Skip to main content
  • Research article
  • Open access
  • Published:

Associations of sleep quality and sleep duration with frailty and pre-frailty in an elderly population Rugao longevity and ageing study

Abstract

Background

Previous studies suggest that poor sleep quality or abnormal sleep duration may be associated with frailty. Here we test the associations of sleep disturbances with both frailty and pre-frailty in an elderly population.

Methods

Participants included 1726 community-dwelling elders aged 70–87 years. Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep disturbances. Frailty was defined using phenotype criteria. Logistic regression models were used to estimate odds ratio of the associations.

Results

The average PSQI score was 5.4 (SD, 3.1). Overall 43.6% of the participants had poor sleep quality (PSQI> 5), 8.2% had night sleep time ≤ 5 h, and 27.8% had night sleep time ≥ 9 h. The prevalence of frailty and pre-frailty was 9.2 and 52.8%, respectively. The proportions of PSQI> 5 increased with the severity of frailty status (robust: pre-frail: frail, 34.5%: 48%: 56.1%, P < 0.001). After adjustment for multiple potential confounders, poor sleep quality (PSQI> 5) was associated with higher odds of frailty (OR = 1.78, 95% CI 1.19–2.66) and pre-frailty (OR = 1.51, 95% CI 1.20–1.90). Sleep latency, sleep disturbance, and daytime dysfunction components of PSQI measurements were also associated with frailty and pre-frailty. In addition, sleep time 9 h/night was associated with higher odds of frailty and pre-frailty.

Conclusions

We provided preliminary evidences that poor sleep quality and prolonged sleep duration were associated with being frailty and pre-frailty in an elderly population aged 70–87 years. The associations need to be validated in other elderly populations.

Peer Review reports

Background

Frailty is a clinical syndrome characterized by loss of physiologic reserve and resistance to stressors due to cumulative declines across multiple physiologic systems. Frailty results in vulnerability to adverse outcomes including restricted mobility, reduced self-reliance and disability, falls, hospitalization, and mortality [1,2,3]. Frailty is a public health problem with a prevalence of about 10% in the community-dwelling elderly population [4]. However, frailty and pre-frailty are reversible conditions if appropriately treated. Therefore, identifying high risk elders of frailty for specific management of underlining causes is important to prevent from developing to more advanced condition, such as disability. Several risk factors of frailty had been proposed and some had been validated, such as age, low socioeconomic status, cognitive impairment, and diabetes [5, 6].

Sleep disturbances are common and serious problems of the elderly population [7, 8]. About 50% of the elderly people suffers from sleep problems [7]. Sleep is extremely important to health since human body carries out a series of biological and physiological activities during sleep process, such as hormonal release, energy metabolism, glucose and cardiovascular regulation, and self-regulation and recovery of physiological functions [9]. Sleep disorders were found to be associated with increased risks of different adverse outcomes, such as obesity, hypertension, cognitive impairment, depression, and death [10,11,12,13,14].

Recently, poor sleep quality was reported to be associated with prevalent [15, 16] and incident frailty at follow-up in U.S. community-dwelling elders [17]. In addition, an U-shaped sleep duration-frailty association [17, 18] or prolonged sleep duration-frailty relationship [19, 20] was also reported to community dwellers. However, more evidences need to be accumulated before sleep disturbances established as a behavior risk factors of frailty.

In this study, we aimed to investigate the associations of different symptoms of sleep disturbance (poor sleep quality, several components of sleep quality, prolonged and insufficient sleep duration) with frailty in a community-dwelling population aged 70–87 years.

Methods

Study design and participants

We used data of the ageing arm of the Rugao Longevity and Ageing Study (RuLAS), a population-based observational two-arm cohort study conducted in Rugao, a typical, medium-sized city of Jiangsu province, China. The ageing arm of RuLAS is a longitudinal cohort followed-up every 1.5 years. A detailed description of this study was provided elsewhere [21]. Briefly, we recruited 1788 elders from 31 rural communities of Jiang’an Township of Rugao city between in Nov-Dec. 2014 (wave1) according to 5-year age and sex strata. From Apri. 2016 through Jun. 2016, we conducted the second-wave examination of the ageing arm, excluding 297 subjects (55 died and 242 did not come) and including an additional 333 subjects. Among the participants in the second wave, 1726 subjects aged 70–87 years with complete data on sleep and frailty variables were included in the present study. During the fieldwork, all participants were taken a fasting blood sample drawn. Then they participated in a face-to-face interview and physical examination. All of them answered a structured questionnaire themselves. This study was approved by the Human Ethics Committee of the School of Life Sciences of Fudan University, Shanghai, China. Written informed consents were obtained from all the participants.

