An Online Calculator to Estimate the Impact of Changes in Breastfeeding Rates on Population Health and Costs

Breastfeed Med. 2017 Dec;12(10):645-658. doi: 10.1089/bfm.2017.0083. Epub 2017 Sep 14.

Abstract

Objective: We sought to determine the impact of changes in breastfeeding rates on population health.

Materials and methods: We used a Monte Carlo simulation model to estimate the population-level changes in disease burden associated with marginal changes in rates of any breastfeeding at each month from birth to 12 months of life, and in rates of exclusive breastfeeding from birth to 6 months of life. We used these marginal estimates to construct an interactive online calculator (available at www.usbreastfeeding.org/saving-calc ). The Institutional Review Board of the Cambridge Health Alliance exempted the study.

Results: Using our interactive online calculator, we found that a 5% point increase in breastfeeding rates was associated with statistically significant differences in child infectious morbidity for the U.S. population, including otitis media (101,952 cases, 95% confidence interval [CI] 77,929-131,894 cases) and gastrointestinal infection (236,073 cases, 95% CI 190,643-290,278 cases). Associated medical cost differences were $31,784,763 (95% CI $24,295,235-$41,119,548) for otitis media and $12,588,848 ($10,166,203-$15,479,352) for gastrointestinal infection. The state-level impact of attaining Healthy People 2020 goals varied by population size and current breastfeeding rates.

Conclusion: Modest increases in breastfeeding rates substantially impact healthcare costs in the first year of life.

Keywords: breastfeeding; breastfeeding impact; breastfeeding policy; cost savings; economic tools.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Feeding / economics*
  • Breast Feeding / statistics & numerical data*
  • Female
  • Health Care Costs / statistics & numerical data*
  • Health Knowledge, Attitudes, Practice
  • Humans
  • Infant
  • Infant, Newborn
  • Internet*
  • Male
  • Monte Carlo Method
  • Population Health / statistics & numerical data*
  • Software
  • United States