Work Schedule Control and Allostatic Load Biomarkers: Disparities Between and Within Gender

Senhu Wang, Lambert Zixin Li (), Zhuofei Lu, Shuanglong Li and David Rehkopf
Additional contact information
Senhu Wang: National University of Singapore
Lambert Zixin Li: Stanford University
Zhuofei Lu: University of Manchester
Shuanglong Li: Guangzhou University
David Rehkopf: Stanford University

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2022, vol. 163, issue 3, No 10, 1249-1267

Abstract: Abstract Work schedule control has been linked to self-reported mental health, a measure that may suffer recall, social desirability, and common-method variance biases. The study proposes an alternative outcome measure to reduce survey measurement errors. It tests whether schedule control is associated with objective allostatic load biomarkers of chronic stress in a national working population, and whether the relationship depends on workers’ gender and gender role attitudes. A representative sample of 3677 British adults answered a cross-sectional survey on their work schedule control and provided blood samples in a nurse assessment. Allostatic load was constructed from 12 biomarkers across the cardiovascular, metabolic, and immune systems. The associations between work schedule control and allostatic load were tested for men and women with negative binomial models adjusting for covariates. Traditional versus egalitarian gender role attitude was then tested as a moderator. Control over work schedule is associated with lower or heathier allostatic load in women but not in men. The association is stronger among women who hold a more traditional gender role attitude towards the division of household labor. Women, especially those with traditional gender role attitudes, benefit most in allostatic load from work schedule control. Future research could use allostatic load biomarkers as a complementary indicator of quality of working life. Public health policymakers and organizations could use biomarkers to monitor the mental health risks of psychosocial work conditions and implement work-family policies to reduce the employed women’s work-family conflict.

Keywords: Allostatic load biomarkers; Survey measurement error; Schedule control; Gender; Work-family policies; Occupational epidemiology (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://link.springer.com/10.1007/s11205-022-02940-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:soinre:v:163:y:2022:i:3:d:10.1007_s11205-022-02940-7

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11135

DOI: 10.1007/s11205-022-02940-7

Access Statistics for this article

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement is currently edited by Filomena Maggino

More articles in Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().