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Deep machine learning study finds that body shape is associated with income

Cyber Security | December 1, 2021

A new study published in PLOS One has found a relationship between a person’s body shape and their family income. The findings provide more evidence for the “beauty premium” — a phenomenon in which people who are physically attractive tend to earn more than their less attractive counterparts.

Researchers have consistently found evidence for the beauty premium. But Suyong Song, an associate professor at The University of Iowa, and his colleagues observed that the measurements used to gauge physical appearance suffered some important limitations.

“I have been curious of whether or not there is physical attractiveness premium in labor market outcomes. One of the challenges is how researchers overcome reporting errors in body measures such as height or weight, as most previous studies often defined physical appearance from subjective opinions based on surveys,” Song explained.

“The other challenge is how to define body shapes from these body measures, as these measures are too simple to provide a complete description of body shapes. In this study, collaborated with one of my coauthors (Stephen Baek at University of Virginia), we use novel data which contains three-dimensional whole-body scans. Using a state-of-the art machine learning technique, called graphical autoencoder, we addressed these concerns.”

The researchers used the deep machine learning methods to identify important physical features in whole-body scans of 2,383 individuals from North America.

The data came from the Civilian American and European Surface Anthropometry Resource (CAESAR) project, a study conducted primarily by the U.S. Air Force from 1998 to 2000. The dataset included detailed demographic information, tape measure and caliper body measurements, and digital three-dimensional whole-body scans of participants.

“The findings showed that there is a statistically significant relationship between physical appearance and family income and that these associations differ across genders,” Song told PsyPost. “In particular, the male’s stature has a positive impact on family income, whereas the female’s obesity has a negative impact on family income.”

The researchers estimated “that one centimeter increase in stature (converted in height) is associated with approximately $998 increase in family income for a male who earns $70,000 of the median family income.” For women, the researchers estimated that “one unit decrease in obesity (converted in BMI) is associated with approximately $934 increase in the family income for a female who earns $70,000 of family income.”

“The results show that the physical attractiveness premium continues to exist, and the relationship between body shapes and family income is heterogeneous across genders,” Song said.

“Our findings also highlight importance of correctly measuring body shapes to provide adequate public policies for improving healthcare and mitigating discrimination and bias in the labor market. We suggest that (1) efforts to promote the awareness of such discrimination must occur through workplace ethics/non-discrimination training; and (2) mechanisms to minimize the invasion of bias throughout hiring and promotion processes, such as blind interviews, should be encouraged.”

The new study avoids a major limitation of previous research that relied on self-reported attractiveness and body-mass index calculations, which do not distinguish between fat, muscle, or bone mass. But the new study has an important limitation of its own.

“One major caveat is that the data set only includes family income as opposed to individual income. This opens up additional channels through which physical appearance could affect family income,” Song explained. “In this study, we identified the combined association between body shapes and family income through the labor market and marriage market. Thus, further investigations with a new survey on individual income would be an interesting direction for the future research.”

This content was originally published here.