How Did the Recent Infant Formula Shortage Affect Breastfeeding Rates in Northeast New York [ID 2683397

Abstract

INTRODUCTION: To determine the effect of the recent infant formula shortage on breastfeeding rates in the northeast New York area. METHODS: This was a retrospective analysis of the Northeast New York (NENY) Regional Birth Registry database from January 2021 to June 2022. Breastfeeding rates of patients in the first 6 months of 2022 were compared to those from 2021. Maternal demographics, obstetrical history, breastfeeding, and delivery information were collected. We wanted to determine whether the recent infant formula shortage in the United States affected the breastfeeding rates. Statistical analyses were performed using STATA software (Stata/SE 12.1). A P value of <.05 was considered statistically significant. This study was approved by the IRB at Albany Medical Center. We controlled for maternal marital status, education level, ethnicity, and employment status during pregnancy in our statistical analysis. RESULTS: We identified 19,610 patients in the NENY database from January 2021 to June 2022. 170 (0.87%) were excluded from our study due to breastfeeding data not being available. The exclusive breastfeeding rate increased from 55.97% to 57.25%. However, this was not statistically significant (P<.104). The formula-only rates essentially stayed the same, 17.94% versus 17.54%. The rates of the infants who were supplemented with formula had a nonsignificant decrease from 25.23% to 24.33% (P<.185). We did a secondary analysis in which the data were excluded for those infants who were admitted to the neonatal intensive care unit and the differences were even smaller with an overall P value of 0.949. CONCLUSION: Although the recent infant formula shortage in the United States led to a slight increase in exclusive breastfeeding rates and decrease in formula feeding in a first 6 months of 2022, none of these were statistically significant. These differences were not statistically significant even after controlling for demographic factors such as marital status, race, and education level and BMI.