Sleep Architecture, Muscle Function, and Daily Life Activities in Patients with Sarcopenia

Abstract

Objective

To examine associations between polysomnography, muscle mass and strength, and daily life activity index (DLAI) in patients with sarcopenia.

Materials and Methods

We measured polysomnography, muscle mass and strength, and DLAI in 16 patients with sarcopenia and 26 controls > 60 years old and then compared variables and correlations in the patients with sarcopenia.

Results

We found no differences in polysomnography between patients with sarcopenia and controls. Among patients with sarcopenia, latency to rapid eye-movement (REM) sleep was positively correlated with weight, REM %, and total sleep time was positively correlated with grip strength. Latency of REM sleep was negatively correlated with body mass index, NREM sleep, and apnea index was negatively correlated with grip strength. Daily life activity index correlated positively with grip strength.

Conclusion

Patients with sarcopenia showed significant correlations between polysomnography and weight, body mass index, and grip strength, suggesting a complex relationship involving sleep architecture, muscle function, and DLAI that deserves more research.

 

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Keywords

sarcopenia - polysomnography - muscle mass - grip strength - daily life activities index

Introduction

Aging refers to progressive changes in an individual that lead to the decline of biological, physiological, psychological, and behavioral-social processes. These changes are important, because in our contemporary societies, there is an increasing number of elderly people who are affected by the deleterious effects of aging.

The muscular system attains maximal performance in youth, after which muscle mass begins to decrease with aging. The generalized and gradual loss of skeletal muscle mass and physical fitness is called: sarcopenia.[1] Muscle loss may result in sleep alteration because sarcopenia can produce hypotonia of the palatal and pharynx muscles thus producing snoring and obstructive sleep apnea.[2] The relationship between low muscle strength and sleep impairment in older age groups has also been studied, and some investigators have reached the conclusion that early symptoms of sarcopenia are influenced by sleep duration and quality in both genders.[3]

Another research studied the association between subjective sleep quality and probably sarcopenia in older adults. The authors found that poor sleep quality was associated with an increased likelihood of sarcopenia in older adults.[4] In another study, the authors studied the effect of sleep quality in the development of presarcopenia. They define presarcopenia in base to appendicular skeletal muscle mass. In addition, they have studied sleep duration, while sleep quality was assessed by a standardized questionnaire. They found that sleep duration was not related to presarcopenia, while sleep quality was associated with an increased risk of presarcopenia.[5] However, not all researchers agree regarding the role of sleep duration in the development of sarcopenia. Chen et al. studied the association between sleep duration measured by a self-administrated questionnaire and sarcopenia in China. They disclosed that sleep deprivation is associated with the development of sarcopenia in middle-aged and elderly people.[6] It is, therefore, important to understand sleep in populations affected by aging, including those with sarcopenia.

Sarcopenia is an important alteration of increased prevalence with functional disabilities and limitations among older people. One review found data that suggested that sarcopenia is associated with low quality of life measured by a sarcopenia-specific questionnaire.[6] The investigation called attention to the need to identify and treat the alterations that impact the quality of life in the elderly.

Although some alterations of polysomnographic (PSG) variables had been described in patients with sarcopenia,[3] the relationship among PSG measurements and the changes in muscle strength and daily life behaviors in aging has not been well studied. Thus, the aim of the present study was to examine possible associations between PSG measurements with variables of skeletal muscle mass and strength, and with the scale of life functionality in patients with sarcopenia. Our working hypothesis was that sleep architecture was worse in patients with sarcopenia than in controls, and that these changes are related to PSG measurements.

