Sleep Health
– Dr Tripat Deep Singh

Sleep Health: A meaningful measure of relationship between Sleep and our health

Sleep health is a new concept to understand the relationship between Sleep and our health. It is recognized now that following multidimensional features characterize “Sleep Health” in young and old adults1,2

  1. Sleep Duration– It refers to how many hours you sleep at night
  2. Sleep Timing– It refers to at what time you go to sleep at night. Different chronotypes prefer either early or late bed times
  3. Sleep Regularity– It refers to having a regular bedtime and wake up time on weekdays and weekends thereby maintaining regular sleep duration
  4. Sleep Efficiency– It refers to how much time you were asleep out of the total time in bed at night and expressed as percentage.
  5. Sleep quality– Subjectively it is assessed by asking the person “how well rested you feel after last night sleep” and it’s one’s personal perception about the quality of their Sleep.

I think it’s better to quantify sleep quality and following parameters of “Sleep continuity” define Sleep quality quantitatively3

  • Sleep Onset Latency (Good Sleep Quality= 0-30 min, Poor Sleep Quality= >45min)
  • Number of awakenings >5 minutes (0-1)
  • Wake after sleep onset (WASO) (<10min or 11-20min) and
  • Sleep efficiency (>95% or 85-94%)

A recent study has also given cut-off values for different dimensions of Sleep health and computed Sleep health score based on these values which showed strong correlation to cardiovascular health.1 I feel it’s a great contribution by the authors in helping to quantify Sleep health.

Currently most of the definitions of “Sleep Deprivation” are based on the Sleep duration and the published literature have looked at the relationship between Sleep duration and the harmful effects on health with conflicting results.4-7

I feel that it’s high time that we start analyzing Sleep as a multidimensional state and consider all the different dimensions to study Sleep health and its relation to our overall health.

Sleep duration does not tell everything about health status

It has been shown that Sleep deprivation as defined by Sleep duration leads to poor health outcomes with conflicting results.4-7 This makes it important to include other parameters of Sleep Health beyond Sleep duration while analyzing someone’s sleep as they have shown important correlations to overall health.

A recent study used three complimentary multivariable modelling approaches for survival endpoints: Cox regression, tree-structured survival analysis, and a random survival forest to study different dimensions of sleep and their relationship to mortality in older men.8 They studies sleep duration, timing, continuity, alertness, quality and rhythmicity. Low sleep continuity and low sleep rhythmicity were associated with all-cause mortality in older people (mean age=76yrs).8 Current sleep recommendations from the National Sleep Foundation9 and the American Academy of Sleep Medicine10 are primarily focused on sleep duration, and this study highlights the importance of other parameters like sleep continuity and rhythmicity and not sleep duration to be associated with all-cause mortality in older people explaining the conflicting results from studies which focused on sleep duration only.

Another study on 1259 subjects, studied the relationship of self-reported sleep duration, sleep quality assessed by Pittsburgh Sleep Quality Index (PSQI) and polysomnography parameters with weight gain.11 The authors reported that poor subjective sleep quality and SpO2<90% were associated with >5Kg weight gain over a 5.3yr follow up period and not sleep duration or other sleep characteristics.11

Absence of Sleep regularity (Irregular sleep duration) and not sleep duration has been shown to be associated with poorer microvascular function as early as young adulthood.12 These findings support the growing body of evidence that irregular sleep patterns may be an independent and modifiable risk factor for CVD.

Questionnaires can also be used to assess multidimensional aspects of Sleep health. RU-SATED is one such questionnaire to assess subjective Sleep health.13 RU-SATED questionnaire takes following dimensions of Sleep into consideration- Satisfaction, Alertness, Timing, Efficiency and Duration. A recent study analyzed relationship between poor sleep health assessed by RU-SATED questionnaire, poor diet and low physical activity with self-reported health status.14 Poor Sleep health defined by RU-SATED questionnaire was associated with poor self- perceived health status, followed by poor diet and low physical activity.14 This study suggests that multidimensional sleep habits and not only sleep duration should be included among the important modifiable health risk factors and be considered a key component of a healthy lifestyle.

