This scale was proposed in 2008 by geriatric experts of the International Association of Nutrition and Aging (IANA) based on the frailty phenotype and frailty index (11). The scale consists of the following five items: Here are the refined sentences to make the language more natural and academic: Fatigue: Have you experienced a feeling of fatigue during the majority of the past 4 weeks or throughout the entire four-week period? Increased resistance or decreased endurance: Do you encounter difficulties in ascending a single flight of stairs without pausing for a break midway or relying on the aid of walking assistive devices? Decline in Mobility: Do you find it challenging to walk a distance of 100 meters unassisted by any walking aids? Disease Condition: Are you currently suffering from five or more different diseases? Weight Loss: Has your body weight diminished by 5% or a greater percentage over the course of the past year? For each of the above items, answering “yes” is scored as 1 point, and answering “no” is scored as 0 point. The total score is 5 points. A score of 3 points or higher indicates frailty, a score of 1 to 2 points indicates pre-frailty, and a score of 0 point indicates no frailty. The overall Cronbach’s α coefficient of the scale is 0.826, indicating good reliability and validity (12).

In the present study, the Mini Nutritional Assessment-Short Form (MNA-SF) was employed as a screening tool for nutritional risk in older adults. As an internationally recognized, concise, and validated questionnaire, the MNA-SF is designed to rapidly identify the risk of malnutrition or malnutritional status in older adult individuals (13). It comprises 6 items, including weight loss in the past 3 months, body mass index (BMI; or calf circumference as an alternative), mobility, recent acute illness/psychological stress, neuropsychological issues (dementia/depression), and eating disorders. Scores range from 0 to 14, with results classified into three categories: 12–14 (good nutritional status), 8–11 (at risk of malnutrition), and 0–7 (malnourished). The MNA-SF is easy to administer, taking approximately 3–5 min, and is applicable to diverse settings such as communities, hospitals, and older adult care facilities (14).

The Pittsburgh Sleep Quality Index (PSQI), devised by Buysse, a psychiatrist from Pittsburgh, the U. S. (15)^, was employed to evaluate participants’ sleep quality over the past month. It is suitable for assessing the sleep quality of both patients with sleep and mental disorders and the general public. The PSQI consists of seven key components (16): subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, sleeping pill usage, and daytime functioning impact. Each component is scored on a 0–3 scale, with the total score ranging from 0 to 21. A lower total score indicates better sleep quality. The scale has a Cronbach’s α coefficient of 0.84, demonstrating good reliability and validity. In this study, In this study, the total sleep quality score ranged from 0 to 21, with >5 points indicating poor sleep quality.

Gender, age, education, residence type, living mode, monthly per-capita family income, alcohol and smoking statuses, annual-physical-exam participation, social-activity participation, exercise habits, social support, nutritional status, and sleep quality were chosen as control variables. Specific assignments are presented in Supplementary Table 1.

Logistic regression model results indicated that, after accounting for demographic and confounding variables, various nutritional statuses of older adults (taking good nutritional status as the reference) exhibited a positive correlation with sleep quality (OR = 1.076–1.193). Conversely, different degrees of frailty in older adults (using no frailty as the reference) were positively associated with sleep quality (OR = 3.472–6.050), as shown in Table 2.

Logistic regression analysis of older adults’ sleep quality: Taking poor sleep quality as the dependent variable and the variables with statistical significance in the univariate analysis as independent variables (assignments shown in Supplementary Table 1), the Logistic regression analysis was conducted. The results indicated that gender, age, educational level, type of residence, living pattern, average monthly per capita family income, alcohol consumption, smoking status, participation in social activities, annual physical examination, exercise, social support, nutritional status, and degree of frailty were all was significantly associated with, and the differences were statistically significant (p < 0.05), as shown in Table 3.