Sleep measurements

The participants finished the Pittsburgh Sleep Quality Index (PSQI) at wave 2 survey.The PSQI questionnaire consists of 19 items which include components of sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, sleep medication use, and daytime dysfunction [22]. Each component is coded on a 4-point scale (0–3), with high scores reflecting more sleep symptoms. The Chinese version of the PSQI have good overall reliability (r = 0.82–0.83) and test-retest reliability (r = 0.77–0.85) in community adults with primary insomnia [23]. Global scores provide an assessment of overall sleep quality which ranges from 0 to 21, with scores of > 5 indicating poor sleep quality [23].

Frailty measurements

The widely used Fried’s phenotype criterion includes unintentional weight loss, weakness, exhaustion, slowness, and low activity components [24]. We used a similar definition to measure frailty phenotype [25, 26]. In brief, unintentional weight loss, exhaustion, and low activity were measured with self-reported items “weight has decreased by 4.5 kg or 5% during the last 12 months”, “energetic most of the time or feeling tired all of the time (at least 3 or 4 days a week)”, and “needing help to walk”, respectively. Slowness was defined as being below the 20th sex-specific percentile in gait speeds measured with a timed ‘up and go’ (TUG) test (the time stand up from an armchair, walk 3 m, return, and sit down again). Weakness was defined as being below the 20th sex-specific percentile in maximum handgrip strength. Grip strength in kilograms was measured using a dynamometer (Shanghai Wanqing Rlrctron Co. Ltd., Shanghai, China) for three attempts of each hand. The max value of two hands was used in this study. Participants with any three or more indicators is defined as “frail”, any one or two is pre-frail, and zero is“non-frail”.

Covariates

Covariates included age (70–74 years, 75–79 years, 80–84 years, 85+ years), gender (men; women), occupation (farmers, others), marital status (currently married, others), education level (illiterate; literate), smoking (none; ever, current smoker), drinking status (none, ever, current drinker), perceived overall health status (good, poor), and body mass index (BMI, < 24 kg/m2, 24 to 27.9 kg/m2, or ≥ 28 kg/m2) [27]. Diabetes was defined as having a diabetic history, on any anti-diabetic agent, or a fasting plasma glucose level of> 7.0 mmol/L.

Hypertension was defined as having a hypertension history, or a mean blood pressure higher than 140/90 mmHg, or on any antihypertensive agent. The Hasegawa Dementia Scale-Revised (HDS-R), including 11 items to measure orientation, memory, attention/calculation and verbal fluency, is a widely used brief and reliable measurement for evaluating global cognitive function [28, 29]. The presence of mild cognitive impairment (MCI) was defined by a HDS-R of ≤21.5 [30].

Statistical analysis

Descriptive statistics were used as percentages or mean ± standard deviation (SD). The Chi-square test was used for comparison of categorical variables among frail groups. Logistic regression models were used to estimate odds ratios and 95% confidence intervals for the associations of sleep variables with frailty. Potential confounding factors adjusted including age, gender, occupation, marital status, education level, smoking status, drinking status, BMI category, hypertension, diabetes, MCI, and perceived overall health. Statistical analyses were performed with IBM SPSS 19.0 (IBM Corporation, Armonk, NY, USA). A two-sided p < 0.05 was considered significant.

Results

Characteristics of the study population

The average PSQI score of the studied elderly population (aged 77.6 ± 3.9 years) was 5.4 (SD, 3.1) and the average night sleep time 7.6 h (SD, 1.7 h). Overall 43.6% of the elderly adults had poor sleep quality (PSQI> 5), 8.2% had night sleep time ≤ 5 h, and 27.8% had night sleep time ≥ 9 h. The prevalence of frailty and pre-frailty was 9.2 and 52.8%, respectively. The percentages of female, illiterate, uncoupling, diabetes, MCI decreased from robust to pre-frail, then to frailty groups while the percentages of smokers and alcohol drinkers increased (p < 0.05) (Table 1).

