Correlation analysis between sleep quality and depressive symptoms among rural elderly in China: An observational study

Abstract

BACKGROUND

The rural elderly in China have a high prevalence of depressive symptoms, which is closely linked to poor sleep quality. This not only poses significant threats to their physical and mental health but also lacks in-depth exploration of associations specific to different sleep dimensions. We hypothesize that specific sleep dimensions are independently and significantly associated with depressive symptoms in this population.

AIM

To explore the links between different sleep dimensions and depressive symptoms among rural elderly in China.

METHODS

This cross-sectional study enrolled 5136 older adults (≥ 60 years) recruited between April and June 2024. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index, and depressive symptoms were assessed with the Patient Health Questionnaire-9. Binary logistic regression analysis was employed to examine the associations between problems in different sleep dimensions and depressive symptoms among these older adults.

RESULTS

The prevalence of depressive symptoms was 19.5%, and the overall rate of sleep disorders was 40.13%. Among the rural elderly, six sleep dimensions were found to be statistically significantly associated with depressive symptoms (all P < 0.05), with the following odds ratios (ORs) and 95% confidence intervals (CIs): Subjective sleep quality (OR = 2.066, 95%CI: 1.709-2.497), sleep onset latency (OR = 2.476, 95%CI: 2.062-2.972), sleep efficiency (OR = 1.686, 95%CI: 1.369-2.076), sleep disturbances (OR = 2.092, 95%CI: 1.566-2.795), daytime dysfunction (OR = 3.378, 95%CI: 2.882-3.959), and use of hypnotic medications (OR = 1.662, 95%CI: 1.093-2.525).

CONCLUSION

Poor subjective sleep quality, prolonged sleep onset latency, reduced sleep efficiency, sleep disturbances, daytime dysfunction, and use of hypnotic medications are associated with depressive symptoms in the elderly. Therefore, healthcare professionals should target elderly individuals with sleep disorders and implement effective interventions to alleviate their depressive symptoms.

Key Words: Elderly; Depressive symptoms; Sleep quality; Rural areas; Patient Health Questionnaire-9; Sleep efficiency

Core Tip: This cross-sectional study included 5136 rural elderly (≥ 60 years old) in China, using the Pittsburgh Sleep Quality Index and Patient Health Questionnaire-9 to assess sleep quality and depressive symptoms. It found 19.5% depressive symptoms prevalence and 40.13% sleep disorder rate; six sleep dimensions were significantly associated with depressive symptoms, providing a basis for targeted interventions for rural elderly.

INTRODUCTION

Over the past few decades, population aging has emerged as a prominent global challenge, with the aging trend in China being particularly pronounced[1]. Furthermore, it is important to note that substantial disparities exist in the aging context between urban and rural regions of China. The outmigration of young labor from rural areas has resulted in a higher concentration of the elderly population in rural settings[2]. However, due to factors such as inadequate infrastructure and a shortage of professional healthcare personnel, rural elderly individuals face barriers to accessing sufficient care and health resources[3].

Aging has given rise to numerous challenges that impact the physical and mental health of the elderly[4]. Among them, depression is particularly worthy of attention. Depression, a common mental health disorder[5], can severely affect the elderly in multiple aspects, including physical health[6-8], emotional state[9], social functioning[10], and quality of life, with specific manifestations such as a decline in immunity, sleep disorders, cognitive impairment, social withdrawal, and a decrease in life satisfaction. Additionally, age-related declines in physical function, such as mobility limitations and chronic conditions[11], can cause the elderly to lose independence and self-esteem, which further exacerbates depressive symptoms. Moreover, psychological impacts associated with aging, such as awareness of impending mortality and death-related anxiety[12], may also contribute to the development of depression. Notably, depression among rural elderly individuals is not driven by a single factor but rather by multi-level influences within the framework of social ecological theory[13]. This multi-level interaction not only links sleep problems closely to survival anxiety and healthcare-related concerns but also strengthens the mediating pathway of “sleep disorders, negative cognition, depression”[14]. Meanwhile, the weakening of support systems in rural areas, for instance, the erosion of traditional family support due to young labor outmigration and insufficient community care resources, results in a lack of external buffers for sleep problems, further amplifying the risk of depression among rural elderly individuals.

