Edited by: Sanford Auerbach, Boston University, United States
Reviewed by: Zenobia Zaiwalla, Oxford University Hospitals NHS Trust, United Kingdom
Enrique Urrea-Mendoza, Florida State University, United States
Peter Hurwitz, Clarity Science LLC, United States
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Poor sleep quality negatively impact health, reducing quality of life and increasing disease risk. For the elderly, poor sleep quality lead to fatigue and reduced mobility, increasing the risk of falls. In Vietnam, no studies have explored the relationship between sleep quality and fall risk in the elderly. This study aimed to determine the correlation between sleep quality and fall risk among the elderly, providing knowledge for fall prevention in this population in Vietnam.
A cross-sectional study was conducted on 404 elderly patients who visited and were treated as outpatients at Thai Binh University Hospital from October 2023 to June 2024. Direct interviews were conducted using the Fall Risk Questionnaire (FRQ) from STEADI-CDC-2017 (USA), and the Pittsburgh Sleep Quality Index (PSQI) with a cut-off score of 7 to assess sleep quality. The FRQ tool used a cut-off score of 4 to evaluate fall risk.
The percentage of elderly at risk of falls was 19.6%. The average PSQI score was 11.0 ± 2.7, with 358 (88.6%) elderly patients showing poor sleep quality. Logistic regression analysis showed that higher PSQI scores in the elderly significantly correlated with an increased risk of falls (OR = 1.16, 95% CI: 1.02–1.32,
Poor sleep quality are closely related to fall risk among the elderly, alongside other factors such as religion, education, comorbidities, and participation in recreational activities.
Falls are the leading cause of injury-related death and rank as the seventh leading cause of death among the elderly (Elderly) (Burns and Kakara,
The risk of falls among the elderly has been shown to be associated with various factors, including both subjective and objective factors. Moreover, recent reports have demonstrated a correlation between fall risk and sleep quality in the elderly (Kuo et al.,
A sleep quality assessment tool that has recently been widely and effectively applied is the Pittsburgh Sleep Quality Index (PSQI). The PSQI is a questionnaire consisting of 18 items that assess sleep quality based on seven different aspects (Buysse et al.,
The study was conducted through a cross-sectional survey of elderly individuals (aged ≥60 years) living in Thai Binh province. The elderly were selected for the study if they met the following criteria: aged ≥60 years, visited and received outpatient treatment at the Department of Examination, Thai Binh University Hospital from October 2023 to June 2024; had permanent residency and had been living in the study area for at least 12 months; and voluntarily agreed to participate in the study. The study did not include elderly individuals with impaired consciousness or coma, those with previously diagnosed and currently treated psychotic disorders, those with hearing or visual impairments, physical deformities, or those who did not reside regularly in the study area.
We applied the formula for estimating a proportion to determine the sample size for the study:
In which,
In the current study, we used a convenience sampling method to select 404 elderly patients who met the inclusion criteria for participation in the study.
The questionnaire was designed based on predefined variables. A pilot survey was conducted with 20 elderly individuals at Thai Binh University Hospital to evaluate the content and presentation of the questionnaire. We conducted direct interviews with research participants using the pre-prepared questionnaire. The interviewers were experienced in community surveys and were fully trained on the tools and methods of data collection.
The Fall Risk Questionnaire (FRQ) from the STEADI-CDC-2017 (USA), was used to assess fall risk among the elderly (Centers for Disease Control Prevention,
The sleep quality of the elderly was assessed using the Pittsburgh Sleep Quality Index (PSQI) questionnaire, which consists of 18 questions covering seven aspects: subjective sleep quality, sleep latency, habitual sleep efficiency, sleep disturbances, use of sleeping medications, and daytime dysfunction. The elderly were considered to have poor sleep quality if their total PSQI score was >7, and good sleep quality if the total PSQI score was 7 or less (Buysse et al.,
The collected data were entered twice using EpiData 3.0 software. Data cleaning: after data entry was completed, the data were cleaned by comparing the two entries and correcting any errors during data entry. The data were presented as counts and percentages (%) for categorical variables and as means and standard deviations for continuous variables. Factors related to fall risk and the correlation between fall risk and sleep quality were determined using logistic regression models.
Variables were screened by examining the unadjusted relationship between each risk factor and the outcome using logistic regression. We assessed the relationship between the tertiles and quartiles of PSQI scores and fall risk in the elderly using logistic regression analysis. The first tertile and quartile were used as references to estimate odds ratios (OR) and 95% confidence intervals (CI). In the first model, we adjusted for age and gender. In the second model, we additionally adjusted for any falls in the previous year. In the third model, we further adjusted for education level, smoking history, alcohol consumption history, participation in leisure activities, and comorbidities.
All analyses were conducted using SPSS 22.0 software to correctly account for complex survey sampling structures, including stratification, clustering, and unequal weighting. The relationship between dependent variables and fall risk in the final model was reported as adjusted odds ratios with 95% confidence intervals (95% CI) and P-values.