Table 1 Demographic characteristics of participants by frailty status

Associations of sleep quality with frailty

The proportions of participants with poor sleep quality (PSQI> 5) increased with the severity of frailty in the elderly (robust: pre-frail: frail, 34.5%: 48%: 56.1%, P < 0.001) (Table 2).

Table 2 Distribution and comparison of the PSQI scores among robust, pre-frail and frail groups

After adjustment for multiple potential confounders including age group, gender, occupation, education, smoking, drinking, BMI category, diabetes, hypertension, MCI, and perceived overall health status, poor sleep quality (PSQI> 5) was associated with higher odds of being frailty (OR = 1.78, 95% CI 1.19–2.66). With 1 point increments in PSQI score, the odds ratio of frailty increased by 16% (OR = 1.16, 95% CI (1.09–1.23). Poor sleep quality defined by PSQI> 5 was also significantly associated with the odds of pre-frailty compared with the robust participants independent of other factors pre-frailty (OR = 1.51, 95% CI 1.20–1.90). With per SD increments in PSQI score, the multivariable-adjusted odds of pre-frailty increased by 11%, OR = 1.11, 95% CI (1.04–1.13) (Table 3). In addition, using PSQI> 6 as cut-point [23], we also found significant associations of poor sleep quality with increased odds of pre-frailty and frailty (data not shown).

Table 3 Associations between sleep quality and components of sleep quality and frailty status by logistic regression analysis

Associations of sleep quality component with frailty

For components of PSQI, on the whole, higher percentages of sleep symptoms were found in sleep quality component, sleep latency component, sleep duration component, sleep efficiency component, sleep disturbance component, and daytime dysfunction component from robust group to pre-frail group, and then to frail group (Table 2). After adjustments for multiple covariates, sleep latency, sleep disturbance, and daytime dysfunction components were significantly associated with higher odds of pre-frailty and frailty (Table 3).

Associations of sleep duration with frailty

Table 4 showed the associations between reported sleep duration and frailty. The odds of being frail in those with a sleep time ≤ 5 h per night was significantly increased compared to those with a sleep time 7–8 h. However, the OR attenuated with the addition of adjustment variables and was not statistically significant after adjustment for sleep quality.

Table 4 Associations between sleep duration and frailty status by logistic regression analysis

Long sleep duration of ≥9 h, compared with sleep 7-8 h, was associated with increased risk of pre-frailty (OR = 1.82, 95% CI 1.37–2.42) and frailty (OR = 2.98, 95% CI 1.95–4.56), and the correlation was not affected by other factors such as sleep quality (Table 4).

Discussion

In the present study, we found that poor sleep quality, long sleep latency, sleep disturbance, daytime dysfunction, and longed sleep duration were associated with increased odds of frailty in an elderly population. In addition, to the best of our knowledge, for the first time, we found that sleep disturbance variables such as sleep latency, were associated pre-frailty in this elderly population aged 70–87 years.

In the Osteoporotic Fractures in Men (MrOS) cohort of U.S. males aged 67 years and older, Ensrud [15] et al. found that poor subjective sleep quality of PSQI> 5, objective parameters of less sleep efficiency, and objective parameters of sleep disordered breathing were independently associated with a higher odd of being frail in cross-sectional analysis. Later, in a prospective study follow-up of an average of 3.4 years, they replicated these associations [17]. Our results are similar to their observations that poor subjective sleep quality was associated with frailty status in Rugao population. In addition, we extended the associations to pre-frailty status which is even more clinically relevant since it is reversible condition when timely intervened.

Poor sleep quality measured by PSQI was associated with frailty not only in community population setting but also in institutionalized setting where frail elderly (374 elderly residents of long-stay institutions aged 77.52 ± 7.82 years) exhibited poor sleep quality [31]. In addition, the associations were also observed for frailty measured with other instruments. In 351 Atahualpa residents aged ≥60 years, Brutto et al. found that higher scores of the PSQI were significantly associated with higher scores in the Edmonton Frail Scale [16].