Sleep quality represents another critical aspect significantly impacted by aging[15]. The Pittsburgh Sleep Quality Index (PSQI) is widely employed to assess multiple dimensions of sleep, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction. Within the elderly population, impairments in these sleep dimensions are highly prevalent. For instance, they may experience difficulties in falling asleep (prolonged sleep latency), frequent awakenings during the night (sleep disturbances), a shortened total sleep time, and a decreased sleep efficiency. Such sleep problems not only contribute to daytime fatigue and decline in cognitive function but also exert a detrimental effect on overall quality of life[16].

The relationship between depression and sleep quality among the elderly population has become a widely researched topic. Prior studies have consistently highlighted a complex bidirectional association between these two conditions[17,18]. On one hand, depression can induce sleep disturbances[19]; the psychological distress and persistent negative thought patterns inherent to depression often disrupt the normal sleep-wake cycle, leading to difficulties in falling asleep, maintaining sleep, or achieving restorative sleep. On the other hand, poor sleep quality may, in turn, trigger the onset or exacerbation of depressive symptoms[20], creating a potentially self-perpetuating cycle. However, the specific associations between distinct dimensions of sleep (e.g., subjective vs objective sleep parameters) and depressive symptoms remain incompletely elucidated, a critical theoretical gap that the present study aims to address. From a mechanistic standpoint, subjective sleep quality is closely linked to the “interpersonal-psychological” level of the social ecological theory. For rural elderly individuals, the loss of traditional support systems (e.g., family care, community networks) and economic instability frequently elicit negative cognitions, such as survival anxiety[21,22]; these adverse cognitive processes, in turn, tend to degrade subjective sleep quality (e.g., increased perceptions of sleep inadequacy or dissatisfaction). In contrast, objective sleep dimensions, including sleep efficiency (the ratio of total sleep time to time in bed) and sleep latency (the time taken to fall asleep), may be directly associated with impairments in “physiological-emotional” regulation within neurobiological mechanisms. A notable example is the dysregulation of the hypothalamic-pituitary-adrenal axis, which disrupts circadian rhythms and thereby perturbs objective sleep parameters[23]. Against the backdrop of scarce medical resources in rural areas, where access to interventions for neurobiological dysregulation (e.g., pharmacotherapy or specialized sleep treatments) is limited, this neurobiologically driven sleep disturbance may exert a more pronounced driving effect on the development and progression of depressive symptoms in the rural elderly population. This study aims to comprehensively investigate the relationships between the seven dimensions of the sleep and depressive symptoms among the elderly population in rural China. The research findings are expected to provide practical suggestions for healthcare providers and policymakers.

MATERIALS AND METHODS

Data and sample

This cross-sectional research was carried out in Shandong province from April to June 2024, targeting the rural elderly in Xintai city. Specifically, 33 administrative villages were selected from rural areas of Xintai city, with temporary survey sites set up at the health centers of each selected village. The survey was conducted in conjunction with basic-level health physical examinations to improve participation and reduce “healthy volunteer bias”. The inclusion criteria were as follows: Age ≥ 60 years old, clear consciousness and distinct language expression, and long-term residence in rural areas. The exclusion criteria included those diagnosed with severe diseases, those suffering from diseases affecting cognitive function, and those unable to cooperate with the investigation. A total of 5389 cases were actually surveyed. After excluding the questionnaires with missing important variables, a total of 5136 valid questionnaires were obtained. Notably, the sample showed no statistical differences in indicators such as age, gender, educational level, and main health status compared with the 2023 baseline data of the rural elderly population in Xintai city, indicating good representativeness.

