"Improvements in economic development, such as higher educational attainment, increasing employment in the formal labor market, and the shift away from agriculture, seem to have a doubly-powerful effect because they not only raise individuals' standards of living, but also correlate to declining fertility rates, according to the results of our study," said Mary Shenk, assistant professor of anthropology in MU's College of Arts and Science. "Another important finding of our study was that intervention programs that made changes that really affected individuals achieved the best results. For example, although advertising campaigns encouraging lower fertility may reach a wider audience for less money, face-to-face intervention campaigns providing health services or access to contraception provide better results and are thus a better use of resources."
In their research, Shenk and her colleagues used data collected since 1966 from approximately 250,000 people in rural Bangladesh, along with detailed interviews of nearly 800 women from the region. Sixty-four factors related to family size were considered and organized according to three possible explanations for declines in fertility rates:
- Risk and mortality - Parents have fewer children when they have more hope that children will survive into adulthood, according to this explanation.
- Economic and investment - This explanation suggests that rising costs of children and higher payoffs to investing in self and children reduce fertility with the shift to a market economy.
- Cultural transmission - This explanation holds that social perceptions of the value of children, ideal family size and acceptance of contraception influence fertility rates.
"Few studies have compared those three possible explanations for fertility declines to determine which had the strongest effect," said Shenk. "Population growth rates have fallen globally, starting in 18th century Western Europe, but the exact cause was intensely debated because there are so many different explanations in the literature. Our study created a framework by which different explanations could be explicitly compared. Population data from any region could be analyzed using these methods to help researchers, government officials, health workers and others understand the key drivers of demographic change in that region."