For the component of sleep quality, we found that long sleep latency and sleep disturbances were associated with increased risks of pre-frailty and frailty in Rugao population. This is similar to the observations that long sleep latency and poor sleep efficiency measured by objective actigraph were associated with higher odds of prevalent frailty [15] and higher risk of incident frailty [17]. Another significant component associated with frailty we observed in this population aged 70–87 years is daytime dysfunction. To the best of our knowledge, this is the first report correlated daytime dysfunction with frailty status in elderly population since other studies such as Ensrud et al. [15, 17] did not specially analyze the relationship between PSQI components and frailty. However, using the objective actigraph measurements, Ensrud et al. found that another relevant symptoms, excessive daytime sleepiness, were associated with increased odds of frailty in the MrOS cohort [15]. This corroborates our observations from another perspective.

The observations addressing the relationship between sleep duration and frailty were less consistent. Both long sleep duration (≥9 h) and short sleep duration (≤6 h or ≤ 5 h) were associated with higher odds of frailty in Japanese [18] and Danish population [32]. However, only long sleep duration (≥10 h or ≥ 9 h or ≥ 8 h) was found associated with higher odds of frailty in American elderly [19], our Chinese elderly, or Korean elderly people [20], respectively. Interestingly, using data of NHANES cohort of U.S. population, Zhang et al. found that sleeping > 9 h was associated with frailty in males and sleeping < 6 h were associated with frailty in females, which indicate a gender specific association [33]. Low levels of daily exercise, low muscle strength, and very slow walking speeds, all indicative of prefrailty/frailty also showed prolonged sleep duration (≥9 h) in a British elderly population [34]. Since both prolonged sleeping hours and frailty may be manifestations or biomarkers of disease status of the studied participant, in the present study, we adjusted several health variables in the analysis models and still observed the associations. In addition, since elderly people may spend more time in bed when they are frail (i.e. reverse causality), and aforementioned cross-sectional data cannot provide evidence for the direction of the association, evidences in the prospective studies need to be accumulated with respect to the association between sleep duration and frailty.

Several possible underline mechanisms may help explain the associations of sleep disturbances with frailty. (1) sleep symptoms may be markers for comorbidities and poor health which increases the likelihood of frailty [17]. Although we adjusted multiple disease covariates in the present study, we could not exclude this possibility. (2) The disrupted circadian rhythms induced by sleep disorder may contribute to dysregulation of immune system with increased systemic inflammation factors which contribute to the development of frailty [35]. (3) sleep disorder may contribute to increased oxidative stress and alterations of metabolic pathways favoring catabolism, which could serve as a combined risk for the development of frailty [36]. (4) Disturbed sleep may reduce growth hormone, insulin-like growth factor-1, and sex hormone such as testosterone secretion, which in turn enhance muscle proteolysis, thus, leading to sarcopenia and frailty [37]. In the future study, we need to measure these cytokines in our participants to explore whether they mediate the sleep-frailty associations.

The limitations of this study need to be mentioned. The cross-sectional nature of this study prohibits causal inference since the relationship between frailty and sleep disturbances may be bidirectional. In addition, it’s a pity that we did not measure the actigraphic or polysomnographic parameters in our cohort, therefore, we could not validate the objective associations of sleep disturbances and sleep disordered breathing with frailty. Further, a significantly large percentage of the subjects were farmers, such a specific occupation is not only physically demanding that could impact frailty but also have a particularly unique regimental challenges to one’s sleep. This may affect the generalizability of our findings.

Conclusions

In summary, we found that poor subjective sleep quality, some sleep symptoms measured by PSQI, and prolonged sleep duration were associated with higher odds of frailty, and even pre-frailty in an elderly population aged 70–84 years However, since the associations were cross-sectional, the effects of sleep disturbances on frailty incidences need to be validated in the prospective cohort studies of the elderly population of this age group.