Study variables

In this study, general information, sleep status and depressive symptoms of older adults were collected using a face-to-face questionnaire. Master’s degree students served as investigators who were uniformly trained before the survey to ensure a consistent understanding of the questionnaire content and scoring methodology and to reduce errors caused by subjective judgment of the investigators. In coordination with the staff of the village committee, the elderly were concentrated in a quiet room, and the investigator and the elderly were face-to-face to distribute, fill out and recover the questionnaires. Elderly people with reading and comprehension difficulties were assisted by the investigator. During the process, the quality of the survey was strictly controlled, and ambiguous answers needed to be reconfirmed with the elderly. After the questionnaire was completed, two investigators checked and entered the data at the same time, and outliers were eliminated when the data were analyzed.

The General Information Questionnaire was developed by the research team itself and included general information and health status of the elderly, covering gender, age, marital status, residence, literacy, monthly income, medical payment method, smoking status, and alcohol consumption. The PSQI[24] was adopted to measure sleep quality. The scale consists of a total of 24 items, among which 19 self-assessment questions are utilized for scoring. PSQI is divided into 7 component scores, namely sleep latency, sleep duration, sleep disturbances, subjective sleep quality, use of sleeping medications, sleep efficiency, and daytime dysfunction. Each component is equally weighted on a 0-3 scale, with a resultant global score ranging from 0 to 21. For individual components, sleep problems are considered to exist when the score of each component is ≥ 2 points, this criterion is based on the classic scoring rules of the PSQI[24] and validated studies on elderly populations at home and abroad, which confirm that it has good discriminative ability among the elderly[25,26]. A higher score indicates worse sleep quality. Participants were determined to have a poor sleep quality status when the total score exceeded 7.

The Patient Health Questionnaire-9 (PHQ-9) (Kroenke et al[27], 2001) is an effective tool for identifying the severity of depressive symptoms, and it was adopted in this study to assess depressive symptoms in the elderly. This scale consists of 9 items, with each item scored from 0 (not at all) to 3 (nearly every day), and the total score ranges from 0 to 27.A higher score indicates a more severe degree of depressive symptoms. In this study, a total score of ≥ 5 points was taken as an indication of the presence of depressive symptoms. This cutoff was determined based on the characteristics of depression in the rural elderly population in China and the study objectives, as it enables sensitive detection of early mild symptoms and is consistent with similar domestic studies[28,29]. This study demonstrated that the PHQ-9 had a Cronbach’s alpha value of 0.801, indicating good internal reliability.

Statistical analysis

Data analysis was carried out using SPSS 26.0 software. Continuous variables were expressed as mean ± SD, and count data were presented as raw n (%). Comparisons of categorical variables between groups were performed using the χ² test. Multivariate binary logistic regression was used to analyze the association between the dimensions of sleep quality and depressive symptoms. The significance level was set at a P value of less than 0.05.

RESULTS

General information

A total of 5136 rural elderly participants were included in this study, with their ages ranging from 60 years to 94 years old and an average age of 70.71 ± 6.72 years. Among them, 1867 were male and 3269 were female. According to the evaluation by the PSQI, 2061 elderly participants were identified as having poor sleep quality, accounting for 40.1% of the total. Elderly females, those of advanced age, in non-marital status, living alone, with an education level of primary school or below, having a low monthly income, relying on self-funded medical care, non-smokers, non-drinkers, and those with poor sleep quality had a higher proportion of depressive symptoms (all P values < 0.05). Other detailed information is presented in Table 1.

Table 1 Comparison of general characteristics among the elderly based on depressive symptoms, n (%).