 

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Materials and Methods

Participants

We recruited a group of patients with sarcopenia consisting of adults > 60 years old who volunteered to attend our sleep disorders clinic after posting an open invitation on our official Facebook page. Sarcopenia was diagnosed based on the following criteria: self-report of muscle power loss, hand grip < 27 kg for men and < 16 kg in women, and bioelectric impedance measurement of skeletal muscle measurement < 20 kg for men and < 15 kg for women.[1] Subjects with cognitive impairment, acute heart disease or with a heart pacemaker, equilibrium disorder, neuromuscular disease, multiple sclerosis, Parkinson's disease, myasthenia gravis, depression, anxiety or other alterations were excluded from the study. The control group was composed of volunteer subjects in the same age range who were healthy or had mild and controlled arterial hypertension without muscle power loss. The research protocol was approved by the Ethics and Research Committee of the institution. All participants were informed of the importance of their participation and the objectives of the study and signed an informed consent form for their participation in the research and publication of results.

 

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Polysomnography

We performed an all-night PSG study with patients sleeping in a comfortable bed of a suite room constructed for this purpose in our sleep disorders clinic from 10 PM to 6 AM. Recording was performed with a neurovirtual PSG/electroencephalography (EEG) equipment model BWII (Equipamos LLC), following international guidelines. Six disk EEG electrodes were placed on the patient's scalp after cleaning at the following locations: F3, F4, C3, C4, O1, O2, with contralateral mastoid reference: (M1, M2) according to the international 10–20 EEG system for electrode location. Moreover, left and right electro-oculogram; chin electromyography (EMG); air flow from nose, and thorax and abdomen movements pletismography; oxygen saturation; D2 electrocardiography and EMG of leg movements over anterior tibial muscles were recorded simultaneously. Each variable was visually scored following the guidelines of the American Academy of Sleep Medicine (version 2.0).[8]

The PSG variables studied were as follows: sleep latency, latencies to non-rapid eye movement (NREM) sleep, REM sleep latency; total and, N1, N2, and NREM sleep time, slow wave sleep time, REM sleep time (TST), and awakenings. The breathing variables were as follows: apnea index, apnea/hypopnea index (AHI), maximal apnea duration, total apnea time, and oxygen saturation.

 

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Muscle Function Measurements

The amount of muscle mass was measured by electric bioimpedance at 500 KHz, and < 500 micro-Amperes with an Omron, Model HBF-514C impedanciometer (OMRON Healthcare). The grip strength of the dominant hand was measured with a DS2 Camry electronic hand dynamometer (CAMRY). Examinations were performed between 9 AM and 12 PM.

 

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Daily Life Activities Index

We used the daily life activities index (DLAI) that is the most used scale for evaluating geriatric population. The test comprises 6 items that correspond to daily life activities such as: 1. taking a shower, 2. dressing, 3. use of the bathroom, 4. mobility, 5. urinary and fecal sphincter control, and 6. eating. The full index was calculated from the level of performance of each activity, according to which subjects totally who could perform all of daily life activities independently received A score, those with limitation in one aspect of the DLAI received B, those with limitation in two aspects received C, and those with three or more limitations received D, in the standard fashion.[9] The questionnaires were answered after muscle function measurements between 9:30 AM and 12:30 PM.

 

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Statistics

The sample size was calculated in relation to the difference of the meaning of N2 sleep state duration (as the most significant difference between groups) from a previous study of sleep disorders in patients with sarcopenia,[2] with a β power of 80%. The mean of quantitative variables and percentages of qualitative variables were calculated. Comparisons of quantitative variables between groups were performed with the student's t test for independent groups as the most appropriate method to compare two independent groups with identical variance. Because not all data was continuous, correlations between PSG, muscular variables, and performance of DLAI were performed by means of the Spearman's coefficient calculation within the group of patients with sarcopenia. The IBM SPSS Statistics for Windows (IBM Corporation), version 20.0 was used for calculations. The threshold of significance was p < 0.05.

 

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Results

Comparisons between Patients with Sarcopenia and Controls

Our study included 16 patients with sarcopenia and 26 controls. The mean age of the group of patients with sarcopenia was 68 ± 7.8 years of age, and for the control group it was 68 years ± 6.8. Body weight in the group of sarcopenia patients was 84.79 ± 16.64, and in the control group it was 79.95 ± 17.03 Kg. Height in the group of sarcopenia patients was 1.57 ± 0.17 m, and in the control group it was 1.63 ± 0.16 m. Body mass index (BMI) in the group of sarcopenia patients was 34.06 ± 9.19, and for the control group it was 29.86 ± 5.65. There were no significant differences between the sarcopenia and control groups in any of these characteristics.

