Early Peanut Introduction in Primary Care: Evaluation of a Multi-Component Intervention

Published:November 18, 2022DOI:



      To determine whether a multi-component intervention focused on early peanut introduction was associated with a lower peanut allergy incidence in young children.


      The study cohort comprised all children born January 1, 2013 through December 31, 2018 receiving care at a large healthcare organization. Intervention activities occurred over 15 months and included provider educational programs, electronic health record tools, and new patient instructions. We used an interrupted time series design to assess whether peanut allergy incidence differed across three time periods (pre-intervention, interim, post-intervention) among high- and low-risk children. The primary outcome was incident peanut allergy by age 24 months, defined as peanut allergy in the allergy field or active problem list plus a positive supportive test. Severe eczema and/or egg allergy presence defined high-risk. Because the study was conducted as part of routine care, it was not feasible to measure what counseling clinicians provided, or how and when parents fed their children peanut-containing foods.


      In a cohort of 22571 children, the percent with peanut allergy by age 24 months was 17.3% (116 of 671) among high-risk and 0.8% (181 of 21900) among low-risk children. In multivariate analyses, the adjusted peanut allergy rate per 100 person-years was not significantly different across study periods among high-risk (9.6 pre-intervention, 11.7 interim, and 9.9 post-intervention, p=0.70) or low-risk (0.5 pre-intervention, 0.7 interim, and 0.5 post-intervention, p=0.17) children.

      Conclusions and Relevance

      In a community-based setting, the incidence of peanut allergy did not decline following a multi-component intervention focused on early peanut introduction.

      Key Words


      CI (confidence interval), EHR (electronic health record), KPCO (Kaiser Permanente Colorado), mm (millimeters), PMCA (Pediatric Medical Complexity Algorithm), SD (standard deviation)
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