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10.1186/s13690-024-01394-2
Research
Association between sleep duration and sleep quality with pre-sarcopenia in the 20–59-year-old population: evidence from the National Health and Nutrition Examination Surveys 2005–2014
Dong Xiuxun 1
He Lei 2
Zhang Li 3
Shen Yang hayyshy@njmu.edu.cn

1
1 https://ror.org/00xpfw690 grid.479982.9 0000 0004 1808 3246 Department of Clinical Nutrition, The Affiliated Huaian No.1 People’s Hospital of Nanjing Medical University, 1 Huanghe West Road, Huaian, 223300 Jiangsu Province China
2 https://ror.org/0555ezg60 grid.417678.b 0000 0004 1800 1941 National & Local Joint Engineering Research Center for Mineral Salt Deep Utilization, Huaiyin Institute of Technology, Huaian, 223003 Jiangsu Province China
3 https://ror.org/05vawe413 grid.440323.2 0000 0004 1757 3171 Department of Clinical Nutrition, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, 264000 Shandong Province China
18 9 2024
18 9 2024
2024
82 16220 6 2024
6 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

Sarcopenia is a musculoskeletal disease characterized by a significant reduction in muscle mass, strength, and performance. As it mostly affects older adults, it is often recognized as a disease of old age. However, sleep is also closely related to its development. Hence, it becomes critical to explore the relationship between sleep and sarcopenia in populations under 60 years of age to develop strategies for preventing sarcopenia. We here aim to explore the specific association between sleep duration and sleep quality with pre-sarcopenia in the non-elderly population using large population samples.

Methods

This study involved 7,187 participants aged 20–59 years from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2014. Pre-sarcopenia is defined based on the appendicular skeletal muscle mass (ASM) adjusted for body mass index (BMI). Self-reported sleep duration was categorized into three groups: <6 h (short sleep), 6–8 h (normal sleep), and > 8 h (long sleep). Sleep quality was assessed based on the Sleep Disorder and Trouble Sleeping Questionnaire. Univariate analysis and multivariate logistic regression were used to examine the relationship between sleep duration and sleep quality with pre-sarcopenia.

Results

Sleep quality was significantly linked with the risk of pre-sarcopenia (OR 1.72, 95% CI 1.36–2.18, P < 0.01). Longer or shorter sleep duration did not affect the risk of pre-sarcopenia, in contrast to normal sleep duration. Subgroup analysis demonstrated a more pronounced association in individuals who are > 40 years old (P < 0.01), non-Hispanic (P ≤ 0.01), overweight (P < 0.01), have a higher income (P < 0.01), and are more educated (P ≤ 0.01). Moreover, this association was noted in populations with or without smoking (P < 0.01) and alcohol consumption (P < 0.01), hypertension (P < 0.01) and diabetes (P ≤ 0.02).

Conclusion

Sleep quality is associated with an increased risk of pre-sarcopenia, while sleep duration is not in the population aged 20–59 years. Further prospective cohort studies with a large sample size are needed to determine causality and develop effective interventions for preventing sarcopenia in the population aged 20–59 years.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-024-01394-2.

Keywords

Pre-sarcopenia
Sleep quality
Sleep duration
NHANES
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
==== Body
pmc Text box 1. Contributions to the literature	
• Currently, there is limited public health policy attention given to the relationship between sleep and pre-sarcopenia, particularly regarding sleep quality.	
• This study found that poor sleep quality significantly increases the prevalence of pre-sarcopenia in adults aged 20–59, while there is no significant association between sleep duration and pre-sarcopenia.	
• Public health policies should prioritize improving sleep quality over merely focusing on sleep duration to more effectively prevent pre-sarcopenia in adults aged 20–59.	