The study was approved by the Ethics Committee of Thai Binh University of Medicine and Pharmacy under Decision No. 0224/IRB dated July 22, 2024. The research participants were informed about the purpose and content of the study before answering the questions and were entirely free to refuse to participate if they chose. Participation in the study was entirely voluntary, and all information about the research subjects was kept confidential. All information from the research participants was encoded and secured. The data and information collected in the reports were committed to being used solely for research purposes and not for any other purposes. The research results and proposed recommendations will be used to improve health and healthcare services for patients visiting and receiving treatment at Thai Binh University Hospital.
The distribution of general characteristics of the study subjects according to fall risk shows that female elderly accounted for 61.1%, as shown in
Characteristics of the study subjects according to fall risk
| Male | 157 (38.9) | 132 (40.6) | 25 (31.6) | 0.14 |
| Female | 247 (61.1) | 193 (59.4) | 54 (68.4) | |
| 60–70 | 236 (58.4) | 200 (61.5) | 36 (45.6) | |
| 70–80 | 132 (32.7) | 101 (31.1) | 31 (39.2) | |
| ≥80 | 36 (8.9) | 24 (7.4) | 12 (15.2) | |
| No | 377 (93.3) | 312 (96.0) | 65 (82.3) | |
| Yes | 27 (6.7) | 13 (4.0) | 14 (17.7) | |
| Normal weight | 246 (60.9) | 198 (60.9) | 48 (60.8) | 0.88 |
| Overweight | 103 (25.5) | 84 (25.8) | 19 (24.1) | |
| Obesity | 55 (13.6) | 43 (13.2) | 12 (15.2) | |
| Primary school and below | 54 (13.4) | 39 (12.0) | 15 (19.0) | |
| Junior school | 194 (48.0) | 166 (51.1) | 28 (35.4) | |
| High school | 104 (25.7) | 75 (23.1) | 29 (36.7) | |
| College and above | 52 (12.9) | 45 (13.8) | 7 (8.9) | |
| No | 353 (87.4) | 287 (88.3) | 66 (83.5) | 0.25 |
| Yes | 51 (12.6) | 38 (11.7) | 13 (16.5) | |
| No | 318 (78.7) | 259 (79.7) | 59 (74.7) | 0.33 |
| Yes | 86 (21.3) | 66 (20.3) | 20 (25.3) | |
| No | 338 (83.7) | 310 (95.4) | 28 (35.4) | |
| Yes | 66 (16.3) | 15 (4.6) | 51 (64.6) | |
| No | 201 (49.8) | 178 (54.8) | 23 (29.1) | |
| Yes | 203 (50.2) | 147 (45.2) | 56 (70.9) | |
| No | 172 (42.6) | 140 (43.1) | 32 (40.5) | 0.68 |
| Yes | 232 (57.4) | 185 (56.9) | 47 (59.5) | |
| No | 54 (13.4) | 39 (12.0) | 15 (19.0) | 0.10 |
| Yes | 350 (86.6) | 286 (88.0) | 64 (81.0) | |
| No | 17 (4.2) | 9 (2.8) | 8 (10.1) | |
| Yes | 387 (95.8) | 316 (97.2) | 71 (89.9) | |
| No | 129 (31.9) | 102 (31.4) | 27 (34.2) | 0.63 |
| Yes | 275 (68.1) | 223 (68.6) | 52 (65.8) | |
| Normal |
46 (11.4) | 39 (12.0) | 7 (8.9) | 0.43 |
| Poor |
358 (88.6) | 286 (88.0) | 72 (91.1) | |
Data are presented as number (percent).
Chi-square test.
Normal sleep quality indicates PSQI ≤ 7.
Poor sleep quality indicates PSQI >7.
BMI, Body Mass Index.
Bold values represent statistically significant differences between comparison groups (
The results of the multivariate regression model presented in
Multiple logistic regression analysis of factors related to fall risk.
| No | Ref | ||||
| Yes | 1.28 | 0.65 | 3.94 | 0.04 | |
| College and above | Ref | ||||
| Junior school | 1.27 | 0.85 | 2.23 | 0.14 | 3.55 (0.67, 18.69) |
| High school | 1.10 | 0.74 | 2.22 | 0.14 | 3.00 (0.71, 12.78) |
| Primary school and below | 1.94 | 0.76 | 6.48 | 0.01 | |
| No | Ref | ||||
| Yes | 2.14 | 0.24 | 79.34 | < 0.001 | |
| No | Ref | ||||
| Yes | 1.55 | 0.42 | 13.46 | < 0.001 | |
| No | Ref | ||||
| Yes | −1.99 | 0.70 | 8.09 | 0.004 | |
| PSQI score | 0.15 | 0.07 | 4.75 | 0.03 | |
| Constant | −5.13 | 1.59 | 10.38 | 0.001 | |
SE, standard error; OR, odds ratio; CI, confidence interval; PSQI, Pittsburgh Sleep Quality Index. Bold values represent statistically significant differences between comparison groups (
In our primary analysis, poorer sleep quality (increased PSQI scores) was significantly associated with a higher risk of falls across all four models, as shown in
Logistic regression analysis of PSQI Score and risk of fall risk.