Characteristics	Surveyed people, n = 5136	People with depressive symptoms, n = 1000	χ2	P value
Gender			59.751	< 0.001
Female	3269 (63.6)	742 (22.7)
Male	1867 (36.4)	258 (13.8)
Age (years old)			45.368	< 0.001
60-69	2339 (45.5)	361 (15.4)
70-79	2229 (43.4)	502 (22.5)
≥ 80	568 (11.1)	137 (24.1)
Marital status			61.458	< 0.001
Married	3926 (76.4)	670 (17.1)
Divorced/widowed/unmarried	1210 (23.6)	330 (27.3)
Living situation			55.179	< 0.001
Living alone	1115 (21.7)	304 (27.3)
Living with others	4021 (78.3)	696 (17.3)
Educational level			53.507	< 0.001
Primary school and below	4008 (78.0)	864 (21.6)
Junior high school	750 (14.6)	101 (13.5)
High school and above	378 (7.4)	35 (9.3)
Monthly income (yuan)			60.512	< 0.001
< 1000	3909 (76.1)	855 (21.9)
1000-3499	799 (15.6)	98 (12.3)
≥ 3500	428 (8.3)	47 (11.0)
Medical payment method			57.943	< 0.001
Self-payment	273 (5.3)	95 (34.8)
Employee medical insurance	724 (14.1)	97 (13.4)
Resident medical insurance	4139 (80.6)	808 (19.5)
Smoking status			9.120	0.003
Smoking	678 (13.2)	103 (15.2)
Non-smoking	4458 (86.8)	897 (20.1)
Drinking status			41.440	< 0.001
Drinking	1198 (23.3)	156 (13.0)
Non-drinking	3938 (76.7)	844 (21.4)
Sleep quality			661.372	< 0.001
Poor	2061 (40.1)	759 (36.8)
Good	3075 (59.9)	241 (7.8)

Sleep quality scoring in each dimension

The average score of sleep quality was 6.70 ± 4.37. There are significant differences in the proportions of subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, daytime dysfunction, and use of sleeping medications between the group with depressive symptoms and the group without depressive symptoms among rural elderly (all P < 0.05; Table 2).

Table 2 Comparison of sleep status in the elderly according to depressive symptoms, n (%).

Items	Number of cases	Depressive group	Non-depressive group	χ2	P value
Overall sleep disorder (score)				661.372	< 0.001
≤ 7	3075 (59.87)	241 (7.8)	2834 (92.2)
> 7	2061 (40.13)	759 (36.8)	1302 (63.2)
Subjective sleep quality (score)				598.994	< 0.001
< 2	4125 (80.3)	527 (12.8)	3598 (87.2)
≥ 2	1011 (19.7)	473 (46.8)	538 (53.2)
Sleep onset time (score)				500.220	< 0.001
< 2	3113 (60.6)	296 (9.5)	2817 (90.5)
≥ 2	2023 (39.4)	704 (34.8)	1319 (65.2)
Sleep duration (score)				181.489	< 0.001
< 2	2056 (40.0)	213 (10.4)	1843 (89.6)
≥ 2	3080 (60.0)	787 (25.6)	2293 (74.4)
Sleep efficiency (score)				296.058	< 0.001
< 2	2790 (54.3)	300 (10.8)	2490 (89.2)
≥ 2	2346 (45.7)	700 (29.8)	1646 (70.2)
Sleep disturbance (score)				208.417	< 0.001
< 2	4880 (95.0)	861 (17.6)	4019 (82.4)
≥ 2	256 (5.0)	139 (54.3)	117 (45.7)
Daytime dysfunction (score)				507.038	< 0.001
< 2	3468 (67.5)	376 (10.8)	3092 (89.2)
≥ 2	1668 (32.5)	624 (37.4)	1044 (62.6)
Hypnotic drug use (score)				75.671	< 0.001
< 2	5015 (97.6)	939 (18.7)	4076 (81.3)
≥ 2	121 (2.4)	61 (50.4)	60 (49.6)

The correlation between sleep quality and depressive symptoms

Logistic regression showed that there was a significant association between the total sleep score and depressive symptoms (odds ratio = 1.311, P < 0.001). The higher the sleep quality score, the higher the probability of depression occurrence, indicating that the total sleep score is an important factor linked to depression. Subsequently, to exclude the interference of overall sleep level and accurately identify the independent predictive link of each PSQI component on depression (avoiding overestimation or underestimation of dimension-specific effects), the total sleep score was included as a correction variable in the regression model analyzing the association between individual PSQI components and depression. Subjective sleep quality, sleep onset latency, sleep efficiency, sleep disturbance, daytime dysfunction, and use of hypnotic medications in rural elderly had a statistically significant association with depressive symptoms (P < 0.05). The results regarding the association between sleep duration and depressive symptoms indicated no statistically significant difference (P > 0.05). The collinearity diagnosis of the model confirmed that the condition indices were all < 5, indicating good independence of each PSQI component after adjusting for the total sleep score and feasibility of the modeling approach (Table 3).