Background

Sleep deprivation and poor sleep quality have become common health disorders in modern society [1]. According to a recent study, nearly 27.1% of Americans suffer from sleep disorders [2]. Sleep disorders are strongly associated with chronic diseases, such as hypertension, diabetes, cardiovascular disease, and certain types of cancers [3–6]. To maintain good physical and mental health, the Sleep Research Society and the American Academy of Sleep Medicine recommend that adults should sleep 7 h every night [7, 8]. However, sleep involves more than just its duration, including both quantitative and qualitative aspects [9]. The quality of sleep, including sleep continuity, and the circadian rhythm of sleep are critical for maintaining overall health [10]. In recent years, the relationship between sleep and sarcopenia has become a research hotspot [11, 12].

Sarcopenia is an age-related disorder characterized by an increasing decline in muscle mass. It creates an enormous clinical challenge for patients and burdens their daily lives [13]. Evidence suggests that people with sarcopenia have a threefold increased risk of death, experience functional decline, have fall-related injuries and hospitalizations, and are less likely to be satisfied with their lives [14, 15]. Further, sarcopenia is associated with higher hospitalization costs [16–18].

Pre-sarcopenia is a condition characterized by low skeletal muscle mass but normal muscle functions [19]. Sarcopenia is associated with a decline in skeletal muscle strength, accompanied by a decline in muscle mass. Sarcopenia is a disorder generally found in the older population. However, modern lifestyles have gradually led to an increase in its prevalence among young adults [20]. Therefore, it has become highly desirable to develop preventive strategies for young adults with a high risk of sarcopenia [21].

The accelerated pace of modern life has seriously challenged the duration and quality of sleep in young adults. Studies have shown that middle-aged adults with delayed sleep timings are more likely to suffer from sarcopenia [22, 23]. Although several studies have found a association between sleep duration and sarcopenia, there is some controversy surrounding this finding. Two community-based studies have shown that a sleep duration of less than 6 h or more than 8 h is associated with a higher risk of sarcopenia [24, 25]. In contrast, Kim et al. reported that sarcopenia among women is associated with higher sleep duration only [26, 27]. Therefore, understanding the role of sleep in pre-sarcopenia in the population aged 20–59 years is essential for developing relevant strategies to minimize the occurrence of sarcopenia. Thus, the primary objective of the present study is to examine the relationship between sleep duration and sleep quality with pre-sarcopenia in the population aged 20–59 years using a nationally representative sample in the United States.

Methods

Study design and participants

Data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2014 were cross-sectionally analyzed. The study was approved by the National Center for Health Statistics and the NCHS Research Ethics Review Board (https://www.cdc.gov/nchs/nhanes/irba98.htm). All study participants provided written informed consent. This study was performed in accordance with the tenets of the Declaration of Helsinki and the relevant guidelines.

The original data set included 14,546 participants. We excluded 7,359 participants because of the missing data on pre-sarcopenia, sleep, and covariates; higher age (≥ 60 years); pregnant participants; and those weighing over 204 kg or taller than 195 cm. Our final analysis included 7,187 participants (Fig. 1).

Fig. 1 Schematic of specific patient screening process

Measurements and definition of pre-sarcopenia

From 2005 to 2014, NHANES data files on dual-energy X-ray absorptiometry (DXA) were collected to obtain complete results. DXA measurements of body composition were performed using the Hologic QDR-4500 A fanbeam densitometer (Hologic, Inc., Bedford, MA, USA). Clinical practices measure skeletal muscle mass in the legs and arms as a whole, typically known as appendicular skeletal muscle mass (ASM). Skeletal muscle mass index (SMI) was calculated by adjusting the ASM for BMI based on the recommendations of the Foundation for the National Institutes of Health Sarcopenia [28, 29]. Pre-sarcopenia is defined in men as having an SMI of < 0.789 and in women as having an SMI of < 0.512 [30].

Assessment of sleep quality

We measured sleep status using three questions, as in previous studies [31, 32]. Participants who responded “yes” to the question “Have you ever told a doctor or other health professional that you have trouble sleeping or a sleep disorder?” were identified as having a sleep trouble or sleep disorder. Next, participants were asked, “How much sleep do you get (hours)?” to identify their sleep duration. Sleep duration was classified as short (< 6 h/day), normal (6–8 h/day), and long (> 8 h/day) [33]. Sleep was evaluated based on two dimensions: sleep quality and sleep duration [34]. Participants without any sleep trouble and sleep disorder were defined as having good quality sleep, while those with sleep trouble or sleep disorder were defined as having poor quality sleep.

