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Stochastic Variability in Stress, Sleep Duration, and Sleep Quality Across the Distribution of Body Mass Index: Insights from Quantile Regression

International Journal of Behavioral Medicine volume 21, pages 282–291 (2014)Cite this article

Abstract

Background

Obesity has become a problem in the USA and identifying modifiable factors at the individual level may help to address this public health concern. A burgeoning literature has suggested that sleep and stress may be associated with obesity; however, little is know about whether these two factors moderate each other and even less is known about whether their impacts on obesity differ by gender.

Purpose

This study investigates whether sleep and stress are associated with body mass index (BMI) respectively, explores whether the combination of stress and sleep is also related to BMI, and demonstrates how these associations vary across the distribution of BMI values.

Methods

We analyze the data from 3,318 men and 6,689 women in the Philadelphia area using quantile regression (QR) to evaluate the relationships between sleep, stress, and obesity by gender.

Results

Our substantive findings include: (1) high and/or extreme stress were related to roughly an increase of 1.2 in BMI after accounting for other covariates; (2) the pathways linking sleep and BMI differed by gender, with BMI for men increasing by 0.77–1 units with reduced sleep duration and BMI for women declining by 0.12 unit with 1 unit increase in sleep quality; (3) stress- and sleep-related variables were confounded, but there was little evidence for moderation between these two; (4) the QR results demonstrate that the association between high and/or extreme stress to BMI varied stochastically across the distribution of BMI values, with an upward trend, suggesting that stress played a more important role among adults with higher BMI (i.e., BMI > 26 for both genders); and (5) the QR plots of sleep-related variables show similar patterns, with stronger effects on BMI at the upper end of BMI distribution.

Conclusions

Our findings suggested that sleep and stress were two seemingly independent predictors for BMI and their relationships with BMI were not constant across the BMI distribution.

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Acknowledgments

We acknowledge the support of Penn State’s Social Science Research Institute to secure the data licensing agreement. Additional support has been provided by the Population Research Institute, which receives core funding from the NICHD (R24HD41025).

Author information

Affiliations

  1. The Pennsylvania State University, 803 Oswald Tower, University Park, PA, 16802, USA

    Tse-Chuan Yang

  2. The Pennsylvania State University, 601 Oswald Tower, University Park, PA, 16802, USA

    Stephen A. Matthews

  3. Tamkang University, 151 Ying-Chuan Road, Tamsui, New Taipei County 251, Taiwan

    Vivian Y.-J. Chen

Authors
  1. Tse-Chuan Yang
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  2. Stephen A. Matthews
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  3. Vivian Y.-J. Chen
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Correspondence to Tse-Chuan Yang.

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Yang, TC., Matthews, S.A. & Chen, V.YJ. Stochastic Variability in Stress, Sleep Duration, and Sleep Quality Across the Distribution of Body Mass Index: Insights from Quantile Regression. Int.J. Behav. Med. 21, 282–291 (2014). https://doi.org/10.1007/s12529-013-9293-2

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  • DOI: https://doi.org/10.1007/s12529-013-9293-2

Keywords

  • Body mass index
  • Quantile regression
  • Stress
  • Sleep
  • Philadelphia