Table 3 Binary logistic regression analysis of different sleep dimensions and depression status (adjusted for total sleep score).

Variables	B	Standard error	Wald	P value	OR (95%CI)
Subjective sleep quality	0.726	0.097	56.337	< 0.001	2.066 (1.709-2.497)
Sleep onset time	0.907	0.093	94.592	< 0.001	2.476 (2.062-2.972)
Sleep duration	-0.001	0.115	< 0.001	0.993	0.999 (0.797-1.253)
Sleep efficiency	0.522	0.106	24.219	< 0.001	1.686 (1.369-2.076)
Sleep disturbance	0.738	0.148	24.982	< 0.001	2.092 (1.566-2.795)
Daytime dysfunction	1.217	0.081	225.585	< 0.001	3.378 (2.882-3.959)
Hypnotic drug use	0.508	0.214	5.649	0.017	1.662 (1.093-2.525)

OR: Odds ratio; CI: Confidence interval.

DISCUSSION

This study investigated the association between depressive symptoms and sleep quality among rural elderly in Shandong province, China. The current study ascertained that the prevalence of depressive symptoms among elderly people in rural areas of Shandong province, China, was 19.5%. Depressive symptoms were identified using the PHQ-9 with a cutoff score of ≥ 5, a threshold that not only effectively detects early mild depressive symptoms in older adults but also aligns with the core objective of this study (focusing on capturing early signals of depression risk in the rural elderly) and has been widely adopted in multiple clinical and epidemiological studies.

The results of this study are similar to the 19.2% prevalence of depressive symptoms observed among the elderly population in Sichuan province[30]. Notably, the aging rate in rural areas of China is generally higher than that in urban areas[31,32]. Moreover, the access to medical resources in rural regions is relatively scarce[33], and the society pays less attention to the mental health of the elderly[34]. There are differences between urban and rural areas in terms of depressive symptoms among the elderly in China. The proportion of rural elderly with depressive symptoms (15.70%) is higher than that of urban elderly (12.25%)[35]. Although various scales have been employed in the research process to screen for depressive symptoms, the existing research findings have unambiguously unveiled a reality that cannot be underestimated: The issue of depressive symptoms among the rural elderly in China has reached a critical level that demands immediate and high-level attention from all parties[36]. Consequently, concerted efforts are urgently needed to develop and implement targeted, evidence-based intervention measures in a timely manner to alleviate this growing public health burden.

In this study, the proportion of elderly people with sleep disorders was 40.13%. Some prior studies[37,38] have demonstrated that the prevalence of sleep disorders among rural elderly ranges from 35% to 60.3%. Given the relatively high prevalence of sleep disorders in the elderly population observed here and in existing literature, this issue warrants substantial attention in public health practice. The analysis of each dimension of sleep quality shows that elderly individuals with poor subjective sleep quality, prolonged sleep latency, decreased sleep efficiency, sleep fragmentation, daytime dysfunction, and those using hypnotic medications have a high proportion of depression. Further, the results showed that the sleep quality of the elderly was associated with the probability of developing depressive symptoms, and findings regarding the correlation between overall sleep quality and depressive symptoms are consistent with those of previous studies[29,39,40].

