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Association between nap time, nighttime sleep, and multimorbidity in Chinese older adults: a cross-sectional study

BMC Geriatrics volume 25, Article number: 151 (2025) Cite this article

Abstract

Objective

This study aims to explore the relationship between sleep duration and multimorbidity among elderly Chinese and to determine the optimal sleep duration for preventing multimorbidity.

Methods

This study is based on data from the 2020 China Health and Elderly Care Longitudinal Survey (CHARLS), which collected detailed information from 5,761elderly individuals, including demographic characteristics, sleep duration, health status, and lifestyle information. Logistic regression models were used to investigate the relationship between sleep duration and multimorbidity, and restricted cubic spline analysis was employed to analyze the dose-response relationship between sleep duration and multimorbidity.

Results

After adjusting for potential confounders, a U-shaped association was found between nighttime sleep duration and the likelihood of multimorbidity among the elderly. Specifically, elderly individuals with a nighttime sleep duration of 7 h had the lowest incidence of multimorbidity. Compared to those with 6–8 h of nighttime sleep, elderly individuals with less than 6 h (OR = 1.24, 95% CI: 1.05–1.48) or more than 8 h (OR = 1.79, 95% CI: 1.37–2.34) of nighttime sleep had a 24% and 79% increased likelihood of multimorbidity, respectively. The restricted cubic spline analysis further confirmed this U-shaped relationship, showing that the likelihood of multimorbidity gradually decreased as sleep duration increased from 6 to 7 h, but gradually increased as sleep duration exceeded 7 h. Additionally, a positive correlation was found between napping habits and the likelihood of multimorbidity, with elderly individuals without napping habits having a lower likelihood of multimorbidity compared to those with napping habits. Subgroup analysis indicated no significant differences in the impact of 6–8 h of nighttime sleep on multimorbidity among male and female elderly individuals and different age groups.

Conclusion

Appropriate nighttime sleep duration may be an important factor in preventing multimorbidity among the elderly, while increased napping duration may increase the likelihood of multimorbidity. These findings provide scientific evidence for sleep health management among the elderly, suggesting the promotion of appropriate sleep duration to reduce the likelihood of multimorbidity in this population.

Peer Review reports

Introduction

With the acceleration of global aging, multimorbidity has become a significant public health issue. Projections indicate that by 2050, the elderly population aged 65 and above in China will reach 400 million [1]. The advent of an aging society will inevitably lead to a gradual increase in age-related chronic diseases, and the prevalence of multimorbidity will also rise with age [2]. Multimorbidity is very common among the elderly, with prevalence rates ranging from 30 to 95% across different age groups and countries [3]. Currently, more than one-third of the elderly in China suffer from two or more chronic conditions [4]. There is substantial evidence that multimorbidity leads to various adverse outcomes, such as poor quality of life, high mortality risk, and significant economic burden [5,6,7]. These consequences not only have profound impacts on individual health but also place a heavy burden on the social healthcare system.

The outbreak of the COVID-19 pandemic has significantly highlighted the vulnerability of patients with chronic diseases in the allocation of medical resources, leading to a reduced likelihood of accessing essential medical services. This phenomenon may further exacerbate the potential risk of multimorbidity [8]. The prevalence of multimorbidity among Brazilian adults increased from 18.7% in 2013 to 22.3% in 2019 [9]. Data from some high-income countries also indicate that the incidence of multimorbidity has risen during the COVID-19 pandemic [10–11]. Studies have evaluated the relationship between sleep duration and multimorbidity during the COVID-19 pandemic, finding that compared to 7–8 h of sleep per day, a sleep duration of ≤ 5 h increased the likelihood of multimorbidity by 145% (95% CI: 1.90–3.14), and a sleep duration of ≥ 9 h increased the likelihood of multimorbidity by 49% (95% CI: 1.14–1.95) [9].

