Impact of obesity on employment and wages among young adults: Observational study with panel data

Hyeain Lee, Rosemary Ahn, Tae Hyun Kim, Euna Han

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


This paper assesses the relationship between obesity and the job market by focusing on young adults early on in their careers, while considering the factor of gender and the individuals’ job qualifications. This study extracted data on high school students for four years from the Korean Education and Employment Panel (from 2010 to 2013), a nationally representative dataset comprising of 2000 middle school students and 4000 high school seniors. The individual-level fixed effects were controlled using conditional logistic regression models and an ordinary least squares model. Obese and overweight men were 1.46 times more likely to be placed in professional jobs and had 13.9% higher monthly wages than their normal-weight counterparts. However, obese and overweight women were 0.33 times less likely to have service jobs, earned 9.0% lower monthly wages, and half as likely to have jobs with bonuses than that of their normal-weight counterparts. However, such penalty among women was found only when they had none of the assessed job market qualifications. Given that initial jobs and job conditions have lingering impacts in long-term job performance, the cumulative penalty for overweight or obesity could be more substantial for young adults in particular.

Original languageEnglish
Article number139
JournalInternational journal of environmental research and public health
Issue number1
Publication statusPublished - 2019 Jan 1

Bibliographical note

Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Public Health, Environmental and Occupational Health
  • Pollution
  • Health, Toxicology and Mutagenesis


Dive into the research topics of 'Impact of obesity on employment and wages among young adults: Observational study with panel data'. Together they form a unique fingerprint.

Cite this