| Continuous variable |
11.76 ± 3.33 | ||||
| PSQI = 0–10 ( |
32 (19.6) | 1 (reference) | 1 (reference) | 1 (reference) | 1 (reference) |
| PSQI = 10–12 ( |
16 (10.7) | 0.72 (0.31, 1.66) | 0.65 (0.26, 1.64) | ||
| PSQI = 12–21 ( |
31 (33.7) | 1.71 (0.93, 3.12) | 2.17 (1.00, 4.82) | 2.23 (0.93, 5.37) | |
| PSQI = 0–9 ( |
20 (18.9) | 1 (reference) | 1 (reference) | 1 (reference) | 1 (reference) |
| PSQI = 9–11 ( |
19 (14.2) | 0.71 (0.36, 1.41) | 0.70 (0.35, 1.40) | 0.91 (0.37, 2.23) | 0.79 (0.29, 2.16) |
| PSQI = 11–12 ( |
9 (12.5) | 0.61 (0.26, 1.44) | 0.57 (0.24, 1.35) | 1.00 (0.33, 2.98) | 0.93 (0.28, 3.13) |
| PSQI = 12–21 ( |
31 (33.7) | 1.86 (0.95, 3.64) | 2.43 (1.00, 5.93) | 2.53 (0.93, 6.88) | |
OR, odds ratio; CI, confidence interval; PSQI, Pittsburgh Sleep Quality Index.
Model 1 adjusted for age and gender.
Model 2 adjusted for age, gender, and any falls in the previous year.
Model 3 adjusted for age, gender, any falls in the previous year, education level, smoking history, drinking history, participation in leisure activity, and comorbidity.
Mean ± standard deviation (SD).
Bold values represent statistically significant differences between comparison groups (
Our study was conducted to determine the correlation between fall risk and sleep quality among 404 elderly outpatients at Thai Binh University Hospital. The results showed that 79 elderly individuals were at risk of falls (accounting for 19.5%), while 325 elderly individuals were not at risk of falls. The differences in age, religion, education level, regular participation in recreational activities, and previous fall history between the two groups of elderly individuals with and without fall risk were statistically significant (
The results of the multivariate regression model presented show that elderly individuals who were religious, had an education level of elementary school or below, had a history of falls, had comorbidities, regularly participated in recreational activities, and had an average sleep quality score according to the PSQI were at higher risk of falls. Low education level has been identified as a risk factor for poor sleep quality in previous studies (Wu et al.,
Our study found that older adults who belong to a religion have a higher risk of falls than those who do not follow any religion. This finding is in contrast to a recent systematic review, which suggested that religious participation can have a positive impact on physical health (Kruk and Aboul-Enein,
Multimorbidity has also been shown to be closely associated with poor sleep quality (Fu et al.,
This study adds further evidence to the relationship between sleep quality and fall risk through a well-designed survey process on a large sample. Sleep variables, including sleep duration and sleep disorders, have been encouraged to be considered in studies related to sleep quality because these variables can affect study outcomes. Therefore, a notable strength of the current study is the simultaneous consideration of the relationship between sleep duration and sleep quality with fall risk in the elderly.
Our study has some limitations. The use of a cross-sectional design does not allow for causal inferences about the relationship between sleep quality and fall risk in the participants. Moreover, due to the time-varying nature of both sleep quality and fall risk variables, the study design used does not allow for determining which factor occurs first. Additionally, some factors related to injuries and mental disorders, which have been reported to be associated with falls, were not accounted for in the current study because no such data were collected. The information collected from the participants was based on self-report, so this study cannot exclude the possibility of recall bias. Another limitation is that the study was conducted at only one provincial hospital in a northern province of Vietnam, so the findings may not be representative of the broader Vietnamese population. Therefore, further cross-sectional and longitudinal studies in multiple centers are needed to provide comprehensive evidence on the factors affecting fall risk among Vietnamese elderly.
The results of the current study show a strong and significant relationship between sleep quality and fall risk among the elderly in a province in Northern Vietnam. Our research findings provide positive contributions to the health of the elderly community by suggesting that improving sleep quality may reduce falls and fall-related injuries among the elderly. Future prospective longitudinal studies are needed to investigate the causal relationship between sleep duration, sleep quality, and fall risk in the elderly.
The datasets underlying the results of this study are available from the corresponding author upon reasonable request.
The studies involving humans were approved by the study was approved by the Ethics Committee of Thai Binh University of Medicine and Pharmacy under Decision No. 0224/IRB dated July 22, 2024. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
NT: Writing – original draft, Writing – review & editing. DA: Conceptualization, Writing – original draft. TV: Conceptualization, Data curation, Methodology, Writing – original draft, Writing – review & editing. HA: Formal analysis, Software, Writing – review & editing. DH: Formal analysis, Software, Writing – review & editing.
The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
The authors thank the study participants and our colleagues for completing the survey for this study.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.