In this context, sleep duration, as an important health indicator, has garnered widespread attention for its relationship with multimorbidity. Consistent evidence suggests that sleep duration is associated with chronic diseases such as cardiovascular disease (CVD) and cancer [12–13], as well as mortality [14]. Compared to individuals who sleep less than 7–9 h per day, those who regularly sleep 7 to 8 h are more likely to live 1 to 3 years longer without chronic diseases [15].

These data reveal that both insufficient and excessive sleep are associated with an increased risk of multimorbidity. A meta-analysis showed that individuals who sleep less than 7 h per day have a higher risk of all-cause mortality, and compared to adequate sleep duration, increasing or decreasing sleep by 1 h increases the risk of cardiovascular disease [16]. Additionally, a longitudinal study demonstrated that short sleep duration increases the risk of chronic diseases such as stroke and cancer [17]. These findings provide biological plausibility for the relationship between sleep duration and multimorbidity.

While many studies have established this relationship in various populations, there is limited research focusing on the elderly in China. Through a review of previous literature, we found that after the outbreak of the COVID-19 pandemic, studies on sleep and multimorbidity among the elderly in China are scarce, and the data for these studies were collected before the COVID-19 pandemic. Additionally, these studies focus on specific types of chronic diseases, and there are no relevant reports on the overall relationship between multimorbidity and nighttime sleep or naptime. Most of the reference studies are concentrated in Western countries. Through this study, we aim to provide insights specific to this population, considering the differences in Chinese culture, lifestyle, and healthcare system, which may influence the results.

Therefore, this study aims to explore the relationship between sleep duration and multimorbidity among elderly Chinese in depth within different cultural contexts. We analyzed the latest CHARLS data obtained during the COVID-19 pandemic. We chose this dataset because it best reflects the characteristics of multimorbidity among the elderly in China at this stage. Through this study, we hope to clarify the independent impact of sleep duration on the risk of multimorbidity and provide a theoretical basis for future intervention studies.

Methods

Study population

The data used in this study comes from the 2020 CHARLS database. CHARLS employs a scientific sampling strategy, first implicitly stratifying regions in China according to certain socioeconomic characteristics, and then using probability proportional to size (PPS) sampling within each stratum. This process involves multiple stages, with each stage considering the representativeness of different levels and regions, ensuring that the selected sample comprehensively and accurately reflects the overall situation of the middle-aged and elderly population in China [18]. This sampling method guarantees broad coverage and representativeness of the sample, making the survey results more generalizable and valuable for reference.

The CHARLS questionnaire design covers multiple aspects, including demographic characteristics, psychological health status, and physical health status. It collects data on participants’ age, gender, educational background, and other demographic information, as well as their psychological and physical health status. These modules together constitute a comprehensive dataset, providing a solid data foundation for researchers to explore the relationship between naptime duration, nighttime sleep duration, and multimorbidity among the elderly in China.

The ethical approval for the 2020 CHARLS survey was granted by the Biomedical Ethics Committee of Peking University, with the approval number IRB00001052-11015. During the field survey, each consenting respondent was required to sign two copies of the informed consent form, one of which was retained by the respondent and the other stored in the CHARLS office.

The inclusion criteria for this study specified elderly individuals aged 60 and above; completion of the sleep duration and health status questionnaire; and provision of informed consent. At the initial stage of the study, a total of 7,880 elderly individuals aged 60 and above joined the study cohort. In the subsequent data processing, we excluded cases with missing data on demographic characteristics or multimorbidity status, as well as those with severe cognitive impairment or other conditions that might affect the accuracy of self-reported data. After applying these strict inclusion and exclusion criteria, we ultimately removed 2,118 participants from the study. Following this screening process, we obtained a final effective sample of 5,762 participants for further analysis of the relationship between sleep duration and multimorbidity.

