Methods: We used longitudinal data from 260 mother-child dyads from the Synergistic Theory and Research on Obesity and Nutrition Group (STRONG) Kids Program. Data from Wave 1 (W1) and W2 were used in this study. Maternal depressive symptoms were measured by self-report at W1 using the depression subscale of the Depression, Anxiety, and Stress Scales (DASS). Breastfeeding duration was measured by self-report at W1. Child height and weight were measured by researchers using manualized procedures. The Centers for Disease Control and Prevention BMI for age and sex growth charts were used to calculate BMI percentile. We used correlations, chi-square tests, and OLS and logistic regression to analyze the data using SPSS 22.
Results: The majority of the participants were white (73%), college graduates, and married or living with a partner. The average age of the mothers was 33 years. H1: No associations were found between elevated maternal depressive symptoms at W1 and child BMI percentile at W2. H2: Higher depressive symptom scores were negatively correlated with breastfeeding for 6 months or more but these relationships were no longer significant after controlling for race/ethnicity, education, age, family structure, and WIC participation. H3: Finally, never breastfeeding was associated with higher child BMI percentile at wave 2; and breastfeeding for 6 months or more was associated with lower BMI percentile, even after controlling for race/ethnicity, education, age, family structure, and WIC participation.
Conclusions and Implications: Findings suggest that while maternal depressive symptoms do not necessarily increase a child’s risk for obesity, they may be associated with reduced breastfeeding duration, which in turn raises risk for child obesity. Therefore, it is vital for social work practitioners to assist and provide support to mothers with depression who choose to breastfeed, in order for them to be able to initiate and sustain breastfeeding for longer periods. Finally, more research among more diverse and low-income populations is necessary to better understand these dynamics.