Currently, the specific mechanisms underlying the relationship between sleep quality and depressive symptoms remain unclear. Given the close connection between sleep quality and depressive symptoms, current research is also exploring potential intervention targets and therapeutic substances. Among them, research related to biotin and 5-hydroxytryptamine (5-HT) provides new perspectives for our understanding of this relationship, and this is particularly relevant to the rural elderly population in our study, who exhibit distinct characteristics of low leisure activity, monotonous diets, and adherence to nature-aligned daily routines. Some studies have indicated that the circadian rhythm system governing sleep is highly correlated with stress-sensitive neurotransmitter systems, such as the 5-HT system[41]. Specifically, 5-HT is a crucial mediator linking circadian rhythm dysregulation to emotional disturbances, which implies a strong association between sleep quality and depressive mood. For the rural elderly in our study, who typically follow nature-aligned routines (e.g., early bedtimes and wake-up times tied to daylight hours), disruptions in sleep onset (e.g., the prolonged sleep latency observed in our results) may directly destabilize their inherent circadian rhythm. This disruption not only impairs 5-HT synthesis (as 5-HT production is closely linked to light exposure) but also exacerbates emotional dysregulation, thereby strengthening the association between poor sleep and depressive symptoms. Notably, their low level of leisure activity may further reduce opportunities for light exposure and social interaction. These two factors are critical for circadian alignment and 5-HT homeostasis, and their reduction can indirectly exacerbate 5-HT deficiency and circadian misalignment. Existing evidence indicates that compounds targeting 5-HT can exert rapid antidepressant effects[42]; furthermore, a study focusing on elderly populations further confirms that enhancing 5-HT activity can alleviate depressive symptoms induced by circadian misalignment and low social engagement (a common consequence of low leisure activity)[43,44].

Animal experiments have demonstrated that biotin exhibits significant therapeutic potential. It can effectively alleviate the adverse effects associated with depression and has a positive effect on relieving depressive symptoms[45]. For the rural elderly in our study, however, biotin deficiency may be a non-negligible contributing factor: Their monotonous diets may lead to insufficient biotin intake, which in turn impairs neurotransmitter metabolism (including 5-HT) and neural function[46]. This deficiency not only worsens sleep quality but also amplifies depressive vulnerability. Therefore, it can be speculated that the deficiency of neurotransmitters, biotin and other substances may affect the association between sleep quality and depressive symptoms. Future research should be centered on delving into the precise pathways by which these substances interact among themselves and with the sleep-depression regulatory network, aiming to furnish more targeted therapeutic strategies for patients concurrently afflicted with sleep disorders and depressive symptoms.

The results of this study analyzing the association between sleep disorders and depressive symptoms are generally consistent with existing research findings[47-50]. However, the association between sleep duration and depressive symptoms is not significant. In this study, sleep duration was categorized into four levels based on responses to item 4 of the PSQI, specifically: > 7 hours (scored 0), 6-7 hours (scored 1), 5-6 hours (scored 2), and < 5 hours (scored 3). Emerging evidence has documented a U-shaped association between nocturnal sleep duration and the risk of depression in elderly populations, individuals with a nocturnal sleep duration of 6-8 hours typically exhibit the lowest likelihood of developing depression[51]. Additionally, results from a longitudinal study indicated that each one-hour increase in nocturnal sleep duration is negatively associated with depressive symptoms among the elderly[52]. Possible reasons for this analysis are as follows: Firstly, the sleep survey in this study was conducted in the form of questionnaires, which might be related to the recall bias of the elderly. Secondly, this study only calculated the nighttime sleep duration and did not take into account the nap time, which might have a certain impact. The research findings indicate that among middle-aged and elderly populations in China, taking a midday nap is associated with a lower likelihood of depressive symptoms[53]. For instance, an older adult with 5.5 hours of nighttime sleep (PSQI: 2 points for sleep duration) and 1 hour of midday napping may reach a total sleep time of 6.5 hours, aligning with the PSQI’s 1-point nighttime sleep threshold. However, since nap duration was not incorporated into the assessment, this compensatory effect of napping remained unaccounted for, which undermined the ability to effectively capture the association between overall sleep health and depression. It can be interpreted that sleep quality is more critical to depressive symptoms in older adults than sleep duration alone. Even if the number of hours of sleep at night is up to standard (e.g., 6-8 hours), older adults may still experience depressive symptoms if problems such as poor sleep quality (e.g., frequent nocturnal awakenings, reduced proportion of slow-wave sleep) and sleep disorders are present. The core of this phenomenon is closely associated with age-related degenerative changes in sleep structure: With advancing age, older adults exhibit a significant decrease in the proportion of slow-wave sleep (deep sleep), increased sleep fragmentation, and advanced sleep phase[54,55]. These physiological alterations result in a critical discrepancy, older adults may subjectively perceive their sleep duration as sufficient, while their objective sleep quality undergoes a substantial decline, failing to meet the restorative needs of both the body and mind. At the same time, there are individual differences in the amount of sleep older adults need, with some older adults needing shorter, higher-quality sleep that does not affect mood. In addition, a varied lifestyle, such as light physical work and social activities, can compensate for sleep deprivation.