Abbreviations

BMI:

Body mass index

CRP:

C reactive protein

DBP:

Diastolic blood pressure

HDS:

Hasegawa Dementia Scale

HDS-R:

Hasegawa Dementia Scale-Revised

MCI:

Mild cognitive impairment

MrOS:

Osteoporotic Fractures in Men

NHANES:

The National Health and Nutrition Examination Survey

OR:

Odds ratio

PSQI:

Pittsburgh Sleep Quality Index

RuLAS:

Rugao Longevity and Ageing Study

SBP:

Systolic blood pressure

TUG:

Up and go

References

  1. Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381:752–62.

    Article  Google Scholar 

  2. Blodgett JM, Theou O, Howlett SE, Wu FC, Rockwood K. A frailty index based on laboratory deficits in community-dwelling men predicted their risk of adverse health outcomes. Age Ageing. 2016;45(4):463–8.

    Article  Google Scholar 

  3. Song X, Mitnitski A, Rockwood K. Prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation. J Am Geriatr Soc. 2010;58(4):681–7.

    Article  Google Scholar 

  4. Collard RM, Boter H, Schoevers RA, Oude Voshaar RC. Prevalence of frailty in community-dwelling older persons: a systematic review. J Am Geriatr Soc. 2012;60(8):1487–92.

    Article  Google Scholar 

  5. Ng TP, Feng L, Nyunt MS, Larbi A, Yap KB. Frailty in older persons: multisystem risk factors and the frailty risk index (FRI). J Am Med Dir Assoc. 2014;15(9):635–42.

    Article  Google Scholar 

  6. Espinoza SE, Fried LP. Risk factors for frailty in the older adult. Clin Geriatr. 2007;15:37–44.

    Google Scholar 

  7. Foley D, Ancoli-Israel S, Britz P, Walsh J. Sleep disturbances and chronic disease in older adults: results of the 2003 national sleep foundation sleep in America survey. J Psychosom Res. 2004;56(5):497–502. https://doi.org/10.1016/j.jpsychores.2004.02.010.

    Article  PubMed  Google Scholar 

  8. 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):361–70. https://doi.org/10.1016/j.annepidem.2013.03.015.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Van Cauter E, Spiegel K, Tasali E, Leproult R. Metabolic consequences of sleep and sleep loss. Sleep Med. 2008;9(Suppl 1):S23–8. https://doi.org/10.1016/S1389-9457(08)70013-3.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Gindin J, Shochat T, Chetrit A, Epstein S, Ben Israel Y, Levi S, Onder G, Carpenter I, Finne-Soveri H, van Hout H, SHELTER project, et al. Insomnia in long-term care facilities: a comparison of seven european countries and Israel: the services and health for elderly in long term care study. J Am Geriatr Soc. 2014;62(11):2033–9. https://doi.org/10.1111/jgs.13099.

    Article  PubMed  Google Scholar 

  11. Gildner TE, Liebert MA, Kowal P, Chatterji S, Snodgrass JJ. Associations between sleep duration, sleep quality, and cognitive test performance among older adults from six middle income countries: results from the study on global ageing and adult health (sage). J Clin Sleep Med. 2014;10(6):613–21. https://doi.org/10.5664/jcsm.3782.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Maglione JE, Ancoli-Israel S, Peters KW, Paudel ML, Yaffe K, Ensrud KE, Stone KL, Study of Osteoporotic Fractures Research Group. Subjective and objective sleep disturbance and longitudinal risk of depression in a cohort of older women. Sleep. 2014;37(7):1179–87. https://doi.org/10.5665/sleep.3834.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Kim J, Jo I. Age-dependent association between sleep duration and hypertension in the adult korean population. Am J Hypertens. 2010;23(12):1286–91. https://doi.org/10.1038/ajh.2010.166.

    Article  PubMed  Google Scholar 

  14. Mesas AE, López-García E, León-Muñoz LM, Guallar-Castillón P, Rodríguez-Artalejo F. Sleep duration and mortality according to health status in older adults. J Am Geriatr Soc. 2010;58(10):1870–7. https://doi.org/10.1111/j.1532-5415.2010.03071.x.

