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

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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