Subjective sleep quality is an individual’s overall perception of his or her sleep condition. In this study, poor subjective sleep quality showed a link to depressive symptoms in older adults. Analyzed from a psychological perspective, older adults who subjectively perceive poor sleep are highly susceptible to negative emotions such as anxiety and depression[56]. This is due to the fact that sleep, as a key factor in maintaining physical and mental health, significantly interferes with the elderly’s assessment of their own physical condition when subjective sleep quality is poor, causing them to worry excessively about their health status[57]. This psychological burden not only further disrupts the emotional state, but also greatly increases the likelihood of depression[58]. Therefore, in recent years, many studies have been conducted to explore effective ways to improve subjective sleep quality in older adults. Among them, some studies have confirmed that virtual reality relaxation experiences[59] and structured mindfulness group therapy programme[60] can have a positive association with the sleep and mood states of older adults.

Long latency to sleep onset is associated with depressive symptoms. Difficulty in falling asleep can disrupt the normal circadian rhythm of the human body. As a key endogenous mechanism regulating physiological activities, circadian rhythm disruption exhibits a significant association with endocrine system dysfunction, which is manifested by altered secretion timing and levels of melatonin[61]. Melatonin not only regulates sleep, but also participates in mood regulation, and its abnormal secretion is prone to triggering symptoms of depression. At the same time, difficulty in falling asleep makes the brain continuously excited, depleting neurotransmitters, interfering with normal brain function and increasing the likelihood of depression. Based on this, the following two ways can be used to help the elderly ease the difficulty in falling asleep and the accompanying symptoms of depression. On the one hand, with the help of biofeedback equipment to monitor the relaxation of the elderly brain in real time, according to the results of the precise regulation, to assist the elderly to enter a state of relaxation, which can effectively shorten the time to fall asleep[62]. On the other hand, sound therapy can help seniors with their difficulty falling asleep by playing bedtime stories. It includes a variety of auditory stimuli. These include colored noises such as white noise and pink noise, autonomic sensory meridian response sounds such as nature sounds (rain, crackling firewood), whispers and object friction, and classical music or the type of music preferred by the elderly[63,64]. All of these can be incorporated into the audio content of a bedtime story to help seniors relax and improve their sleep.

Decreased sleep efficiency means a decreased ratio of actual sleep time to time spent in bed. This study found a link to depressive symptoms. Inefficient sleep prevents the body from resting and recovering, leading to decreased immune function and increased inflammation, and chronic inflammation can trigger depression by affecting neurotransmitter metabolism and neuroplasticity. At the same time, sleep inefficiency also impairs cognitive functioning of the brain[65], leading to difficulties in socializing and daily activities, and exacerbating depressive symptoms due to self-denial[66]. Individualized training programs incorporating cognitive-behavioral therapy can be developed to improve sleep efficiency and alleviate related depressive symptoms[67]. In rural areas, low-cost sleep aids can be vigorously promoted, taking into account the economic situation. For example, simple sleep monitoring bracelets can be introduced to help the elderly understand their own sleep conditions[68]. In addition, the elderly are actively encouraged to participate in physical exercises such as Tai Chi and Baduanjin to improve their sleep quality from a multi-dimensional perspective[69].