    Article  PubMed  Google Scholar 

  15. Ensrud KE, Blackwell TL, Redline S, Ancoli-Israel S, Paudel ML, Cawthon PM, Dam TT, Barrett-Connor E, Leung PC, Stone KL, Osteoporotic Fractures in Men Study Group. Sleep disturbances and frailty status in older community-dwelling men. J Am Geriatr Soc. 2009;57(11):2085–93. https://doi.org/10.1111/j.1532-5415.2009.02490.x.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Del Brutto OH, Mera RM, Sedler MJ, Zambrano M, Nieves JL, Cagino K, Fanning KD, Milla-Martinez MF, Castillo PR. The effect of age in the association between frailty and poor sleep quality: a population-based study in community-dwellers (the Atahualpa project). J Am Med Dir Assoc. 2016;17(3):269–71.

    Article  Google Scholar 

  17. Ensrud KE, Blackwell TL, Ancoli-Israel S, Redline S, Cawthon PM, Paudel ML, Dam TT, Stone KL. Sleep disturbances and risk of frailty and mortality in older men. Sleep Med. 2012;13(10):1217–25. https://doi.org/10.1016/j.sleep.2012.04.010.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Nakakubo S, Makizako H, Doi T, Tsutsumimoto K, Hotta R, Lee S, Lee S, Bae S, Makino K, Suzuki T, Shimada H. Long and short sleep duration and physical frailty in community-dwelling older adults. J Nutr Health Aging. 2018;22(9):1066–71.

    Article  CAS  Google Scholar 

  19. Baniak LM, Yang K, Choi J, Chasens ER. Long sleep duration is associated with increased frailty risk in older community-dwelling adults. J Aging Health. 2018. https://doi.org/10.1177/0898264318803470.

    Article  Google Scholar 

  20. Kang I, Kim S, Kim BS, Yoo J, Kim M, Won CW. Sleep latency in men and sleep duration in women can be frailty markers in community-dwelling older adults: the Korean frailty and aging cohort study (KFACS). J Nutr Health Aging. 2019;23(1):63–7.

    Article  CAS  Google Scholar 

  21. Liu Z, Wang Y, Zhang Y, Chu X, Wang Z, Qian D, Chen F, Xu J, Li S, Jin L, et al. Cohort profile: the Rugao Longevity and Ageing Study (RuLAS). Int J Epidemiol. 2016;45(4):1064–73. https://doi.org/10.1093/ije/dyv101.

    Article  PubMed  Google Scholar 

  22. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.

    Article  CAS  Google Scholar 

  23. Tsai PS, Wang SY, Wang MY, Su CT, Yang TT, Huang CJ, Fang SC. Psychometric evaluation of the Chinese version of the Pittsburgh sleep quality index (CPSQI) in primary insomnia and control subjects. Qual Life Res. 2005;14(8):1943–52. https://doi.org/10.1007/s11136-005-4346-x.

    Article  CAS  PubMed  Google Scholar 

  24. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, Cardiovascular Health Study Collaborative Research Group, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146–56.

    Article  CAS  Google Scholar 

  25. Zhu Y, Liu Z, Wang Y, Wang Z, Shi J, Xie X, Jin L, Chu X, Wang X. Agreement between the frailty index and phenotype and their associations with falls and overnight hospitalizations. Arch Gerontol Geriatr. 2016;66:161–5. https://doi.org/10.1016/j.archger.2016.06.004.

    Article  PubMed  Google Scholar 

  26. Liu Z, Burgess S, Wang Z, Deng W, Chu X, Cai J, Zhu Y, Shi J, Xie X, Wang Y, et al. Associations of triglyceride levels with longevity and frailty: a Mendelian randomization analysis. Sci Rep. 2017;7:41579. https://doi.org/10.1038/srep41579.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Zhou B, Coorperative Meta-Analysis Group Of China Obesity Task Force. Predictive values of body mass index and waist circumference to risk factors of related diseases in Chinese adult population. Zhonghua Liu Xing Bing Xue Za Zhi. 2002;23:5–10 [Article in Chinese].

    PubMed  Google Scholar 

  28. Tsukamoto R, Akisaki T, Kuranaga M, Takata T, Yokono K, Sakurai T. Hasegawa dementia scale− revised, for screening of early Alzheimer’s disease in the elderly with type 2 diabetes. Geriatr Gerontol Int. 2009;9(2):213–5. https://doi.org/10.1111/j.1447-0594.2009.00524.x.

