Using a machine learning approach to shed light on relationship between SES and women’s height

Photos of Adel Daoud, Rockli Kim and S V Subramanian

Even though height is commonly correlated with socioeconomic status (SES), SES is not known as a reliable predictor of height. In this study, Harvard Pop Center Bell Fellow Adel Daoud, Research Associate Rockli Kim, and faculty member S (Subu) V Subramanian utilized machine learning algorithms to assess whether there were non-linear patterns in the data that might shed more light on the relationship between height and socio-economic status.