Main variables

Multimorbidity

Participants self-reported 14 chronic diseases diagnosed by a doctor, including hypertension, dyslipidemia (elevation of low-density lipoprotein, triglycerides (TGs), and total cholesterol, or a low high-density lipoprotein level), diabetes or high blood sugar, cancer or malignant tumor (excluding minor skin cancers), chronic lung diseases such as chronic bronchitis and emphysema (excluding tumors or cancer), liver disease (except fatty liver, tumors, and cancer), heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems, stroke, kidney disease (except for tumor or cancer), stomach or other digestive diseases (except for tumor or cancer), emotional, nervous, or psychiatric problems, memory-related diseases, arthritis or rheumatism, and asthma. Multimorbidity was defined as the presence of two or more of the above 14 chronic diseases in an individual [19–20].

Sleep duration

Nighttime sleep duration was assessed using the following question: “How many hours do you usually sleep each night over the past month?” In a meta-analysis of 35 sleep studies, participants were categorized into three groups based on sleep duration: short sleep (< 6 h), moderate sleep (6–8 h), and long sleep (> 8 h) [21]. Naptime duration was assessed using the following question: “How long do you usually nap during the day over the past month?” Participants were divided into four groups: no nap (0 min), short nap (< 30 min), moderate nap (30–90 min), and long nap (> 90 min). The selection of these cut-off points was based on previous epidemiological literature on daytime napping [22].

Covariates

Sociodemographic and lifestyle information was collected through questionnaires, including age (60–69 years, 70–79 years, 80 years and above), gender (male, female), region (urban, rural), marital status (married, divorced, widowed, unmarried), living alone (yes, no), education level (illiterate, elementary school, junior high school and above), self-rated health (very bad, bad, fair, good, very good), social activities (yes, no), smoking (yes, no), alcohol consumption (yes, no), frequency of physical exercise (0 times a week, 1–4 times a week, more than 4 times a week), social medical insurance (yes, no), pension insurance (yes, no), depression (yes, no), and occupation (retired, working after retirement, employed, unemployed).

Statistical analysis

The normal distribution of continuous variables was assessed using the Kolmogorov-Smirnov test. Data that followed a normal distribution were expressed as mean ± standard deviation (x ± s), and comparisons between two groups were performed using the t-test, while comparisons among multiple groups were conducted using one-way analysis of variance (ANOVA). For non-normally distributed data, the median (interquartile range, Q1, Q3) was used to describe the data, and differences between groups were tested using the Mann-Whitney U test. Categorical variables were expressed as frequency and percentage (n/%), and comparisons between groups were made using the chi-square test or Fisher’s exact test. Multicollinearity was diagnosed using the variance inflation factor (VIF), and the linear relationship between continuous independent variables and the dependent variable was assessed using the Box-Tidwell test. Binary logistic regression models were constructed to analyze the relationship between sleep duration and multimorbidity among the elderly, controlling for potential confounders, and restricted cubic splines were used to explore the dose-response relationship. Additionally, subgroup analyses were conducted by introducing interaction terms into the model to examine the differences in the impact of nighttime sleep duration on multimorbidity among male and female elderly individuals and different age groups. All statistical analyses were performed using R4.2 software, with a two-tailed P-value of less than 0.05 considered statistically significant.

Results

Participant characteristics

The effective sample consisted of 5,761 elderly individuals, of whom 2,572 were male, accounting for 44.65%. The average age of the elderly was (68.27 ± 6.19) years, and 4,315 cases (74.9%) had multimorbidity. Table 1 shows the characteristics of the subjects. Among the nighttime sleep groups, the proportion of elderly individuals with multimorbidity was lowest in the group with 6–8 h of nighttime sleep compared to other groups. In the naptime sleep groups, elderly individuals without a napping habit had a relatively lower proportion of multimorbidity.

