Illustration of Measurement Error Models for Reducing Bias in Nutrition and Obesity Research Using 2-D Body Composition Data

Body shape matters: Evidence from machine learning on body shape-income relationship

The association between physical appearance and income has been of central interest in social science. However, most previous studies often measured physical appearance using classical proxies from subjective opinions based on surveys. In this study, we use novel data, called CAESAR, which contains three-dimensional (3D) whole-body scans to mitigate possible reporting and measurement errors. We demonstrate the existence of significant nonclassical reporting errors in the reported heights and weights by comparing them with measured counterparts, and show that these discrete measurements are too sparse to provide a complete description of the body shape. Instead, we use a graphical autoencoder to obtain intrinsic features, consisting of human body shapes directly from 3D scans and estimate the relationship between body shapes and family income. We also take into account a possible issue of endogenous body shapes using proxy variables and control functions. The estimation results reveal a statistically significant relationship between physical appearance and family income and that these associations differ across genders. This supports the hypothesis on the physical attractiveness premium in labor market outcomes and its heterogeneity across genders.

Comparison of Nutritional Behaviors and Physical Activities between Overweight/Obese and Normal-Weight Adults

Background:

Overweight and obesity are major problems with increasing rates among adult populations. Nutritional behaviors and physical activity are the most important influencing factors. In this article, we conducted a survey on the nutritional behaviors and physical activities among normal-weight and overweight/obese adults.

Materials and Methods:

We conducted a survey on some of the nutritional behaviors and physical activities of 729 middle-aged adults. Data regarding desirable or undesirable use of fruits, fish, dairy products, oil, fast foods, and carbonated drinks and the intensity and duration of physical activities were collected from our data bank and analyzed using the SPSS software.

Results:

Our results indicated that overweight/obese people had an improper usage of fruits, oil, fast foods, and carbonated drinks and had lower physical activity. There was also a significant increase in intensity, duration per day, and weekly days of physical activity in healthy groups. Logistic regression analysis of nutritional behaviors, physical activities, and obesity also indicated that undesirable usage of oil, fast foods, and carbonated drinks and undesirable physical activity are associated with risks for overweight/obesity (odds ratio [OR] =10.70, OR = 7.45, OR = 7.48, and OR = 2.16, respectively) (P < 0.05).

Conclusion:

This article puts emphasis on the role of proper nutritional behaviors and higher physical activities in decreasing the risks of developing obesity, and we suggest that further interventions could be made based on the results of our study.