 

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PSG Variables

We found no significant differences in the quantitative sleep and breathing variables in PSG recordings between the group of patients with sarcopenia and controls ([Tables 1] and [2]).

Table 1 Comparison of polysomnographic variables between the control group and patients with sarcopenia.

Variable	Controls: mean ± SD	Sarcopenia: mean ± SD	p	95% confidence intervals
NREM latency (min)	35.43 ± 25.68	24.95 ± 18.72	0.47	-18.73–39.69
REM latency (min)	188.74 ± 104.40	191.58 ± 114.35	0.49	-49.63–101.28
N1%	18.59 ± 13.14	16.62 ± 9.71	0.60	-5.71–9.65
N2%	47.14 ± 15.98	51.71 ± 16.55	0.37	-14.97–5.82
N3%	21.95 ± 12.82	21.09 ± 14.57	0.84	-7.80–9.52
REM%	14.04 ± 7.13	10.58 ± 8.03	0.30	-2.34–7.25
N1 (min)	55.77 ± 41.60	51.40 ± 29.33	0.71	-19.70–28.42
N2 (min)	160.02 ± 77.06	179.06 ± 88.90	0.46	-71.50–33.42
N3 (min)	75.00 ± 37.90	69.65 ± 32.42	0.75	-21.50–29.36
REM (min)	49.00 ± 34.13	49.05 ± 30.42	0.51	-14.80–29.33
Total sleep time (min)	332.30 ± 116.40	335.91 ± 108.62	0.92	-76.52–69.30
Awakenings	262.62 ± 99.63	272.81 ± 139.60	0.78	-84.84–64.45

Abbreviations: NREM, no rapid eye movements sleep stage; REM, rapid eye movements sleep stage; SD, standard deviation.

Table 2 Comparison of respiratory variables between controls and patients with sarcopenia.

Variable	Controls	Sarcopenia	p	95% confidence interval
Mean apnea index	50.01 ± 24.81	50.17 ± 22.03	0.91	-14.44–16.13
Mean apnea-hypopnea index	58.12 ± 35.68	51.88 ± 26.48	0.55	-14.65–27.13
Mean apnea maximal duration (s)	46.21 ± 30.17	41.06 ± 26.00	0.52	-13.26–23.56
Mean total apnea time (min)	36.92 ± 41.72	39.50 ± 50.63	0.85	-31.65–26.48
Mean oxygen saturation (%)	86.62 ± 3.98	87.00 ± 5.55	0.70	-3.35–2.59

 

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Muscle Function Measurements

Muscle mass in the control group (22.80 ± 5.93 Kg) was significantly greater than in the group of patients with sarcopenia (18.56 ± 3.27 Kg) (p = 0.01). Hand grip power in the control group was also significantly greater (25.25 ± 9.57 Kg) than in the group of patients with sarcopenia (18.86 ± 5.58 Kg) (p = 0.02) (see [Fig. 1]).

Fig. 1 Comparison of muscle strength and muscle mass between controls and patients with sarcopenia. The first two columns show a grip strength (Kg) comparison between controls and patients with sarcopenia, with significant greater values in controls (*). Columns three and four show a comparison of body mass (Kg) between controls and patients with sarcopenia, with significant greater values in controls (*).

 

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Daily Life Activities Index

With respect to the DLAI, three participants from the control group and one patient with sarcopenia presented limitations and dependence on one item. One participant of the control group presented dependence for two items of daily activities, and one patient with sarcopenia presented dependence for three items of the DLAI ([Table 3]).

Table 3 Scores on the questionnaire of Daily Life Activities Index of controls and patients with sarcopenia.