Table 1 Basic characteristics of study participants(n = 5761)
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Logistic regression of the relationship between sleep duration and Multimorbidity in older adults

Multicollinearity diagnostics showed that all VIF values in our data were below 10, indicating no multicollinearity issues. The Box-Tidwell test confirmed a linear relationship between continuous independent variables (age, nighttime sleep, naptime duration) and the dependent variable (multimorbidity) (P > 0.05). Model 1: This model includes only the variables of nighttime sleep duration and naptime duration to analyze their basic relationship with multimorbidity. Model 2: This model controls for demographic variables such as age, gender, and region, in addition to nighttime sleep duration and naptime duration, to exclude the potential confounding effects of these demographic factors. Model 3: This model controls for all covariates, including socioeconomic factors and lifestyle factors, providing a comprehensive analysis of the relationship between sleep duration and multimorbidity. Logistic regression analysis, controlling for all covariates in Model 3, indicated that 6–8 h of nighttime sleep is a protective factor against multimorbidity. Compared to elderly individuals with 6–8 h of nighttime sleep, those with less than 6 h or more than 8 h of nighttime sleep had an increased likelihood of multimorbidity. Additionally, compared to elderly individuals without a napping habit, napping increased the likelihood of multimorbidity (Table 2).

Table 2 Logistic regression table of the relationship between sleep duration and Multimorbidity in the elderly
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Dose–response relationship between sleep duration and Multimorbidity in older adults

The dose-response relationship between nighttime sleep duration and multimorbidity among the elderly showed a U-shaped curve (P overall < 0.001; nonlinearity P < 0.001). The likelihood of multimorbidity decreased from 6 h of sleep to approximately 7 h. Additionally, the likelihood of multimorbidity increased after exceeding 7 h of sleep (Fig. 1a). Regarding naptime duration, no nonlinear relationship was observed between naptime duration and multimorbidity among the elderly (P overall = 0.098; nonlinearity P = 0.209) (Fig. 1b). The probability of multimorbidity increased with longer naptime duration.

Fig. 1
figure 1

Dose-response relationship between sleep duration and the likelihood of multimorbidity among the elderly. The x-axis represents sleep duration, and the y-axis represents the OR values calculated by the model. The shaded area indicates the 95% confidence interval. In (a), within the range of less than 7 h of sleep, the OR gradually decreases with increasing nighttime sleep. Beyond 7 h, the OR gradually increases with increasing sleep duration. In (b), the OR gradually increases with increasing naptime duration. The red line represents the fitted logistic regression model, and the red shaded area represents the 95% confidence interval of the fitted curve

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Subgroup analysis of age- and gender-specific factors affecting the impact of nighttime sleep duration on Multimorbidity among the elderly

After adjusting for all covariates, this study identified age- and gender-specific factors affecting the impact of nighttime sleep duration on multimorbidity among the elderly. The analysis was performed using three models: Model 1 included basic demographic variables such as age, gender, region, marital status, and whether the participant was living alone; Model 2 added lifestyle variables to Model 1, including education level, self-rated health, social activities, smoking, alcohol consumption, and frequency of physical exercise; Model 3 further added socioeconomic factors and other lifestyle factors to Model 2, such as social medical insurance, pension insurance, depression, and occupation.Within the 6–8 h nighttime sleep duration, there were no significant interactions between age, gender, and multimorbidity among the elderly (P for interaction > 0.05). This indicates that the impact of 6–8 h of nighttime sleep on multimorbidity is consistent across both male and female elderly individuals, as well as across different age groups. Table 3 provides a detailed subgroup analysis, presenting the odds ratios (OR) and confidence intervals (CI) for the impact of nighttime sleep duration on multimorbidity, adjusted for the variables included in Models 1–3.

Table 3 Subgroup analysis of Age- and Gender-Specific factors affecting the impact of nighttime sleep duration on Multimorbidity among the elderly
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Discussion

This study found that elderly individuals with 6–8 h of nighttime sleep had a significantly lower likelihood of multimorbidity compared to those with less than 6 h or more than 8 h of sleep. Additionally, increased naptime duration was associated with a higher likelihood of multimorbidity. These findings suggest that moderate nighttime sleep duration has an important protective effect on the health of the elderly, while both excessively short and long sleep durations may increase the likelihood of multimorbidity. Similarly, increased naptime duration may be a risk factor. These results provide scientific evidence for elderly individuals to reasonably arrange their sleep duration, helping to prevent multimorbidity and improve their quality of life.