Covariates

A clinical experience-based and literature-based definition of the covariates was used, which included the following: sex (male or female); ethnicity (non-Hispanic White, non-Hispanic Black, Mexican American, and other); family income (≤$20,000 or >$20,000); educational level (< high school, high school, or > high school); living with a partner (yes or no); current smoking status (no or yes) [35]; current alcohol use (no or yes) [36]; presence of hypertension (no or yes) [37]; and presence of diabetes mellitus (DM) (no or yes) [38].

Statistical analysis

An unweighted frequency and a weighted estimated population proportion or weighted standard error (SE) were calculated for each variable. A t-test or chi-square test was performed for both continuous and categorical data. Univariate analysis was used to assess the association between sleep duration and sleep quality with pre-sarcopenia across sex-specific populations. Stratified analysis and adjusted multivariable regression analysis were performed to explore associations between sleep quality and the pre-sarcopenia risk. Statistical significance was defined as a P-value of 0.05 for all analyses performed using R 4.1.2.

Results

Participant characteristics

Baseline characteristics of the participants with pre-sarcopenia are presented in Table 1. In total, 7,187 participants were included in the study, of whom 555 (273 females [49.2%]) were diagnosed with pre-sarcopenia. As expected, the mean age and SE of the pre-sarcopenia group was 43.64 ± 0.58, while that for participants without pre-sarcopenia was 39.00 ± 0.31. In addition, participants with pre-sarcopenia had higher levels of BMI, lower levels of education, and lower levels of annual family income compared to those of participants without pre-sarcopenia (P < 0.01). In addition, the pre-sarcopenia group had a lower proportion of current smokers (P = 0.02) and alcoholic drinkers (P < 0.01) than those in the non-pre-sarcopenia group. Individuals with poor sleep quality have an increased prevalence of pre-sarcopenia (P < 0.01), as evidenced by the prevalence of sleep disorders (P < 0.01) and trouble sleeping (P < 0.01). However, no significant association was noted between pre-sarcopenia and sleep duration (P = 0.06).

Table 1 Characteristics of adults with and without pre-sarcopenia (N = 7187)

	Non-pre-sarcopenia
(N = 6632)	Pre-sarcopenia
(N = 555)	P-value	
Age, mean (SE)	39.00(0.31)	43.64(0.58)	< 0.01	
Sex (N, Weighted %)			0.13	
 Male	3437(92.44)	282(7.56)		
 Female	3195(93.46)	273(6.54)		
BMI (N, Weighted %)			< 0.01	
 ≤25	2377(98.63)	48(1.37)		
 25–30	2226(95.03)	143(4.97)		
 >30	2029(84.70)	364(15.30)		
Ethnicity (N, Weighted %)			< 0.01	
 Non-Hispanic White	2862(94.09)	191(5.91)		
 Non-Hispanic Black	1510(97.63)	38(2.37)		
 Mexican American	901(84.09)	183(15.91)		
 Other	1359(89.44)	143(10.56)		
Annual family income (N, Weighted %)			< 0.01	
 ≤$20,000	1459(90.97)	159(9.03)		
 >$20,000	5173(93.33)	396(6.67)		
Living with a partner (N, Weighted %)			0.80	
 No	2685(92.81)	208(7.19)		
 Yes	3947(93.01)	347(6.99)		
Education (N, Weighted %)			< 0.01	
 Less than high school	1153(88.84)	166(11.16)		
 High school	1430(90.90)	150(9.10)		
 More than high school	4049(94.49)	239(5.51)		
Current smoking (N, Weighted %)			0.02	
 No	4941(92.44)	452(7.56)		
 Yes	1691(94.47)	103(5.53)		
Current drinking (N, Weighted %)			< 0.01	
 No	1530(87.93)	211(12.07)		
 Yes	5102(94.25)	344(5.75)		
Hypertension (N, Weighted %)			< 0.01	
 No	4889(94.29)	340(5.71)		
 Yes	1743(89.22)	215(10.78)		
DM (N, Weighted %)			< 0.01	
 No	6049(93.95)	430(6.05)		
 Yes	583(81.09)	125(18.91)		
Sleep quality (N, Weighted %)			< 0.01	
 Good	5074(94.23)	372(5.77)		
 Poor	1558(89.40)	183(10.60)		
Sleep disorder (N, Weighted %)			< 0.01	
 No	6167(93.76)	469(6.24)		
 Yes	465(83.66)	86(16.34)		
Trouble sleeping (N, Weighted %)			< 0.01	
 No	5154(94.00)	383(6.00)		
 Yes	1478(89.83)	172(10.17)		
Sleep hours (N, Weighted %)			0.06	
 6–8	5236(93.30)	413(6.70)		
 <6	1023(91.62)	98(8.38)		
 >8	373(90.95)	44(9.05)		
DM: diabetes mellitus; BMI: body mass index

