Article

The Epidemiologic Transition: A Theory of the Epidemiology of Population Change

Milbank Quarterly (Impact Factor: 5.06). 02/2005; 83(4):731-57. DOI: 10.1111/j.1468-0009.2005.00398.x
Source: PubMed
0 Followers
 · 
72 Views
  • Source
    • "One is a demographical change with higher life expectancy and reduced fertility rates. The other is an epidemiological transition where the patterns of disease shift away from infectious and nutrient deficiency diseases towards higher rates of coronary heart disease, certain types of cancer, a higher prevalence of obesity (particularly childhood obesity), and non-insulin-dependent diabetes (Drewnowski and Popkin, 1997; Omran, 1971; Popkin, 2003). Popkin (1993) uses ''nutrition transition'' to term these changes and further divides it into five steps, namely: collecting food, famine, receding famine, degenerative diseases and behavioral change. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In company with rapid economic growth, Chinese consumers have seen a remarkable nutrition improvement and a dramatic dietary change. This article investigates the driving forces behind these changes with use of the China Health and Nutrition Survey (CHNS) data. This paper first proposes 10 different indices to measure nutrition improvement and dietary change from different perspectives, and then adopts semiparametric panel data models to capture the complicated nonlinear relationship between these nutrition indices and income growth, while controlling for other variables parametrically. This enables us to directly predict the nutrition improvement and dietary change at different income levels from different aspects. This paper particularly finds that nutrition improvement and dietary change will continue in China but will slow down in the future with further income growth.
    Food Policy 05/2015; 53. DOI:10.1016/j.foodpol.2015.04.006 · 2.33 Impact Factor
    • "Mortality trends in high-income countries between 1900 and 1950 showed a clear age-pattern shift: mortality at young ages and from infectious conditions was rapidly receding while mortality at older ages and from chronic conditions began to dominate (Omran, 1971; Preston, 1976). By the 1960s major medical improvements in cardiovascular survival led to an increasing prevalence of heart disease at older ages. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The success of the current biomedical paradigm based on a “disease model” may be limited in the future due to large number of comorbidities inflicting older people. In recent years, there has been growing empirical evidence based on animal models suggesting that the aging process could be delayed and that this process may lead to increases in life expectancy accompanied by improvements in health at older ages. In this chapter we explore past, present and future prospects of healthy life expectancy and examine whether increases in average length of life associated with delayed aging link with additional years lived disability-free at older ages. Trends in healthy life expectancy suggest improvements among older people in the U.S., although younger cohorts appear to be reaching old age with increasing levels of frailty and disability. Trends in health risk factors such as obesity and smoking show worrisome signs of negative impacts on adult health and mortality in the near future. However, results based on a simulation model of delayed aging in humans indicate that it has the potential to increase not only the length of life but also the fraction and number of years spent disability-free at older ages. Delayed aging would likely come with additional aggregate costs. These costs could be offset if delayed aging is widely applied and people are willing to convert their greater healthiness into more years of work.
    The Longevity Dividend, Edited by J.S. Olshanky, G.M. Martin, L. Kirkland, 01/2015; Cold Spring Harbor Laboratory Press.
  • Source
    • "In the past two centuries, life expectancy has more than doubled from 30–40 years to approximately 80 or more years in many developed countries (Oeppen and Vaupel 2002). The epidemiologic transition (Olshansky and Ault 1986; Omran 1971) is thought to be the key mechanism behind the increase in human life expectancy. Epidemiologic transition theory portrays four stages through which advanced societies pass, starting with the age of pestilence and infectious diseases that characterizes most of the human history, entering the age of receding pandemics around the middle of the nineteenth century, and advancing to the age of degenerative and human-made diseases (e.g., cardiovascular disease) in the early twentieth century, and to the age of delayed degenerative diseases around the 1960s. "
    [Show abstract] [Hide abstract]
    ABSTRACT: This study examines historical patterns of aging through the perspectives of cohort evolution and mortality selection, where the former emphasizes the correlation across cohorts in the age dependence of mortality rates, and the latter emphasizes cohort change in the acceleration of mortality over the life course. In the analysis of historical cohort mortality data, I find support for both perspectives. The rate of demographic aging, or the rate at which mortality accelerates past age 70, is not fixed across cohorts; rather, it is affected by the extent of mortality selection at young and late ages. This causes later cohorts to have higher rates of demographic aging than earlier cohorts. The rate of biological aging, approximating the rate of the senescence process, significantly declined between the mid- and late-nineteenth century birth cohorts and stabilized afterward. Unlike the rate of demographic aging, the rate of biological aging is not affected by mortality selection earlier in the life course but rather by cross-cohort changes in young-age mortality, which cause lower rates of biological aging in old age among later cohorts. These findings enrich theories of cohort evolution and have implications for the study of limits on the human lifespan and evolution of aging.
    Demography 06/2014; 51(4). DOI:10.1007/s13524-014-0306-9 · 1.93 Impact Factor
Show more

Preview

Download
1 Download
Available from