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.
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](https://www.hsph.harvard.edu/population-development/wp-content/uploads/sites/2623/2019/11/Adel_Rockli_Subu_720-by-540.jpg)