Univariate analysis to determine the prevalence of pre-sarcopenia based on sleep duration and sleep quality

Univariate analysis was performed to assess the effect of sleep duration and sleep quality on pre-sarcopenia. Table 2 shows that poor sleep quality significantly increases the prevalence of pre-sarcopenia by 1.94 times (P < 0.01). Furthermore, sleep disorder and trouble sleeping significantly increased the prevalence of pre-sarcopenia by 2.93 and 1.77 times, respectively (P < 0.01). However, both < 6 h (P = 0.07) as well as > 8 h (P = 0.08) of sleep did not significantly increase the prevalence of pre-sarcopenia compared to that observed with normal sleep duration (6–8 h) (Table 3). Similarly, both long and short sleep durations were not significantly associated with pre-sarcopenia, with these associations being consistent across both males and females (P > 0.05).

Table 2 Univariate analysis for assessing the association between sleep quality and pre-sarcopenia

Sleep quality	Pre-sarcopenia (OR (95% CI))	P-value	
Sleep quality			
Good	Reference		
Poor	1.94(1.58,2.38)	< 0.01	
Sleep disorder			
No	Reference		
Yes	2.93(2.09,4.12)	< 0.01	
Trouble sleeping			
No	Reference		
Yes	1.77(1.46,2.15)	< 0.01	
OR: adjusted odds ratio; 95% CI: 95% confidence interval of odds ratio

Table 3 Univariate analysis for assessing the association between sleep duration and pre-sarcopenia

Sleep duration (h)	Pre-sarcopenia (OR (95% CI))	P-value	
Complete sample			
6–8	Reference		
< 6	1.27(0.98,1.66)	0.07	
> 8	1.39(0.96,2.01)	0.08	
Men			
6–8	Reference		
< 6	1.36(0.93,2.00)	0.12	
> 8	1.47(0.87,2.47)	0.15	
Women			
6–8	Reference		
< 6	1.15(0.83,1.59)	0.39	
> 8	1.35(0.76,2.38)	0.30	
OR: adjusted odds ratio; 95% CI: 95% confidence interval of odds ratio

Multivariate logistic regression of the relationship between pre-sarcopenia and sleep duration and sleep quality

We established logistic regression models to analyze the relationship between pre-sarcopenia and sleep quality (Table 4). After adjustment for age, BMI, annual family income, ethnicity, education, smoking, drinking, hypertension, and diabetes, the prevalence of pre-sarcopenia in the group with poor sleep quality was 1.72 times than in the good sleep quality group (P < 0.01). Furthermore, subgroup analyses showed that sleep disorders and trouble sleeping significantly increased the prevalence of pre-sarcopenia by 1.91 and 1.60 times, respectively (P < 0.01).

