Infant feeding practices within a large electronic medical record database.

Auteur(s) :
Bartsch E., Park AL., Young J., Ray JG., Tu K.
Date :
Jan, 2018
Source(s) :
BMC pregnancy and childbirth. #18:1 p
Adresse :
University of Toronto, Toronto, Canada. [email protected].

Sommaire de l'article

BACKGROUND
The emerging adoption of the electronic medical record (EMR) in primary care enables clinicians and researchers to efficiently examine epidemiological trends in child health, including infant feeding practices.

METHODS
We completed a population-based retrospective cohort study of 8815 singleton infants born at term in Ontario, Canada, April 2002 to March 2013. Newborn records were linked to the Electronic Medical Record Administrative data Linked Database (EMRALD™), which uses patient-level information from participating family practice EMRs across Ontario. We assessed exclusive breastfeeding patterns using an automated electronic search algorithm, with manual review of EMRs when the latter was not possible. We examined the rate of breastfeeding at visits corresponding to 2, 4 and 6 months of age, as well as sociodemographic factors associated with exclusive breastfeeding.

RESULTS
Of the 8815 newborns, 1044 (11.8%) lacked breastfeeding information in their EMR. Rates of exclusive breastfeeding were 39.5% at 2 months, 32.4% at 4 months and 25.1% at 6 months. At age 6 months, exclusive breastfeeding rates were highest among mothers aged ≥40 vs. < 20 years (rate ratio [RR] 2.45, 95% confidence interval [CI] 1.62-3.68), urban vs. rural residence (RR 1.35, 95% CI 1.22-1.50), and highest vs. lowest income quintile (RR 1.18, 95% CI 1.02-1.36). Overall, immigrants had similar rates of exclusive breastfeeding as non-immigrants; yet, by age 6 months, among those residing in the lowest income quintile, immigrants were more likely to exclusively breastfeed than their non-immigrant counterparts (RR 1.43, 95% CI 1.12-1.83).

CONCLUSIONS
We efficiently determined rates and factors associated with exclusive breastfeeding using data from a large EMR database.

Source : Pubmed
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