Sleep disorders, which encompass frequent nighttime awakenings, excessive dreaming, and other related issues, are closely associated with depressive symptoms[70]. Such disorders disrupt the brain’s normal sleep cycle, impair neuroprotective mechanisms, and interrupt deep sleep, collectively compromising the brain’s emotional regulation function. In the long term, these disruptions can contribute to the development of depressive symptoms[71]. In rural areas of China, in order to deal with sleep disorders in the elderly, we can cooperate with relevant enterprises and public welfare organizations to seek subsidies or donations for brain wave stimulation sleep aid equipment; at the same time, we can carry out sleep disorders mutual aid groups in villages, using simple art forms such as ballad singing and color pencil scribbling to treat the disorders[72]; and inviting medical experts to carry out sleep disorders lectures in the spare time of farms.

Daytime dysfunction is characterized by daytime fatigue, sleepiness, and poor concentration[73]. This study shows its association with depressive symptoms. Daytime dysfunction seriously impairs older adults’ ability to perform activities of daily living and social participation[74]. When older adults are unable to carry out normal daily activities due to poor daytime mental functioning, they often experience intense feelings of helplessness and worthlessness. Furthermore, fatigue and reduced concentration make it challenging for them to communicate and interact effectively with others in social settings, leading to a gradual narrowing of their social circles. This state of social isolation, in turn, further exacerbates feelings of loneliness and depressive symptoms among older adults. To address these issues, older adults can be encouraged to participate in low-intensity activities, such as walking and handicraft-making, which may help them overcome difficulties in social interaction caused by fatigue and inattention, thereby alleviating their depressive symptoms[75].

The use of hypnotic medications has been associated with depressive symptoms. While hypnotics can help older adults initiate sleep, they inherently carry certain side effects, including next-day feelings of depression and psychomotor slowing. Furthermore, long-term hypnotic use may lead to drug dependence; when these medications become ineffective or are discontinued, older adults often face more severe sleep disturbances and psychological distress, which further exacerbate depressive symptoms[76]. Therefore, it is essential to establish medical records for older adults using hypnotic medications, with detailed documentation of medication use, sleep patterns, and mood fluctuations. Additionally, doctors should conduct regular assessments of these elderly individuals: Based on their sleep quality and psychological status, medication dosages can be adjusted, or psychological interventions can be implemented[61]. This approach helps older adults develop a proper understanding of their sleep disorders and the effects of hypnotic medications, thereby alleviating psychological stress related to medication use and mitigating the impact of drug side effects on their mood.

This study has several limitations that should be acknowledged. First, in this investigation, both sleep quality and depressive symptoms among rural older adults were assessed using questionnaire scales, which may introduce certain information bias. Second, covariates such as gender, age, and marital status were not included in the analysis. Previous studies have confirmed that these demographic factors are associated with both sleep health and depression in older adults, which may confound the observed association between sleep indicators and depressive symptoms. Third, the specific types and severity of chronic diseases as well as comorbidities in rural older adults were not considered; neglecting these factors may further obscure the sleep-depression relationship. Fourth, this study employed a cross-sectional design, so it is unable to verify the causal relationship between sleep quality and depressive symptoms. Additionally, the study sample has inherent limitations: It was only derived from rural areas of Shandong province, rendering it difficult to generalize to rural older adults across China. Therefore, in future research, longitudinal follow-up studies and qualitative interviews should be incorporated to conduct an in-depth analysis of the relationship between depressive symptoms and sleep quality in older adults, and to explore more rigorous scientific research methodologies.

CONCLUSION

This study reveals that poor subjective sleep quality, prolonged sleep onset latency, reduced sleep efficiency, sleep disturbances, daytime dysfunction, and hypnotic medication use are correlated with depressive symptoms among rural older adults in Shandong province, China. Specifically, sleep disorders are closely associated with the occurrence of depressive symptoms in this elderly population. In future, primary healthcare providers should pay early attention to older adults with sleep disorders, strengthen mental health management for this group, and provide guidance to improve their sleep status. Additionally, the government should implement regular screenings for depressive symptoms among rural older adults, with the goal of enabling early detection and delivering individualized intervention measures, ultimately reducing the impact of depressive symptoms on their quality of life and overall health.