The relationship between rising incomes and health care in the developing world is not a simple one, suggested Dr. Angus Deaton, Professor of Economics at Princeton University, in a lecture hosted by Fogarty at the NIH's Stone House. "There seems to be little progress--more than a billion people still live in absolute poverty, and we still have 10.5 million child deaths a year that would not take place in rich countries," he said.
Princeton economist Dr. Angus Deaton challenged the commonly held belief that income is a determinant of health in poor countries.
Dr. Deaton challenged the commonly held belief that income is a powerful determinant of health in poor countries, using a model called the Millennium Preston Curve to illustrate his point. The curves measure the relationship between a country's life expectancy and its per capita income. According to Dr. Deaton, the creator of the curve felt that the majority of health improvements were related to technology and technique, rather than income.
China and India are both examples of countries that have seen significant recent income rises but have also experienced only small declines in infant mortality rates, according to Dr. Deaton. "Is wealthier healthier?" he asked. "It's plausible, but certainly not automatically true. Health improvement is likely related to governments, and their capacity and interest in doing something."
Randomized control trials should be incorporated into the evaluation of global health programs, he said, touting the success of the World Bank's Dvelopment Impact Evaluation Initiative. "Randomized control trials are excellent for debunking things that are not true, and sometimes even reveal problems that were not obvious in advance," he concluded.
Dr. Deaton is professor of international affairs and economics at Princeton University. His current research focuses on the determinants of health in rich and poor countries, as well as on the measurement of poverty in India and around the world. He also maintains a long-standing interest in the analysis of household surveys.