Mommy and Me: The Impact of Paid Family Leave on Breastfeeding

The presidential election and recent policy changes at large companies like Netflix have drawn a great deal of attention to the concept of paid family leave (PFL), which generally entails extended periods of leave from employment to care for newborn children or sick family members, spouses, or domestic partners. Recent research has shown that PFL policies can impact rates of breastfeeding, a practice encouraged by health organizations worldwide, among new mothers.

Research has shown that breastfeeding has beneficial health impacts, reducing the risk of sudden infant death syndrome, asthma, diabetes, and obesity for children, in addition to lowering rates of breast and ovarian cancer for mothers. Yet breastfeeding rates in the United States drop from 76.9 percent at birth to 25.5 percent just one year later.

Researchers have identified returning to work as a main reason for the cessation of breastfeeding in the United States. To determine the impact that PFL can have on extended breastfeeding, Rui Huang and Muzhe Yang examined the impact of a PFL policy implemented in California. Their paper, Paid Maternity Leave and Breastfeeding Practice Before and After California’s Implementation of the Nation’s First Paid Family Leave Program, finds that the PFL program increases exclusive breastfeeding by three to five percentage points and by 10 to 20 percentage points at several important markers of development.

The California program provides individuals with up to six weeks of partially paid leave (receiving 55 percent of their previous earnings). To determine the impact of this policy, the researchers used two waves of the Infant Feeding and Practices Study (IFPS): one from before implementation of the policy and one from after implementation. Using women from all other continental states, they determined the counterfactual for breastfeeding. Although rates of breastfeeding increased across the country during this time, the rate of increase was much greater in California than anywhere else.

The IFPS asked questions related to breastfeeding, formula and complementary feeding, infant health, breast pump use, and family characteristics. Surveys were sent during the third trimester of pregnancy, within three weeks of birth, and then monthly throughout the first year of each child’s life. Though the survey is nationally distributed, it is not representative, as parents with low socioeconomic statuses are underrepresented in the sample. Wave I was sent in 1993 (before implementation), while Wave II was sent in 2005 or 2006 (after implementation). The policy was implemented in 2002.

Overall, researchers found that Wave II women breastfed longer and more exclusively. California, which already had higher breastfeeding rates than the rest of the country, increased its rates more rapidly between Wave I and Wave II than any other state. There are, however, important questions regarding the validity of the counterfactual. California differs considerably from other states, and the analysis may have been more convincing had it used a synthetic control that weighted states based on their similarity to California, particularly in terms of demographics. Another potential problem is that Wave II measurements were taken three years after policy implementation. That lag time makes it more difficult to determine any causal relationship.

Still, this research may indicate that PFL can have a significant impact on breastfeeding and thus maternal and child health. Further research is likely needed to better identify the impact on low-income households, but it seems like new policies supporting PFL may be heading in the right direction. Additional research should be continued, as other states enact similar policies, to determine whether the impact seen in California could be universal.

 

Article Source: Huang, Rui, and Muzhe Yang. “Paid Maternity Leave and Breastfeeding Practice Before and After California’s Implementation of the Nation’s First Paid Family Leave Program.” Economics & Human Biology 16 (2015): 45-59.

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