Previous studies have found that moderate nighttime sleep duration is associated with a lower risk of chronic diseases [23]. One study found that compared to participants with 6–8 h of nighttime sleep, those with ≤ 5 h and 5–6 h of sleep had a 33.3% (95% CI: 14.8-54.7%) and 24.2% (95% CI: 5.9-45.6%) increased risk of multimorbidity, respectively, with no significant association between long sleep duration and the incidence of multimorbidity [24]. Another study found that compared to participants with 7–8 h of nighttime sleep, those with < 5 h of sleep had a higher risk of hypertension (OR = 2.52, 95% CI: 2.17–2.93), and this association remained significant even after adjusting for age, gender, and BMI (OR = 1.38, 95% CI: 1.16–1.64) [25]. Another study showed that middle-aged and elderly individuals with < 6 h of sleep had a 1.16 times higher likelihood of having multiple diseases compared to those with 6–8 h of nighttime sleep [26]. A cross-sectional study of 4,115 Chinese individuals aged 60 to 79 years found that only long sleep duration was associated with multimorbidity [27]. A large cross-sectional analysis in Canada also found that both short and long sleep durations were associated with the risk of multimorbidity [26]. Two systematic reviews reported that short sleep duration is associated with mortality, diabetes, hypertension, cardiovascular disease, coronary heart disease, and obesity, while long sleep duration is associated with mortality, diabetes, cardiovascular disease, coronary heart disease, and obesity [28–29].

This study clarified that the dose-response relationship between nighttime sleep duration and multimorbidity follows a U-shaped curve, which is consistent with some previous research findings [30,31,32,33]. Previous studies exploring the relationship between daily sleep duration and cardiometabolic multimorbidity (CMM) among the elderly also found a U-shaped association, with lower risks of cardiovascular and metabolic diseases when elderly individuals slept 9 and 10 h per day [4]. In this study, the risk of multimorbidity significantly increased after exceeding 7 h of nighttime sleep, which differs from previous recommendations on sleep duration. This discrepancy may be due to different definitions of daily sleep duration, as previous studies included both naptime and nighttime sleep duration [4].

Our study also suggests that increased naptime duration may be a factor that increases the likelihood of multimorbidity. This is consistent with some previous research findings [34–35]. One study exploring the relationship between daytime napping trajectories and the incidence of multimorbidity found no association between the two [36]. However, inconsistent results have also been reported. Some studies have found a significant association between short nighttime sleep duration and increased risk of multimorbidity, even after accounting for daytime napping duration, indicating that this association is independent of daytime napping [24]. Additionally, other studies have found that in the elderly, napping for 0–30 min is associated with lower risks of heart disease, hypertension, and kidney disease, suggesting a protective effect of napping on the incidence of new kidney disease in the elderly [37]. Therefore, regarding the relationship between daytime napping and the risk of new chronic diseases, some studies suggest that appropriate napping may increase or decrease the risk [38–39], while other studies show no significant association between the two [40].

This study found that within the 6–8 h nighttime sleep duration, there were no significant interactions between age, gender, and multimorbidity among the elderly (P for interaction > 0.05). This is consistent with previous findings. Previous research has shown that among female participants aged 45 and above, despite experiencing hormonal and metabolic changes due to menopause, these changes did not result in significant gender differences in the risk of multimorbidity [41]. Additionally, previous studies did not find a significant association between age and sleep quality. Although aging may lead to the deterioration of circadian rhythms, affecting sleep and health, and making the elderly more susceptible to adverse health outcomes due to poor sleep duration and quality, no significant age-related differences were observed [42].

Moderate sleep exerts protective effects on health through various mechanisms.Firstly, moderate sleep helps maintain the normal function of the immune system. Insufficient sleep can impair immune function, leading to increased inflammatory responses. Chronic sleep deprivation may result in a state of low-grade inflammation [26]. The immune system is a crucial defense mechanism that protects the body from pathogens and initiates inflammatory responses during injury or infection. The inflammatory system may play a role in various diseases. Previous studies have shown that short sleep duration is associated with elevated levels of inflammatory markers such as C-reactive protein and interleukin-6 [43]. Inflammation is the immune system’s response to infection, tissue damage, or other stimuli. During inflammation, the immune system releases a series of chemicals, including cytokines and acute-phase proteins, which promote the inflammatory and repair processes. C-reactive protein and interleukin-6 are such inflammatory markers. This may increase the risk of several chronic diseases, including cardiovascular events, type 2 diabetes, hypertension, and depression [44].

