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Effect of walking behavior on perceived stress based on binary multi-level modeling

  • Dianxu Ren
  • Amy M. KwonEmail author
Original Article

Abstract

Aim

Present study examines whether perceived stress levels of health controls may be reduced by walking behavior in daily life.

Subject and methods

The subjects were a part of the Korean National Health and Nutritional Examination Survey (KNHANES), an ongoing nationwide epidemiology study, in 2008 and 2011. We examined the association between walking behavior and perceived stress (PS) of healthy controls based on multi-level modeling. We assumed that walking behavior may have an influence on how people perceive their stress, and observed the significance of the effect with adjustment for other covariates.

Results

We found that the odds of ‘high PS’ are about 16% lower for those with walking behavior with adjustment for other covariates. Inj addition, the odds of ‘high PS’ were lower for male subjects than female subjects by about 19%, while current smokers showed 1.2 times higher odds of ‘high PS’. Based on our final model, there was significant interaction effect between age and sleep duration. In particular, sleep duration has a role in reducing the odds of ‘high PS’ by 18% at the reference age of 52.98 years.

Conclusion

Walking behavior has the potential to reduce perceived stress in daily life. Also, there are strong associations between smoking, sleep duration, and perceived stress.

Keywords

Perceived stress Walking behavior Multi-level Smoking Sleep duration 

Notes

Funding information

This article is financially supported by the 2019 College of Public Policy at Korea University.

Compliance with ethical standards

Conflict of interest

All authors declare no conflicts of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Center for Research & Evaluation, Department of Health & Community System, School of NursingUniversity of PittsburghPittsburghUSA
  2. 2.Big Data Analysis, Division of Economics & Statistics, College of Public PolicyKorea UniversitySejongSouth Korea

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