Association between pre-birth waist circumference and neonatal size and health in mother-newborn pairs in Lausanne, 1917–1921
Abstract
Background Maternal anthropometric dimensions influence neonatal size and survival, yet waist circumference measured shortly before delivery remains little studied. Using historical maternity records from Lausanne, Switzerland (1917–1921), we examined associations between maternal waist circumference and neonatal anthropometry and perinatal health outcomes. Data and Methods We analyzed 4,448 singleton births recorded at the Lausanne maternity hospital. Maternal waist circumference measured shortly before delivery was categorized as <80, 80–95, 95–110, and >110 cm. Dependent variables included birth weight, length, head circumference, ponderal index, preterm birth, low birth weight, macrosomia, microcephaly, stillbirth, and early neonatal mortality within five days. Missing data were handled using multiple imputation. Associations were estimated using generalized linear models adjusted for maternal age, gravidity, civil status, residence, infection during pregnancy, birth year and season, and infant sex. Results Mean maternal waist circumference was 94.9 cm. Compared with the 80–95 cm reference group, waist circumference <80 cm was associated with lower birth weight (–575 g) and higher risks of low birth weight, preterm birth, microcephaly, stillbirth, and early neonatal death. Conversely, waist circumference >110 cm was associated with higher birth weight (+623 g) and substantially higher risk of macrosomia, but not higher infant mortality. Conclusion In this historical cohort, maternal waist circumference before delivery was strongly associated with neonatal size and adverse outcomes. Small circumference was associated with lower birth weight, prematurity, and a higher risk of mortality, whereas a large circumference was associated with macrosomia. This dataset shows that pre-delivery waist circumference was associated with perinatal risk, offering insights relevant to historical populations.
Article Details
Authors (4)
Rosa Hinselmann
Katarina L. Matthes
Kaspar Staub
Mathilde Le Vu