Another study included multidimensional aspects of Sleep as assessed by 1 week of actigraphy data including night time sleep duration, wake after sleep onset (WASO), sleep timing, and daytime napping and studied their relationship with cardiometabolic risk score as assessed by Framingham risk score in IT workers and nursing home workers.15 Following Sleep health metrics- more sleep efficiency, less WASO, and less daytime napping (having no naps, fewer naps, and shorter nap duration) were linked to lower cardiometabolic risk score in nursing home workers. Sleep duration was not associated with cardiometabolic risk score.15 This study also highlights the importance of taking napping into consideration while evaluating relationship between multi dimensions of Sleep and overall health. Most of the studies evaluating relationship between sleep duration and different health parameters have not asked about napping habit.

Overall health can be affected by amount of physical activity, age, mental health, intake of medications and comorbid diseases besides poor sleep. All are important for health but it is important to understand how each of these factors affecting health fare against each other for appropriate policy making and prioritizing the resources. A recent study included Multidimensional sleep domain which included-Total Sleep Time, Bed Time, Wake-up Time, Time in Bed, Sleep Efficiency, Sleep Latency, Napping, subjective Sleep quality and the Epworth Sleepiness Scale- was a significant predictor of both all-cause and cardiovascular mortality.16 This study also highlighted that predictive ability of multidimensional Sleep health domain ranked lower than that of the physical health, sociodemographic (including age), mental health, and medication domains, but higher than that of the health behaviors domain and several well-established individual non-sleep predictors (e.g., self-rated health status, heart failure). The most predictive individual sleep characteristics across outcomes were time in bed, hours spent napping, and wake-up time. Authors suggested that future research should develop tools for measuring multidimensional sleep – especially those incorporating time in bed, napping, and timing and not only sleep duration—and test mechanistic pathways through which these characteristics relate to mortality.

In adults there are conflicting reports of association between Sleep duration and obesity.6 Actigraphy based assessment of multidimensional sleep health (sleep efficiency, midpoint, duration, regularity, and self-report measures of alertness and satisfaction ) in women in their middle ages showed no cross-sectional or longitudinal associations between multidimensional sleep health and adiposity.17 This study highlights that the conflicting results in earlier studies may be due to focusing on sleep duration only or including older age populations.

Mindfulness may be a great tool for professionals who constantly face stressful conditions  like nurses. Mindfulness is defined as receptive attention and awareness of what is taking place in the present moment without evaluating it as good or bad.18 a study showed that optimal sleep health (sleep efficiency, duration, regularity, and self-report measures of alertness and satisfaction) is an antecedent of daily mindful attention in nurses. Improving sleep may provide important benefits to their well-being and to the quality of patient care. 19 The authors also reported that at the between-person level, participants with greater sleep sufficiency, higher sleep quality, and fewer insomnia symptoms reported greater mindful attention overall.

Above data highlights the importance of focusing on multidimensional nature of Sleep health and not only sleep duration while monitoring and evaluating the influence of Sleep on health.

Consumer Sleep Technologies (CST’s) do not measure multidimensional aspects of Sleep Health

CST’s have made people get involved with their sleep and also allowed continuous monitoring of Sleep for several nights continuously which was not possible with polysomnography. It helped us to understand various current trends in sleep duration. But, currently available CST’s monitor sleep duration and to the best of my knowledge none of the current CST’s measure multidimensional aspects of Sleep Health which have been shown to be more informative about one’s health.

I hope that in near future CST measuring multidimensional nature of Sleep health become available for more meaningful monitoring of our patients and population Sleep health.

Sleep health as a multidimensional construct is a very welcoming and timely development and I hope to see it becoming the standard of Sleep evaluation in the clinics.


