Motherhood meets epidemiology: measuring risk factors for breast-feeding cessation

Jennifer K. Peat, Jane Allen, Nguyen Nguyen, Andrew Hayen, Wendy H. Oddy, Seema Mihrshahi

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Objective: To examine statistical models that have been used to predict the cessation of breast–feeding.

Setting: In nutritional epidemiology, a knowledge of risk factors that lead to breast-feeding cessation is essential to promote optimal infant health by increasing or sustaining breast–feeding rates. However, a number of methodological issues complicate the measurement of such risk factors. It is important when building multivariate models that variables entered into the model are not intervening variables, factors on the causal pathway or surrogate outcomes. Inclusion of these types of variable can lead to inaccurate models and biased results. A factor often cited to predict breast–feeding is ‘intention to breast–feed’ prior to the birth of the infant, although this factor is directly on the causal decision–making pathway. Another factor often cited is the age of introduction of formula feeding, which is actually part of the outcome variable because formula feeding defines the difference between full, complementary and no breast-feeding. Rather than include these as risk factors in multivariate models, factors removed from the causal pathway such as influences of educational practices, including advice to complementary feed, and beliefs and attitudes of families and health-care practitioners should be measured.

Conclusions: The accurate quantification of modifiable risk factors is essential for designing public health education campaigns that are effective in sustaining or increasing breast–feeding duration.
Original languageEnglish
Pages (from-to)1033-1037
Number of pages5
JournalPublic Health Nutrition
Issue number8
Publication statusPublished - Dec 2004
Externally publishedYes


  • Breast-feeding epidemiology
  • Breast-feeding promotion
  • Infant health
  • Risk factors
  • Statistical methods

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