    Article  PubMed  Google Scholar 

  29. Imai Y, Hasegawa K. The revised Hasegawa’s dementia scale (HDS-R)-evaluation of its usefulness as a screening test for dementia. Hong Kong J Psychiatry. 1994;4(2):20–4.

    Google Scholar 

  30. Liu H, Lu X, Li C, Bai L, Dong X. Studying on relationship between Hasegawa dementia scale and nursing care of senile dementia patients. Mod Nurs. 2001;7:1–2.

    Google Scholar 

  31. Nóbrega PV, Maciel AC, de Almeida Holanda CM, Oliveira Guerra R, Araújo JF. Sleep and frailty syndrome in elderly residents of long-stay institutions: a cross-sectional study. Geriatr Gerontol Int. 2014;14(3):605–12. https://doi.org/10.1111/ggi.12144.

    Article  PubMed  Google Scholar 

  32. van Oostrom SH, van der A DL, Rietman ML, Picavet HSJ, Lette M, Verschuren WMM, de Bruin SR, Spijkerman AMW. A four-domain approach of frailty explored in the doetinchem cohort study. BMC Geriatr. 2017;17(1):196. https://doi.org/10.1186/s12877-017-0595-0.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Zhang Q, Guo H, Gu H, Zhao X. Gender-associated factors for frailty and their impact on hospitalization and mortality among community-dwelling older adults: a cross-sectional population-based study. Peer J. 2018;6:e4326. https://doi.org/10.7717/peerj.4326.

    Article  PubMed  Google Scholar 

  34. Morgan K, Hartescu I. Sleep duration and all-cause mortality: links to physical activity and prefrailty in a 27-year follow up of older adults in the UK. Sleep Med. 2019;54:231–7. https://doi.org/10.1016/j.sleep.2018.11.008.

    Article  PubMed  Google Scholar 

  35. Mehra R. Failing sleep? Beware of frailty or death. Sleep Med. 2012;13(10):1211–2. https://doi.org/10.1016/j.sleep.2012.10.001.

    Article  PubMed  Google Scholar 

  36. Cochen V, Arbus C, Soto ME, Villars H, Tiberge M, Montemayor T, Hein C, Veccherini MF, Onen SH, Ghorayeb I, et al. Sleep disorders and their impacts on healthy, dependent, and frail older adults. J Nutr Health Aging. 2009;13(4):322–9.

    Article  CAS  Google Scholar 

  37. Piovezan RD, Abucham J, Dos Santos RV, Mello MT, Tufik S, Poyares D. The impact of sleep on age-related sarcopenia: possible connections and clinical implications. Ageing Res Rev. 2015;23(Pt B):210–20. https://doi.org/10.1016/j.arr.2015.07.003.

    Article  PubMed  Google Scholar 

Download references

Ethics approval and consent to participate

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee (This study was approved by the Human Ethics Committee of the School of Life Sciences of Fudan University, Shanghai, China.) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written consents were obtained from all participants prior to participation.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was financially supported by grants from the National Key R&D Program of China (2018YFC2002000,2018YFC2000400), the National Natural Science Foundation of China (81571372, 81670465, 81600577). The funders have no role in the study design, the collection, analysis, and interpretation of data, in the writing of this manuscript, and in the decision to submit it for publication.

Author’s contribution

XH Sun and T Ma were responsible for managing the participant database and retrieving follow-up information; they also contributed to article preparation, in the analyses of data and in drafting the article. S Yao, ZK Chen, and WD Xu supervised the ongoing research, taking part in the initiation of the study and contributing to article preparation. XH Sun,T Ma and XY Jiang contributed to analyses of data and in article preparation. XY Jiang and XF Wang conceived the study, participated in its design and coordination, and helped draft the article. All authors read and approved the final article.

Acknowledgments

We acknowledge all participants involved in the present study.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Xiao-Yan Jiang or Xiao-Feng Wang.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, XH., Ma, T., Yao, S. et al. Associations of sleep quality and sleep duration with frailty and pre-frailty in an elderly population Rugao longevity and ageing study. BMC Geriatr 20, 9 (2020). https://doi.org/10.1186/s12877-019-1407-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12877-019-1407-5

Keywords