1.           Brindle RC, Yu L, Buysse DJ, Hall MH. Empirical derivation of cutoff values for the sleep health metric and its relationship to cardiometabolic morbidity: results from the Midlife in the United States (MIDUS) study. Sleep. 2019;42(9).

2.           Wallace ML, Yu L, Buysse DJ, et al. Multidimensional sleep health domains in older men and women: an actigraphy factor analysis. Sleep. 2021;44(2).

3.           Ohayon M, Wickwire EM, Hirshkowitz M, et al. National Sleep Foundation’s sleep quality recommendations: first report. Sleep Health. 2017;3(1):6-19.

4.           Kurina LM, McClintock MK, Chen JH, Waite LJ, Thisted RA, Lauderdale DS. Sleep duration and all-cause mortality: a critical review of measurement and associations. Ann Epidemiol. 2013;23(6):361-370.

5.           Cappuccio FP, D’Elia L, Strazzullo P, Miller MA. Sleep duration and all-cause mortality: a systematic review and meta-analysis of prospective studies. Sleep. 2010;33(5):585-592.

6.           Patel SR, Hu FB. Short sleep duration and weight gain: a systematic review. Obesity (Silver Spring). 2008;16(3):643-653.

7.           Itani O, Jike M, Watanabe N, Kaneita Y. Short sleep duration and health outcomes: a systematic review, meta-analysis, and meta-regression. Sleep Med. 2017;32:246-256.

8.           Wallace ML, Stone K, Smagula SF, et al. Which Sleep Health Characteristics Predict All-Cause Mortality in Older Men? An Application of Flexible Multivariable Approaches. Sleep. 2018;41(1):zsx189.

9.           Hirshkowitz M, Whiton K, Albert SM, et al. National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health. 2015;1(1):40-43.

10.        Watson NF, Badr MS, Belenky G, et al. Recommended Amount of Sleep for a Healthy Adult: A Joint Consensus Statement of the American Academy of Sleep Medicine and Sleep Research Society. Sleep. 2015;38(6):843-844.

11.        Häusler N, Heinzer R, Haba-Rubio J, Marques-Vidal P. Does sleep affect weight gain? Assessing subjective sleep and polysomnography measures in a population-based cohort study (CoLaus/HypnoLaus). Sleep. 2019;42(6).

12.        Hoopes EK, Berube FR, D’Agata MN, et al. Sleep duration regularity, but not sleep duration, is associated with microvascular function in college students. Sleep. 2021;44(2).

13.        Buysse DJ. Sleep health: can we define it? Does it matter? Sleep. 2014;37(1):9-17.

14.        Dalmases M, Benítez I, Sapiña-Beltran E, et al. Impact of sleep health on self-perceived health status. Scientific Reports. 2019;9(1):7284.

15.        Buxton OM, Lee S, Marino M, Beverly C, Almeida DM, Berkman L. Sleep Health and Predicted Cardiometabolic Risk Scores in Employed Adults From Two Industries. Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine. 2018;14(3):371-383.

16.        Wallace ML, Buysse DJ, Redline S, et al. Multidimensional Sleep and Mortality in Older Adults: A Machine-Learning Comparison With Other Risk Factors. J Gerontol A Biol Sci Med Sci. 2019;74(12):1903-1909.

17.        Bowman MA, Brindle RC, Joffe H, et al. Multidimensional sleep health is not cross-sectionally or longitudinally associated with adiposity in the Study of Women’s Health Across the Nation (SWAN). Sleep Health. 2020;6(6):790-796.

18.        Brown KW, Ryan RM, Creswell JD. Mindfulness: Theoretical Foundations and Evidence for its Salutary Effects. Psychological Inquiry. 2007;18(4):211-237.

19.        Lee S, Mu C, Gonzalez BD, Vinci CE, Small BJ. Sleep health is associated with next-day mindful attention in healthcare workers. Sleep Health. 2021;7(1):105-112.