Secondly, moderate sleep helps maintain the balance of the endocrine system. The endocrine system is one of the body’s important regulatory systems, secreting hormones to regulate various physiological processes, including growth, metabolism, mood behavior, reproduction, and stress response. For example, short sleep duration may affect insulin sensitivity. In an experimental study, healthy men were asked to restrict their sleep to 4–5 h per night for a week, resulting in reduced glucose tolerance and insulin sensitivity [45]. Individuals with insufficient sleep may also experience circadian rhythm disturbances and autonomic nervous system changes [31]. The human biological clock (circadian rhythm) affects hormone secretion. Cortisol levels typically peak in the morning and decrease in the evening, helping us prepare for activity and rest. Insufficient or poor-quality sleep can disrupt this natural rhythm, leading to abnormal hormone secretion [46]. Additionally, sleep deprivation is associated with changes in circulating catecholamine levels and alterations in neurovegetative responses.

Moderate sleep helps maintain mental health. Studies have shown that both insufficient and excessive sleep can lead to psychological issues such as depression and anxiety, thereby increasing the risk of multimorbidity. Some research has demonstrated a bidirectional relationship between sleep duration and depression, where insufficient sleep may increase the risk of depression [47–48]. In patients with depression, endothelial dysfunction and increased platelet aggregation can accelerate the development of cardiovascular diseases [49]. Insufficient sleep can lead to decreased levels of neurotransmitters in the brain, such as serotonin and dopamine, thereby increasing the risk of depression and anxiety.

Lastly, moderate sleep helps maintain cognitive function. Studies have found that both insufficient and excessive sleep can lead to cognitive decline, thereby increasing the risk of Alzheimer’s disease and other cognitive impairments. Insufficient sleep can lead to the accumulation of β-amyloid protein in the brain, increasing the risk of Alzheimer’s disease [50]. Excessive sleep duration is a risk factor for certain types of cognitive impairment. Evidence suggests that long sleep duration may accelerate the rate of frontal and temporal lobe gray matter atrophy in the elderly, potentially impairing memory [51]. Long sleep duration may also reflect circadian rhythm disruptions associated with sleep disorders and cognitive impairment [31]. Irregular circadian rhythms are associated with short-term cognitive impairment and long-term brain atrophy. Additionally, moderate sleep helps maintain brain plasticity, promoting memory consolidation and learning ability.

Limitations

Our study primarily investigated the general relationship between nighttime sleep duration and multimorbidity among the elderly. However, there are certain limitations in exploring the relationship between specific disease states or clusters within multimorbidity and sleep duration. Multimorbidity involves complex etiological relationships and unclear definitions of disease types, making it challenging to pinpoint index diseases. We plan to discuss these specific disease states or clusters in detail based on comorbidity patterns in future research. Further research on the relationship between sleep and these specific clusters, delving into the different responses of specific disease types within multimorbidity to sleep duration, could help uncover more nuanced health management strategies.

At the same time, there are some areas that need improvement in this study.Firstly, the data relies on self-reports, which may introduce bias. Elderly individuals might overestimate or underestimate their sleep duration, affecting the accuracy of the study results. Using self-reported measures for chronic diseases may underestimate the prevalence of chronic conditions, especially among the elderly and those with lower socioeconomic and educational backgrounds.

Secondly, this study employs a cross-sectional design, which cannot establish causality. Although we found associations between nighttime sleep duration, naptime duration, and multimorbidity, we cannot determine the causal relationship. Additionally, due to the availability of questionnaire data, potential influencing factors were overlooked. In the future, with the release of new post-COVID-19 data, we can construct a new longitudinal data model. Longitudinal studies can determine the long-term impact of sleep duration on multimorbidity by tracking the sleep duration and health status of the elderly over time.

