IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0061495.html
   My bibliography  Save this article

Age-Period-Cohort Projections of Ischaemic Heart Disease Mortality by Socio-Economic Position in a Rapidly Transitioning Chinese Population

Author

Listed:
  • Irene O L Wong
  • Benjamin J Cowling
  • Gabriel M Leung
  • C Mary Schooling

Abstract

Background: With economic development and population aging, ischaemic heart disease (IHD) is becoming a leading cause of mortality with widening inequalities in China. To forewarn the trends in China we projected IHD trends in the most economically developed part of China, i.e., Hong Kong. Methods: Based on sex-specific IHD mortality rates from 1976 to 2005, we projected mortality rates by neighborhood-level socio-economic position (i.e., low- or high-income groups) to 2020 in Hong Kong using Poisson age-period-cohort models with autoregressive priors. Results: In the low-income group, age-standardized IHD mortality rates among women declined from 33.3 deaths in 1976–1980 to 19.7 per 100,000 in 2016–2020 (from 55.5 deaths to 34.2 per 100,000 among men). The rates in the high-income group were initially higher in both sexes, particularly among men, but this had reversed by the end of the study periods. The rates declined faster for the high-income group than for the low-income group in both sexes. The rates were projected to decline faster in the high-income group, such that by the end of the projection period the high-income group would have lower IHD mortality rates, particularly for women. Birth cohort effects varied with sex, with a marked upturn in IHD mortality around 1945, i.e., for the first generation of men to grow up in a more economically developed environment. There was no such upturn in women. Birth cohort effects were the main drivers of change in IHD mortality rates. Conclusion: IHD mortality rates are declining in Hong Kong and are projected to continue to do so, even taking into account greater vulnerability for the first generation of men born into a more developed environment. At the same time social disparities in IHD have reversed and are widening, partly as a result of a cohort effect, with corresponding implications for prevention.

Suggested Citation

  • Irene O L Wong & Benjamin J Cowling & Gabriel M Leung & C Mary Schooling, 2013. "Age-Period-Cohort Projections of Ischaemic Heart Disease Mortality by Socio-Economic Position in a Rapidly Transitioning Chinese Population," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-8, April.
  • Handle: RePEc:plo:pone00:0061495
    DOI: 10.1371/journal.pone.0061495
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0061495
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0061495&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0061495?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ram C. Tiwari & Kathleen A. Cronin & William Davis & Eric J. Feuer & Binbing Yu & Siddhartha Chib, 2005. "Bayesian model selection for join point regression with application to age‐adjusted cancer rates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 919-939, November.
    2. Isabelle Bray, 2002. "Application of Markov chain Monte Carlo methods to projecting cancer incidence and mortality," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(2), pages 151-164, May.
    3. Yang Yang, 2008. "Trends in U.S. adult chronic disease mortality, 1960–1999: age, period, and cohort variations," Demography, Springer;Population Association of America (PAA), vol. 45(2), pages 387-416, May.
    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. Carlo Giovanni Camarda, 2019. "Smooth constrained mortality forecasting," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(38), pages 1091-1130.

    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. Hui Zheng & Jonathan Dirlam & Paola Echave, 2021. "Divergent Trends in the Effects of Early Life Factors on Adult Health," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 40(5), pages 1119-1148, October.
    2. 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.
    3. 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.
    4. Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015. "Bayesian Poisson log-bilinear models for mortality projections with multiple populations," BAFFI CAREFIN Working Papers 1505, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    5. Ting Li & Yang Yang & James Anderson, 2013. "Mortality Increase in Late-Middle and Early-Old Age: Heterogeneity in Death Processes as a New Explanation," Demography, Springer;Population Association of America (PAA), vol. 50(5), pages 1563-1591, October.
    6. Yang Yang & Kenneth Land, 2013. "Misunderstandings, Mischaracterizations, and the Problematic Choice of a Specific Instance in Which the IE Should Never Be Applied," Demography, Springer;Population Association of America (PAA), vol. 50(6), pages 1969-1971, December.
    7. Erjia Ge & Yee Leung, 2013. "Detection of crossover time scales in multifractal detrended fluctuation analysis," Journal of Geographical Systems, Springer, vol. 15(2), pages 115-147, April.
    8. Chen, Cathy W.S. & Chan, Jennifer S.K. & So, Mike K.P. & Lee, Kevin K.M., 2011. "Classification in segmented regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2276-2287, July.
    9. Alyson van Raalte & Pekka Martikainen & Mikko Myrskylä, 2014. "Lifespan Variation by Occupational Class: Compression or Stagnation Over Time?," Demography, Springer;Population Association of America (PAA), vol. 51(1), pages 73-95, February.
    10. Beck, Audrey N. & Finch, Brian K. & Lin, Shih-Fan & Hummer, Robert A. & Masters, Ryan K., 2014. "Racial disparities in self-rated health: Trends, explanatory factors, and the changing role of socio-demographics," Social Science & Medicine, Elsevier, vol. 104(C), pages 163-177.
    11. Wouter Nientker & Rob Alessie, 2019. "Female Labor Market Participation Across Cohorts: Evidence from the Netherlands," De Economist, Springer, vol. 167(4), pages 407-433, December.
    12. Steven A. Haas & Katsuya Oi & Zhangjun Zhou, 2017. "The Life Course, Cohort Dynamics, and International Differences in Aging Trajectories," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2043-2071, December.
    13. Xiaoxue Liu & Chuanhua Yu & Yongbo Wang & Yongyi Bi & Yu Liu & Zhi-Jiang Zhang, 2019. "Trends in the Incidence and Mortality of Diabetes in China from 1990 to 2017: A Joinpoint and Age-Period-Cohort Analysis," IJERPH, MDPI, vol. 16(1), pages 1-14, January.
    14. Kyoji Furukawa & Munechika Misumi & John B. Cologne & Harry M. Cullings, 2016. "A Bayesian Semiparametric Model for Radiation Dose‐Response Estimation," Risk Analysis, John Wiley & Sons, vol. 36(6), pages 1211-1223, June.
    15. Chan, J.S.K. & Lam, C.P.Y. & Yu, P.L.H. & Choy, S.T.B. & Chen, C.W.S., 2012. "A Bayesian conditional autoregressive geometric process model for range data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3006-3019.
    16. Palladino, Marco G. & Roulet, Alexandra & Stabile, Mark, 2025. "Narrowing industry wage premiums and the decline in the gender wage gap," Labour Economics, Elsevier, vol. 94(C).
    17. Xin Yuan & Changgui Kou & Min Zhang & Wenyuan Ma & Zhitao Tang & Haiyan Sun & Wenjun Li, 2022. "Injury and Poisoning Mortality Trends in Urban and Rural China from 2006 to 2020 Based on Age-Period-Cohort Analysis," IJERPH, MDPI, vol. 19(12), pages 1-13, June.
    18. Carl Schmertmann & Emilio Zagheni & Joshua R. Goldstein & Mikko Myrskylä, 2014. "Bayesian Forecasting of Cohort Fertility," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 500-513, June.
    19. 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.
    20. Irene O L Wong & Benjamin J Cowling & Gabriel M Leung & C Mary Schooling, 2012. "Trends in Mortality from Septicaemia and Pneumonia with Economic Development: An Age-Period-Cohort Analysis," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-7, June.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0061495. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.