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan 430071, China)

  • Hui Shen

    (Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan 430071, China)

  • Fang Wang

    (Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan 430071, China)

  • Haoyu Wen

    (Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan 430071, China)

  • Zixin Zeng

    (Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan 430071, China)

  • Yafeng Wang

    (Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan 430071, China)

  • Chuanhua Yu

    (Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan 430071, China
    Global Health Institute, Wuhan University, Wuhan 430071, China)

Abstract

Tuberculosis (TB) is one of the major infectious diseases with the largest number of morbidity and mortality. Based on the comparison of high and low burden countries of tuberculosis in China, India and the United States, the influence of age-period-cohort on the incidence of tuberculosis in three countries from 1992 to 2017 was studied based on the Global burden of Disease Study 2017. We studied the trends using Joinpoint regression in the age-standardized incidence rate (ASIR). The regression model showed a significant decreasing behavior in China, India and the United States between 1992 and 2017. Here, we analyzed the tuberculosis incidence trends in China, India, as well as the United States and distinguished age, period and cohort effects by using age-period-cohort (APC) model. We found that the relative risks (RRs) of tuberculosis in China and India have similar trends, but the United States was found different. The period effect showed that the incidence of the three countries as a whole declines with time. The incidence of tuberculosis had increased in most age group. The older the age, the higher the risk of TB incidence. The net age effect in China and India showed a negative trend, while the cohort effect decreased from the earlier birth cohort to the recent birth cohort. Aging may lead to a continuous increase in the incidence of tuberculosis. It is related to the aging of the population and the relative decline of the immune function in the elderly. This should be timely population intervention or vaccine measures, especially for the elderly. The net cohort effect in the United States showed an unfavorable trend, mainly due to rising smoking rates and the emergence of an economic crisis. Reducing tobacco consumption can effectively reduce the incidence.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:3334-:d:356582
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    References listed on IDEAS

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    1. Zhang, Xiaobo & Yang, Jin & Wang, Shenglin, 2011. "China has reached the Lewis turning point," China Economic Review, Elsevier, vol. 22(4), pages 542-554.
    2. Wang, Hufeng & Gusmano, Michael K. & Cao, Qi, 2011. "An evaluation of the policy on community health organizations in China: Will the priority of new healthcare reform in China be a success?," Health Policy, Elsevier, vol. 99(1), pages 37-43, January.
    3. 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.
    4. Olivia Oxlade & Megan Murray, 2012. "Tuberculosis and Poverty: Why Are the Poor at Greater Risk in India?," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-8, November.
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    Cited by:

    1. 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.

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