Table 4 Adjusted multivariable logistic regression analysis for assessing the association between sleep quality and pre-sarcopenia

Sleep quality	Pre-sarcopenia (aOR (95% CI))	P-value	
Sleep quality			
Good	Reference		
Poor	1.72(1.36, 2.18)	< 0.01	
Sleep disorder			
No	Reference		
Yes	1.91(1.28, 2.84)	< 0.01	
Trouble sleeping			
No	Reference		
Yes	1.60(1.28, 1.99)	< 0.01	
Regression analyses adjusted for age, BMI, annual family income, ethnicity, education, smoking, drinking, hypertension, and DM

aOR: adjusted odds ratio; 95% CI: 95% confidence interval of the odds ratio

Stratified analysis association between pre-sarcopenia and sleep quality

Stratified analyses were performed based on sex, age, ethnicity, BMI, annual family income, educational level, marital status, hypertension, diabetes, smoking status, and drinking status to investigate the link between sleep quality and pre-sarcopenia in diverse populations (Table 5). We found significant interactions among age, sex, ethnicity, and education level in the relationship between sleep quality and sarcopenia (P for interaction = 0.05, < 0.01, 0.01, and 0.03, respectively). A significant association effect of sleep quality with pre-sarcopenia was noted in individuals aged 40–50 years (P < 0.01) as well as in those aged 50–60 years (P = 0.03). Individuals with or without comorbid conditions, such as hypertension, diabetes, smoking, or drinking, can also exhibit this significant interaction (P < 0.01).

Table 5 Association between sleep quality and pre-sarcopenia according to different variables

	Pre-sarcopenia	P-value	P for interaction	
Age			0.05	
20–30 years	1.38(0.74,2.59)	0.31		
30–40 years	0.92(0.49,1.71)	0.78		
40–50 years	2.60(1.73,3.91)	< 0.01		
50–60 years	1.68(1.07,2.65)	0.03		
Sex			< 0.01	
Male	2.58(1.98,3.36)	< 0.01		
Female	1.45(1.07,1.98)	0.02		
Ethnicity			0.01	
Non-Hispanic White	2.80(2.04,3.84)	< 0.01		
Non-Hispanic Black	2.35(1.20,4.60)	0.01		
Mexican American	1.29(0.84,1.98)	0.24		
Other	1.55(0.98,2.45)	0.06		
BMI			0.15	
≤ 25	1.56(0.65,3.72)	0.31		
25–30	1.14(0.72,1.80)	0.58		
> 30	1.92(1.50,2.46)	< 0.01		
Annual family income			0.18	
<$20,000	1.41(0.93,2.14)	0.10		
≥$20,000	2.08(1.57,2.76)	< 0.01		
Living with a partner			0.24	
No	2.22(1.70,2.90)	< 0.01		
Yes	1.78(1.33,2.37)	< 0.01		
Education			0.03	
Less than high school	1.03(0.65,1.64)	0.88		
High school	1.88(1.17,3.00)	0.01		
More than high school	2.50(1.81,3.47)	< 0.01		
Hypertension			0.76	
No	1.80(1.30,2.48)	< 0.01		
Yes	1.69(1.27,2.23)	< 0.01		
DM			0.52	
No	1.67(1.34,2.08)	< 0.01		
Yes	2.04(1.14,3.66)	0.02		
Current smoking			0.64	
No	1.96(1.52,2.52)	< 0.01		
Yes	2.23(1.36,3.66)	< 0.01		
Current drinking			0.85	
No	1.91(1.26,2.88)	< 0.01		
Yes	2.01(1.48,2.73)	< 0.01		
DM: diabetes mellitus; BMI: body mass index

In addition, significant interactions were found between the annual family income and the association between sleep disorder and pre-sarcopenia (P for interaction = 0.02, Supplementary Table 1). Age and ethnicity were also found to be significantly interactions with the association between trouble sleeping and sarcopenia (P for interaction = 0.05, Supplementary Table 2). Moreover, both indicators (sleep disorder and trouble sleeping) were found to be associated with pre-sarcopenia in individuals aged 40–50 years, overweight individuals, those with a higher annual income, with these associations being consistent across both males and females.