Furthermore, future research should explore the impact of sleep quality on multimorbidity. Although this study primarily focuses on sleep duration, sleep quality is also an important factor affecting health. Future studies should assess the sleep quality of the elderly using various methods (e.g., polysomnography, questionnaires) and investigate the relationship between sleep quality and multimorbidity. Additionally, the CHARLS questionnaire does not include all typical chronic diseases found in clinical database studies. Further research is needed to study the impact of infectious diseases (e.g., tuberculosis, HIV, COVID-19) on multimorbidity.

Lastly, future research should explore the impact of sleep interventions on multimorbidity. Although this study primarily focuses on sleep duration and naptime duration, sleep interventions (e.g., cognitive behavioral therapy, pharmacotherapy) may also affect multimorbidity. Future studies should evaluate the effectiveness of different sleep interventions through randomized controlled trials to provide scientific sleep management plans for the elderly.

Conclusion

This study thoroughly explored the relationship between sleep duration and multimorbidity among the elderly and revealed the dose-response relationship through restricted cubic spline analysis. The results indicated that elderly individuals with 7 h of nighttime sleep had the lowest likelihood of multimorbidity, while both shorter and longer sleep durations increased the likelihood of multimorbidity. This finding provides empirical evidence for the optimal range of nighttime sleep duration for the elderly, suggesting that 7 h should be the ideal target for nighttime sleep. Additionally, the study found a positive correlation between naptime duration and the likelihood of multimorbidity, suggesting that reducing naptime duration may help lower the likelihood of multimorbidity. Furthermore, the study found no significant differences in the impact of nighttime sleep duration on multimorbidity across different ages and genders. These findings provide scientific evidence for sleep health management among the elderly, aiding in the development of targeted interventions to improve the quality of life for the elderly.

Data availability

Data is publicly available. See: https://charls.charlsdata.com/pages/Data/2020-charls-wave5/zh-cn.html. If you can’t open the URL, Please contact the corresponding author for data requests.

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Acknowledgements

The authors would like to thank the National School of Development at Peking University for providing the CHARLS data.

Funding

This project is supported by the Foundation project(Supported by research project of Shanghai University of Sport(2023STD015), Ministry of Education Project of Humanities and Social Sciences for young scholars (22YJC890027).

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Authors and Affiliations

  1. College of Sports, Nanjing Tech University, Nanjing, China

    Yanliqing Song & Lin Chen

  2. School of Athletic Performance, Shanghai University of Sport, Shanghai, China

    Yue Liu

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Contributions

Yanliqing Song conceived the study, participated in its design and coordination, and critically revised the manuscript. Yanliqing Song had full access to all the data collection, analysis, and interpretation, and drafted the manuscript. Lin Chen contributed to the process of data collection and data analyses as study investigators. All authors approved the final manuscript. Yue Liu are the guarantors. All authors had full access to all the data in the study, and the corresponding authors had final responsibility for the decision to submit for publication. The corresponding author (Yue Liu)) attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

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Correspondence to Yue Liu.

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Ethics approval and consent to participate

All methods concerning human participants in our study were conducted in accordance with the ethical standards laid out in the 1964 Declaration of Helsinki and its subsequent amendments. The ethical approval for the 2020 CHARLS survey was granted by the Biomedical Ethics Committee of Peking University under approval number IRB00001052-11015. During the field survey, each consenting respondent was required to sign two informed consent forms, with one copy retained by the respondent and the other deposited in the CHARLS office.

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Not applicable.

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The authors declare no competing interests.

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Song, Y., Chen, L. & Liu, Y. Association between nap time, nighttime sleep, and multimorbidity in Chinese older adults: a cross-sectional study. BMC Geriatr 25, 151 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-025-05807-x

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Keywords

BMC Geriatrics

ISSN: 1471-2318

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