Project Summary
Preterm birth is a well-known determinant of poor child growth and development (CGAD). Premature
infants have a higher risk of infection, malnutrition, and developmental impairments. Additionally,
caregivers of preterm infants are at risk of developing mental health challenges, including depression,
anxiety, and stress and in low- and middle-income countries, where 81% of preterm births occurs,
caregivers frequently experience stigmatization leading to a loss of social support. These experiences have
been shown to negatively impact CGAD by altering bonding and caregiver responsiveness. Although
research shows that these factors influence CGAD through many pathways at many levels, each factor has
traditionally been studied independently, therefore, these pathways are inadequately understood. This
project aims to provide a clearer picture of these mechanisms and solutions to them through three main
aims. The first is to identify child, family, and social factors that mediate and modify the effect of
prematurity on CGAD. Caregivers of preterm infants will be recruited from well-child clinics at hospitals
in Ghana, a country with high rate of preterm birth and developmental disabilities. Factors such as infection,
malnutrition, feeding practices, parenting, maternal health, social stigma, and demographic characteristics
will be measured using routinely collected maternal and child health data and questionnaires completed by
caregivers. This data will be analyzed using path analysis, a statistical modeling technique that identifies
causal pathways among many variables, in order to determine how these factors, interact and influence each
other to determine CGAD. The second aim is to identify profiles of preterm and term babies who are at risk
for poor growth and development. Machine learning algorithms will be applied to the maternal and child
health data to identify the strongest predictors of growth and development. These predictors can be used to
develop clinical screening tools to identify highly at-risk infants. The third aim is to identify local,
caregiver-driven strategies that promote growth and development in preterm infants. This is based on
Positive Deviant Theory, which posits that even in difficult circumstances, some individuals have
uncommon but successful solutions. Caregivers whose preterm infants had high child development scores
will be recruited to participate in qualitative interviews to learn about the strategies they use to achieve
these positive outcomes. These results can be used to create an intervention for families of preterm infants
to improve child growth and development. A multidisciplinary team of researchers will supervise and
mentor graduate and undergraduate students from fields of computer science, health sciences, and child
development. In addition to global research experience, these students will gain leadership, teamwork, and
problem-solving skills that are invaluable to building future successful scientists.