Discussion

This cross-sectional study was conducted based on the survey data collected over 10 years in the United States. This research showed that sleep quality (aOR = 1.72, 95CI%: 1.36–2.18) is associated with pre-sarcopenia in the population aged 20–59 years. No significant association was noted between long sleep duration (> 8 h) or short sleep duration (< 6 h) with pre-sarcopenia compared to those with normal sleep duration (6–8 h) in the abovementioned population.

Long sleep duration plays an important role in the development of sarcopenia. A meta-analysis demonstrated that sleep duration is associated with obesity, cardiovascular disease, diabetes mellitus, and mortality from all causes, compared to normal sleep duration [39]. Our results showed that the prevalence of pre-sarcopenia was higher among participants with a long sleep duration compared to those with normal sleep duration (9.05% vs. 6.70%). Moreover, participants who slept long hours had a 1.39 times higher prevalence of pre-sarcopenia than those who slept normal hours. However, there was no statistically significant difference between long sleep duration and pre-sarcopenia in the 20–59-year-old population. Hu et al. conducted a study on people aged more than 60 years in Chinese communities and demonstrated that sarcopenia was associated with long sleep duration only in women. They did not report any significant difference among men [24]. However, no such differences could be seen in our further univariate analysis. The direct mechanism of the association between long sleep duration and sarcopenia remains unclear, although several studies have suggested various potential mechanisms. Fielding et al. found that increasing sleep duration could decrease physical activity, which could, in turn, lead to the development of sarcopenia [40]. Furthermore, Gildner carried out a longitudinal study that showed that prolonged sleep may impair cognitive functions, resulting in various physical problems, such as reduced lower limb strength and gait dysfunction [41]. Alternatively, the results of a recent cross-sectional study showed that individuals who sleep > 9 h/day are at an increased risk of sarcopenia owing to obesity [42]. Research conducted in mouse models suggests that obesity increases the levels of pro-inflammatory cytokines, which could be an important contributor to sarcopenia [43]. Notably, both Asian and Caucasian participants exhibited a significant association between longer sleep duration and a high sarcopenia risk, indicating that sleep duration is not associated with genetic susceptibility [11].

Short sleep duration is also associated with serious health problems, such as obesity, diabetes, hypertension, and cardiovascular disease [44]. Short sleep duration is linked with a greater prevalence of pre-sarcopenia than normal sleep duration (8.38% vs. 6.70%). After correcting for multiple influencing factors, reduced sleep duration was not found to be significantly associated with the risk of pre-sarcopenia in the 20–59-year-old population. A dose–response meta-analysis showed a U-shaped association between sleep duration and sarcopenia. Participants who slept 6 h had an increased risk of sarcopenia [45]. Similarly, Chien et al. found a U-shaped relationship between sleep duration and sarcopenia, and that the risk of sarcopenia was three times greater in those who slept < 6 h than in those who slept 6–8 h [25]. Several pathophysiologic mechanisms may mediate the link between sleep deprivation and sarcopenia. Animal study has shown that shorter sleep duration increases cortisol levels and causes low-level inflammation, resulting in oxidative and proteolytic pathways that cause sarcopenia [46]. Alternatively, shortened sleep duration may induce insulin resistance through multiple metabolic pathways, which may damage muscle elasticity and accelerate muscle deterioration, leading to sarcopenia [47].

Compared to sleep duration, sleep quality plays a more important role in the development of various systemic diseases. For example, a study on hearing loss showed that only the quality of sleep is associated with hearing loss, but not the duration of sleep [48]. Sleep quality has been shown to be associated with sarcopenia or its influencing factors in the elderly population [49]. Our finding also revealed similar results, that is, pre-sarcopenia has a significant association with sleep quality but not with sleep duration in people aged 20–59 years. Simultaneously, the risk of sarcopenia in participants with poor sleep quality was 1.72 times higher than in those with good sleep quality. Shibuki et al. demonstrated that insomnia is significantly associated with sarcopenia, with a 1.67 times risk than that of normal sleepers [33]. During regular sleep, body damage is gradually repaired and rejuvenated, such as protein synthesis and hormone production, all of which contribute to muscle growth [50]. However, when the circadian rhythm is disrupted, the body exhibits a chronic inflammatory state. As a result, protein synthesis in the muscle is reduced, which causes hydrolysis of muscle protein, resulting in sarcopenia [51].

