BackgroundFood insecurity and anemia are prevalent among low-income families and infants. Anemia may reflect iron deficiency anemia (IDA) risk. IDA in infancy and early childhood may have long-lasting developmental effects. Few studies have examined food security status (FSS) as a risk factor for anemia. ObjectiveTo examine the association between household FSS, sociodemographic and health-related variables, and anemia incidence at age 18 months among low-income infants in the Massachusetts Special Supplemental Nutrition Program for Women, Infants, and Children (MA/WIC). Study designThis was a longitudinal study using data from MA/WIC (August 2001 to November 2009) to assess the relationship between household FSS during the 12 months preceding the 1-year visit (age 9 to 15 months) and anemia at age 18 months. Participants/settingsInfants included were not anemic at age 12 months and had complete data on household FSS and the following covariates (N=17,831): race/Hispanic ethnicity, maternal education, breastfeeding duration, household size, and child age. Statistical analyses performedMultiple logistic regression was used to examine the association between household FSS during the prior 12 months and anemia at 18 months, controlling for infant age, sex, and race/Hispanic ethnicity, breastfeeding, maternal education, and household size. ResultsA majority of infants (56%) were nonwhite, and 19.9% lived in food-insecure households (4.8% in very-low food security). Of the infants who were not anemic at age 12 months, 11.7% became anemic by age 18 months. Infants living in low-food-secure households were 42% more likely (adjusted odds ratio 1.42, 95% CI, 1.27-1.60) to develop anemia at age 18 months than were their food-secure counterparts. Nonwhite race, higher household size, and lower maternal education were also associated with an elevated risk of anemia at age 18 months. ConclusionsLow food security appears to be associated with a significant increased risk of anemia, as do nonwhite ethnicity, lower maternal education, and larger household size. Knowledge of these risk factors can be used to design IDA-prevention interventions in this vulnerable population.
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