Despite the perception that infectious diseases and malnutrition are the main threats to health in the developing world, the reality is that the prevalence of chronic diseases is increasing rapidly. By 2030, chronic diseases are projected to cause more than 40% of deaths in developing countries, prompting a 2008 call from the World Health Organization to establish national action plans for their prevention and control. Such plans must overcome formidable resource constraints. Because chronic diseases overlap with persistent diseases of poverty, policy responses must contend with interacting risks from multiple diseases. For instance, the control of type 2 diabetes through social policies to reduce obesity must avoid exacerbating malnutrition, especially prevalent in children. Conversely, properly targeted diabetes prevention can also reduce tuberculosis prevalence. In countries like India, diabetes'biological link to increased risk of active tuberculosis infection accounts for an estimated 15% of overall tuberculosis incidence. It is, however, not obvious which groups to target as diabetes is more prevalent in middle income groups while tuberculosis is more common in the poor. Current policy assessment methods are insufficient for these problems, as typical analyses focus on the health benefits of addressing a single disease and, therefore, fail to account for important cross-disease effects. A novel approach is required that evaluates the life course benefits of each policy alternative based on its age- and subgroup-specific impact on multiple diseases. This K01 application outlines such an approach. Its training aims are to expand knowledge and skills in: (1) econometric and statistical techniques for analyzing large household surveys, longitudinal studies with non-random attrition, and social policies such as taxes that impact food prices, consumption, and nutritional health outcomes;(2) the life course, developmental processes leading to chronic diseases such as diabetes, cardiovascular and cerebrovascular diseases as well as the biology and epidemiology of persistent diseases of poverty like tuberculosis and malnutrition. This will be accomplished through relevant coursework, mentored directed reading, and seminar participation. This K01 develops specific examples whose logical extension to other countries and diseases indicates far-reaching applicability beyond the scope of the proposal and, hence, high public health significance. The methods developed, though broadly applicable, will be applied to the specific problem of diabetes in India. The specific research aims are: (1) develop a lifetime microsimulation model of type 2 diabetes to assess primary and secondary prevention interventions in Asian Indians;(2) evaluate the impact of nutrition policies on chronic diseases and malnutrition;(3) integrate tuberculosis transmission into the diabetes model to assess how rising diabetes prevalence alters tuberculosis prevalence via their biological interaction;(4) compare the benefits of prevention policies that target subpopulations with different diabetes and tuberculosis risk profiles. In order to determine model inputs, econometric regression and statistical calibration will be used.

Public Health Relevance

Chronic non-communicable diseases are rapidly increasing in developing countries and are projected to cause more than 40% of all deaths by 2030. Chronic disease policies in developing countries are particularly challenged by (1) tight financial and health system resource constraints;and (2) interactions between chronic diseases and persistent diseases of poverty such as infections and malnutrition. The proposed research and training enable the consideration of chronic disease policies in light of these additional challenges by combining recent advances in decision science, simulation modeling, and econometrics in a life-course approach to chronic disease in developing countries.

National Institute of Health (NIH)
Research Scientist Development Award - Research & Training (K01)
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Neuroscience of Aging Review Committee (NIA)
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Patmios, Georgeanne E
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Stanford University
Internal Medicine/Medicine
Schools of Medicine
United States
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Goldhaber-Fiebert, Jeremy D; Brandeau, Margaret L (2015) Modeling and calibration for exposure to time-varying, modifiable risk factors: the example of smoking behavior in India. Med Decis Making 35:196-210
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