The results of a Spanish cohort of middle-aged and older adults showed that neither sleep duration nor sleep quality were associated with sarcopenia, and only depression was associated with it [52]. However, a Chinese study showed a significant correlation between depression and sarcopenia, and subgroup analyses showed that sleeping less than 8 h increased the risk [53]. Depression is associated with reduced physical activity and changes in muscle metabolism, increasing the risk of sarcopenia is well established [54, 55]. However, differences in the role of sleep in the relationship between depression and sarcopenia may be the result of different populations and differences in sample size, and further research is still needed to elucidate.

Gender differences in sarcopenia are also of concern. Kwon et al. conducted a cohort study in Korea and reported a prevalence of 14.3% for sarcopenia. It also reported that men had a higher prevalence of sarcopenia (18.7%) than women (9.7%) [27]. In addition, our study showed a higher prevalence of pre-sarcopenia in men compared to women, consistent with previous studies. This result could be explained by the fact that men have a higher muscle mass than women, although the magnitude of muscle loss with age is greater for men than it is for women [56]. In contrast, an over-69-year-old Spanish study reported a higher prevalence of sarcopenia in women than in men, possibly because of differences in the prevalence of sarcopenia at different age intervals [56]. This aspect needs to be further investigated.

Our results show that pre-sarcopenia is associated with alcohol consumption, which is consistent with previous findings [57]. The elevated prevalence of pre-sarcopenia among individuals in the alcohol consumption group could be attributed to the impact of alcohol on skeletal muscle. Studies in vivo suggest that alcohol may affect the synthesis of muscle proteins and impair their function, and that excessive alcohol intake is a lifestyle that may lead to sarcopenia [58].

In the present study, we showed that a large sample size allows for a more representative and comprehensive analysis of the relationship between sleep and the prevalence of pre-sarcopenia. The study on the independent effect of sleep on the prevalence of pre-sarcopenia can be made more reliable by adjusting for various confounding variables. However, there are potential limitations to consider. First, the study participants were recruited from specific health centers in the United States. Therefore, the results may not be relevant to other populations. Second, the study design was based on a cross-sectional analysis, which did not allow for the determination of a causal relationship between sleep and pre-sarcopenia. More longitudinal research is needed to clarify the causal relationships between sleep and pre-sarcopenia. Third, self-reported sleep duration is likely to be subject to recall bias and therefore not very precise. Fourth, physical activity, as well as medication history, is well known to affect sleep quality and sarcopenia risk. However, these variables were not controlled for during the study. Future studies should take these limitations into account when investigating the relationship between sleep and pre-sarcopenia.

Conclusion

Our research provided evidence that poor sleep quality, but not sleep duration, is associated with an increased risk of pre-sarcopenia in people aged 20–59 years. Further prospective cohort studies with a large sample size are needed to determine causality and develop effective interventions for the prevention of sarcopenia among 20–59-year-old people.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Acknowledgements

We thank Bullet Edits Limited for the linguistic editing and proofreading of the manuscript.

Author contributions

Yang Shen drafted the manuscript. Xiuxun Dong designed the study. Lei He and Li Zhang analyzed the data. All authors read and approved the final manuscript for publication.

Funding

This study did not receive any funding and there are no financial conflicts of interest.

Data availability

The data sets generated during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The Research Ethics Review Committee approved the NHANES survey protocol. Institutional Review Board approval and documented consent was obtained from participants (https://www.cdc.gov/nchs/nhanes/irba98.htm).

Consent for publication

All authors of the manuscript have read and agreed to its content and are accountable for all aspects of the accuracy and integrity of the manuscript in accordance with ICMJE (International Committee of Medical Journal Editors) criteria.

Competing interests

The authors declare no competing interests.

Abbreviations

ASM Appendicular skeletal muscle mass

NHANES National Health and Nutrition Examination Survey

SE Standard error

SMI Skeletal muscle mass index

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