Value	Controls	Sarcopenia	Percentage
A	22	14	86
B	3	1	9.6
C	1	0	2.2
D	0	1	2.2
Total	61.9	38.1	100

Notes: A score was assigned to those subjects without limitation in any aspect of DLAI scale. Subjects with limitation in one aspect received B; those with limitation in two aspects, C; and those with limitation in three or more, D.

 

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Correlations among Variables within the Group of Patients with Sarcopenia

Latency to REM sleep showed positive correlations with weight and with BMI ([Table 3]). REM % of sleep showed a positive correlation with grip strength ([Table 3]). Total sleep time showed a positive correlation with grip strength ([Table 4]).

Table 4 Significant correlations between polysomnographic variables and anthropometrics and muscle function measurements.

	Grip strength	Weight	BMI
NREM time r (p)	-0.59 (0.02)	−	−
NREM % r (p)	-0.54 (0.02)	−	−
REM latency r (p)	−	0.62 (0.02)	0.67 (0.01)
REM % r (p)	0.54 (0.02)	−	−
TST r (p)	0.68 (0.04)	−	−
AI r (p)	-0.65 (0.006)	−	−

Abbreviations: AI, apnea index; BMI, body mass index; NREM, no rapid eye movements sleep stage; REM, rapid eye movements sleep stage; TST, total sleep time.

Non-rapid eye movement sleep time and its percentage showed negative correlation with grip strength in patients with sarcopenia ([Table 4]). The apnea index showed a negative correlation with grip strength ([Table 3]).

The DLAI score presented a positive significant correlation with grip strength (r = 0.62, p = 0.009).

 

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Discussion

We found no differences in PSG results between patients with sarcopenia and controls. However, the correlation analysis suggests that within patients with sarcopenia, individuals that spent more time in NREM sleep had a weak grip strength; and those that took longer to initiate REM sleep had higher weight and BMI; subjects with greater TST and percentage of REM sleep had more grip strength; patients with higher apnea index score had a weak grip strength. The assessment of daily activities showed, for the first time, that it is associated with muscle strength, and the DLAI score was found to be negatively associated with hand grip. Because we were looking for the relationship between PSG measurements and the changes in muscle strength associated with daily life behaviors, these results are in agreement with our objective.

The lack of differences between groups in PSG records show that sleep architecture was not disturbed by sarcopenia during the early stages of the disease, judged by low DLAI scores with absence of significant disability or minimal alterations.

What the current study adds to the literature is that within the group of patients with sarcopenia, the relationships between latency to REM sleep and BMI, and between grip strength and NREM, REM, TST and DLAI suggest a complex relationship of sleep function with skeletal muscle mass loss during the progression of sarcopenia.

It is noteworthy that grip strength was the variable that most frequently correlated with sleep measurements and DLAI. These findings suggest that sleep is needed to repair muscle fibers,[10] benefiting muscle strength necessary for daily life activities.[11] Thus, our data suggests that clinicians could suspect a sleep disorder in patients with sarcopenia when they present weak grip strength, and high BMI and weight.

Some concrete actions must be taken to improve life quality in patients with Sarcopenia and their sleep: 1. To promote a graduated program of exercise, that has proven to prevent strength loss and improve sleep quality,[12] 2. To give them an adequate nutritional intake, chrono-administered, that has the potential to augment muscle mass and re-program the circadian clock.[13]

The results of the present study may impact the attention brought to patients with sarcopenia and sleep disorders in at least two ways: 1. To raise suspicion of the presence of sleep disorders in patients with presarcopenia and sarcopenia when there is decrease of hand grip strength, with the objective to give them an early intervention, and 2. Early attention to and treatment of sleep disorders in patients with sarcopenia to improve their sleep quality and daily life activities.[14]

Matsumoto et al. investigated the association between obstructive sleep apnea severity and computed tomography measures of skeletal muscle loss in 334 subjects that were suspected of suffering from obstructive sleep apnea. They found that the AHI correlated positively with the skeletal mass index and negatively with skeletal mass density, while the severity of obstructive sleep apnea correlated with the increase in skeletal muscle mass rather than muscle depletion and skeletal muscle adiposity.[15] Although they used a different measurement to quantify the degree of sarcopenia, their results are in some way, consistent with ours. However, since no individuals with severe sleep apnea were included in our study, more research is needed to better understand the relationship between sarcopenia and sleep apnea over the full range of severity of both conditions.

