Social and behavioral determinants of perceived insufficient sleep
Open accessAbstract
Insufficient sleep is associated with cardiometabolic disease and poor health. However, few studies have assessed its determinants in a nationally representative sample. Data from the 2009 behavioral risk factor surveillance system were used (N = 323,047 adults). Insufficient sleep was assessed as insufficient rest/sleep over 30 days. This was evaluated relative to sociodemographics (age, sex, race/ethnicity, marital status, region), socioeconomics (education, income, employment, insurance), health behaviors (diet, exercise, smoking, alcohol), and health/functioning (emotional support, BMI, mental/physical health). Overall, insufficient sleep was associated with being female, White or Black/African-American, unemployed, without health insurance, and not married; decreased age, income, education, physical activity; worse diet and overall health; and increased household size, alcohol, and smoking. These factors should be considered as risk factors for insufficient sleep.
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Chronic sleep insufficiency has played a role in motor vehicle accidents, industrial disasters, and medical and other occupational errors.
“Chronic sleep insufficiency has played a role in motor vehicle accidents, industrial disasters, medical and other occupational errors, for instance(41, 42, 47-51).”
From Sleep: important considerations for the prevention of cardiovascular disease (2016) · cites this paper as [41]
In the general population, overall mental health has been identified as the leading predictor of self-reported insufficient sleep.
“In the general population, overall mental health has been identified as the leading predictor of self-reported insufficient sleep.30”
From Sleep, Health, and Society (2017) · cites this paper as [30]
Unemployment is associated with more sleep problems.
“Unemployment, on the other hand, is associated with more sleep problems.28,30”
From Sleep, Health, and Society (2017) · cites this paper as [30]
Once the benefits of income are accounted for by statistically covarying education, access to health care, and so forth, associations with income are often nonexistent and may go in the opposite direction.
“However, once the benefits of income are accounted for (by statistically covarying education, access to health care, and so forth), associations with income are often nonexistent and may go in the opposite direction.”
From Sleep, Health, and Society (2017) · cites this paper as [30]
Poverty is associated with both shorter sleep duration and worse sleep quality.
“Several studies have shown that poverty is associated with both shorter sleep duration and worse sleep quality.30”
From Sleep, Health, and Society (2017) · cites this paper as [30]
Household size is negatively associated with sleep, such that more crowded homes are more likely to foster insufficient sleep.
“For example, household size is negatively associated with sleep, such that more crowded homes are more likely to foster insufficient sleep.30”
From Sleep, Health, and Society (2017) · cites this paper as [30]
A positive relationship between income and insufficient sleep after adjusting for covariates suggests that money may not buy sleep, but many benefits of income may contribute to healthy sleep.
“A positive relationship between income and insufficient sleep after adjusting for covariates suggests that money may not buy sleep, but many of the benefits of income may contribute to healthy sleep.”
From Sleep, Health, and Society (2017) · cites this paper as [30]
In an analysis of more than 350,000 US adults, insufficient sleep was associated with poverty before adjusting for covariates.
“For example, in an analysis of data from greater than 350,000 US adults, insufficient sleep was associated with poverty before adjusting for covariates, but after adjustment, the opposite relationship was seen.30”
From Sleep, Health, and Society (2017) · cites this paper as [30]
After adjustment for covariates, the relationship between income and insufficient sleep was opposite to the pre-adjustment relationship.
“For example, in an analysis of data from greater than 350,000 US adults, insufficient sleep was associated with poverty before adjusting for covariates, but after adjustment, the opposite relationship was seen.30”
From Sleep, Health, and Society (2017) · cites this paper as [30]
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Quantifying impact of real-world barriers to sleep: The Brief Index of Sleep Control (BRISC)
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Self-citationThe Cost of Sleep Lost: Implications for Health, Performance, and the Bottom Line
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Sleep, Diet and Physical Activity Among Adults Living With Type 1 and Type 2 Diabetes
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Rest-activity rhythms in emerging adults: implications for cardiometabolic health
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The impact of environmental exposures on sleep
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Factors associated with sleep quality in university students
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Sleep: The silent hero in cardiometabolic health
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Individual Correlates of Sleep Among Childbearing Age Women in Canada
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Quality of Sleep and Work Productivity among White-Collar Workers during the COVID-19 Pandemic
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Multidimensional Environmental Factors and Sleep Health for Aging Adults: A Focused Narrative Review
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Predictor of sleep difficulty among community dwelling older populations in 2 African settings
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Association between sleep and overweight/obesity among women of childbearing age in Canada
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Mobile technology, sleep, and circadian disruption
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Sleep in Young Adults: Comparing Foster Care Alumni to a Low-Income Sample
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Self-citationSleep during travel balances individual sleep needs
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Predictors of Changes in Sleep Duration in Dutch Primary Schoolchildren: the ChecKid Study
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- Authors
- Grandner, M. A., Jackson, N. J., Izci-Balserak, B., Gallagher, R. A., Murray-Bachmann, R., Williams, N. J., Patel, N. P., & Jean-Louis, G.
- Affiliations
- University of Pennsylvania (US)
- University of Southern California (US)
- SUNY Downstate Health Sciences University (US)
- NYU Langone Health (US)
- Reading Hospital (US)
- Corresponding author
- Grandner, Michael A.
- Venue
- Frontiers in Neurology
- Publisher
- Frontiers Media SA
- Published
- 2015-06-05
- Volume
- 6
- Pages
- 112-112
- ISSN
- 1664-2295 (ISSN-L)
- PMC
- PMC4456880
- OpenAlex
- W1865895031
- Cited by
- 202
- References
- 77
- Citations by year
- 2026: 11 · 2025: 24 · 2024: 18 · 2023: 22 · 2022: 29 · 2021: 20 · 2020: 17 · 2019: 22 · 2018: 20 · 2017: 10 · 2016: 9
- FWCI
- 19.64
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Neurology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- American Heart Association
- University of Pennsylvania
- Georgia Clinical and Translational Science Alliance
- National Heart, Lung, and Blood Institute (K23HL110216)
- National Institute of Nursing Research (K99NR013187)
- National Institute of Environmental Health Sciences (R21ES022931)
- National Center for Research Resources (UL1RR024134)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
- Social Sciences › Health › Health disparities and outcomes
- Keywords
- insufficient sleep, sleep duration, social determinants of health, behavioral risk factors, sociodemographic factors, socioeconomic status, health behavior, diet, physical activity, smoking, alcohol consumption, health insurance, marital status, race and ethnicity, cardiometabolic risk
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