The incidence of poor sleep quality among older adult women is 1.463 times that of older adults men, suggesting that older adult women are more susceptible to such issues. This aligns roughly with Li, X et al.’s (22) findings, which indicated that the risk of sleep disorders in older adult women is 1.45 to 1.60 times higher than in men. The decline in estrogen and progesterone levels as older adult women age may cause more frequent nighttime awakenings and difficulty falling asleep. Post-menopausal women, in particular, often experience symptoms like hot flashes and sweating, which can disrupt sleep quality (23). Additionally, older age is associated with poorer sleep quality, as older adults’ sleep structure changes with age, typically showing less deep sleep and more light sleep. These changes can lead to more nighttime awakenings and thus affect overall sleep quality (24). Educational attainment also influences older adults’ sleep quality. The incidence of poor sleep quality among older adults with a junior high school education or higher is 0.745 times that of those with less education. This is consistent with Xue et al. (25) research. Older adult individuals with higher education may have shorter sleep durations, as they might be troubled by excessive thinking, lingering occupational stress, social role changes after retirement, and increased cognitive activities, all of which can impact their sleep. However, some studies (26) suggest that the highly educated older adults generally have better sleep quality, likely because they are more aware of the importance of healthy sleep and take preventive measures. Thus, higher education may enhance cognitive abilities and health awareness, potentially improving sleep, but excessive thinking can also cause stress and anxiety, degrading sleep quality. Studies (27) have shown that rural areas usually have a quieter natural environment, which may contribute to better sleep quality. Noise pollution is one of the most important factors affecting sleep quality, and rural areas usually have lower noise levels, which may provide better sleeping conditions for residents. older adults living alone may feel lonely due to the lack of family company. Loneliness not only harms mental health but also physical health, especially sleep quality, as it can trigger anxiety and depression, major contributors to sleep disorders (28). For those in nursing homes, research findings on sleep quality remain contentious environmental noise, some results are subject to dispute, light, and other residents’ activities can disrupt their sleep (29). Economic status is another factor. The risk of poor sleep quality among older adults with a monthly per capita family income below 2000 yuan is 1.266 times that of those with 2000 yuan or more. older adults in better economic situations are less likely to have declining sleep quality, in line with previous research (30). High-income groups enjoy better living conditions, including access to better healthcare, psychological support, and a comfortable environment, which promote better sleep. In contrast, the economically disadvantaged older adults may face more stress and health issues, leading to poorer sleep quality (31).

In terms of lifestyle, alcohol intake and smoking can improve sleep structure (32, 33). The reason for this is that some older people may have negative emotions such as anxiety and depression. A small amount of alcohol intake and smoking can improve their psychological state and give them a short period of psychological relaxation, helping them to fall asleep. However, smoking and drinking alcohol to help sleep is not recommended. Because aging reduces alcohol metabolism in older adults, and alcohol may worsen health problems and disrupt sleep (34). Smoking also harms their sleep quality (35), increasing insomnia and nighttime awakenings. Physical exams can detect chronic diseases like hypertension and diabetes in older adults, which affect sleep. Appropriate exercise can regulate the sleep–wake cycle, increase deep sleep time and reduce falling asleep time, enhancing sleep (36). Social activities offer emotional support, reduce anxiety, boost a sense of belonging and lower depression risk, all of which benefit sleep. Social support is vital for older adults’ mental health (37). older adults feeling cared for have more stable emotions, leading to better sleep quality (38).

The generalized linear model reveals that the degree of frailty (B = 1.145) has a far stronger independent effect on sleep quality than nutritional status (B = 0.007). Although the independent role of nutritional status may be overshadowed by frailty, their interaction term is significant, suggesting malnutrition can impact sleep by worsening frailty. This aligns with prior research. Ni et al. (51) noted that malnutrition speeds up frailty through reduced muscle protein synthesis, weakened immunity, and chronic inflammation induction. In a frail state, energy metabolism disorders and decreased mobility further inhibit sleep-regulating hormone secretion, creating a “malnutrition → frailty → sleep disorders” vicious cycle. Xu et al. (52) also found that the risk of sleep quality decline in older adults with both malnutrition and frailty is 2.1 times higher than those with a single risk factor, highlighting the need for prioritized intervention for this group. To address this, personalized diet plans should be tailored to older adults’ specific needs to ensure adequate protein and energy intake. High-protein diets can improve muscle quality and slow frailty progression, alleviating poor sleep (53). Multidisciplinary teamwork is advisable. Dietitians, doctors, and nurses should form a team to jointly create and execute comprehensive management plans for sleep issues related to older adults’ nutrition and frailty (54). For instance, chronic diseases like diabetes and hypertension, which are common among older adults and can affect nutrition, need active management to avoid negative impacts on nutrient intake (55). Family members should be encouraged to participate in older adults’ diet and exercise plans, offering emotional support and supervision. Regular physical activities such as walking, swimming, yoga, and strength training can boost appetite, enhance muscle strength, and lower frailty risk (56). In daily life, promoting older adults’ participation in interest groups and volunteer activities can enhance their enthusiasm and life participation, improving overall health.

Nevertheless, this study has limitations. Though it reveals the synergistic effects of malnutrition and frailty on sleep quality in older adults, both conditions may be driven by other underlying health problems. For example, uncontrolled chronic diseases (e.g., heart failure, chronic kidney disease, advanced tumors) or acute conditions (e.g., infections, postoperative recovery) can directly cause anorexia, metabolic disorders, and muscle loss, exacerbating malnutrition and frailty. These comorbidities may confound the “nutrition-frailty-sleep” chain. Future studies need to systematically collect acute and chronic disease histories, control for such confounders via stratified analyses or multivariate modeling to validate current findings’ generalizability. Secondly, the nutritional status and degree of frailty of older adults changes over time, so the mechanisms and factors influencing the study are complex, and future research could combine cross-sectional and longitudinal studies to fill the gaps in the field.