Piovezan et al. found that sarcopenic obesity, but not obesity in general, was associated with obstructive sleep apnea, and that obesity and sarcopenic obesity, but not sarcopenia alone, were associated with night hypoxemia, suggesting a pathophysiological relationship between body composition and obstructive sleep apnea.[16] Although, there are methodological differences between this study and our data, the results from both studies suggests a relationship between sleep disturbances and muscle mass loss, related in a complex way with sleep alterations.

In another study, Piovezan et al. studied PSG variables and subjective sleep data in 1,902 participants 40 to 80 years old with sarcopenia. They found that objective short and long sleep, sleep efficiency, awakenings, and obstructive sleep apnea were associated with lower muscle mass, older adults were more susceptible to sleep alteration, producing an age-related obstructive sleep apnea.[3] The quoted articles evidenced sleep alterations secondary to sarcopenia, but more research is needed to clarify and relate those findings with our data.

Age-related muscle loss may be due to decreases in both the number of muscle fibers and the size of muscle cells.[17] Decreased exercise frequency and/or intensity results in loss of muscle strength, which has been observed to contribute to a decrease in strength for daily life activities, especially those that require muscle effort.[18] Thus, grip strength has been considered a predictor for disability with sarcopenia,[19] and was correlated with worst scores in sleep architecture. Contrarily, a recent observation suggests that after 12 weeks of resistance exercise training, sleep architecture improves in patients with sarcopenia, possibly due to an increase of anti-inflammatory markers, such as interleukin-10 and interleukin-1 receptor antagonist, in older sarcopenic adults.[20]

Proposed Hypothesis

Sarcopenia may result from a decrease in the frequency and/or intensity of exercise, which leads to loss of strength and muscle mass in patients with sarcopenia. This may cause the brain to hold on to catabolic substances that affect sleep, because physical activity helps to clean toxins from the nervous system. This idea must be tested in future studies.

 

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Strength and Limitations

This is an initial study to search for a relationship among sleep architecture, muscle function, and DLAI in individuals with sarcopenia. The sample size is small, although it was calculated to be of enough size to detect differences in PSG, muscle function parameters, and DLAI between patients with sarcopenia and a group of healthy control participants. It is a statistical rule that the more observations, the more predictive power. Thus, our results must be taken as trends and not as strong conclusions. Among other limitations of the study, we recognize that the cross-sectional design has no power to predict temporal changes in the development of sarcopenia, sleep alterations, and daily life activities. The number of patients and controls was sufficient for this initial study, but a larger number of participants in both groups would increase the predictive power and allow us to find differences in comparisons among groups, and find stronger correlations between muscle function, and daily activities, in the sleep of patients with sarcopenia. In addition, quantifying muscle loss using imaging and biochemical variables would enrich the observation with objective variables to compare and correlate alterations in future observations.

 

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Conclusion

Sarcopenia does not result in PSG differences in sleep microarchitecture in the early stages of the disease compared with a control group. However, among patients with sarcopenia, weaker grip strength was associated with higher proportion of NREM sleep and lower proportion of REM sleep, TST, higher apnea index, and lower DLAI score, while higher BMI and weight were associated with higher latency to REM sleep. Together, these findings suggest a complex relationship involving sleep architecture, muscle function, and DLAI variables.

 

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Conflict of Interests

The authors have no conflict of interests to declare.

Authors' Contributions

ELR: study conception and design, data collection and analysis. GMR, RSM, DSV, AP, and RGE: study design and analysis. All authors wrote and approved the final version of the manuscript.

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Publication History

Received: 17 September 2024

Accepted: 07 March 2025

Article published online:
08 July 2025