Prevalence and Correlates of Depressive Symptoms and Cognitive Impairment in Elderly People over 65 Years Old in the Community and Nursing Homes

Abstract

Objective:

Cognitive impairment and depression significantly reduce quality of life in the aging population. This study aimed to investigate the prevalence of depressive symptoms and cognitive impairment and explore its relationship in the elderly.

Methods:

A total of 1645 elderly people in nursing homes and 4703 elderly people in the community were enrolled in the survey. The Patient Health Questionnaire-9 and Ascertain Dementia-8 were employed to evaluate depressive symptoms and cognitive impairment.

Results:

The overall prevalence of cognitive impairment was 12.5% in the community-dwelling group and 52.2% in the nursing home group. The prevalence of cognitive impairment in nursing homes was significantly higher than that in community-dwelling groups for the same age group (p < 0.001). The overall prevalence of depressive symptoms was 3.9% in the community-dwelling group and 2.0% in the nursing home group. The prevalence of depressive symptoms increased with age in the community-dwelling group (p < 0.001). The binary logistic regression results showed that the type of care mode affected the prevalence of cognitive impairment, and the elderly in nursing homes had a high risk of cognitive impairment (odds ratio [OR] = 3.528, 95% confidence interval [CI]: 2.209–5.635, p < 0.001); depressive symptoms had a significant positive correlation with the odds of cognitive impairment (OR = 1.854, 95% CI: 1.052–3.266, p < 0.05); and the cognitive impairment rate increased with age (OR = 1.412, 95% CI: 1.044–1.910, p < 0.05).

Conclusions:

There was an increased prevalence in cognitive impairment as well as depressive symptoms in the aging population in Zhongshan city. Population-based mental health strategies need to be urgently implemented for the aging.

Keywords

depressive symptoms / cognitive impairment / nursing home / community-dwelling / elderly adults

Main Points

1. The prevalence of cognitive impairment in elderly adults living in nursing homes was significantly higher than that in community-dwelling adults.

2. An increased prevalence of depressive symptoms with age was found in the living in the community-dwelling elderly adults.

3. Depressive symptoms, care in nursing homes, and increased age confer risk for developing cognitive impairment in elderly adults.

1. Introduction

Aging has become a global phenomenon. According to a United Nations report, there were 703 million elderly people (aged 65 years old and above) in the world in 2019, and this figure will exceed 1.5 billion by 2050. It has been estimated that by 2050, one-sixth of the world’s population will be over 65 years old [1]. Asia is a continent with a rapidly aging population and there were 254 million people over 60 years old in China at the end of 2019, accounting for 18.1% of the total population [2]. Dementia and cognitive impairment are among the leading causes of disability and dependence among elderly adults and constitute a major economic burden for public health systems [3]. China is facing substantial challenges regarding its aging population, many of whom have some degree of dementia [4]. In China, there are an estimated 7.4 million elderly individuals with dementia, and this number will grow to 18 million by 2030 if effective preventions are not identified and implemented [5]. The prevalence of mild cognitive impairment among individuals aged \ge60 years (n = 410) has been reported as 21.46% in Shenzhen, while the prevalence of mild cognitive impairment among individuals aged \ge65 years (n = 2111) has been reported as 14.2% in Guangzhou [6]. However, the discrepancies in sample selection and methodology of the investigation limited the generalizability of the findings for general populations. The low reversibility of cognitive functional status, difficulty in treatment and rehabilitation, and high costs of medical services and long-term care impose a heavy burden on individuals, families, and society [7]. Therefore, identifying the factors that affect cognitive function among elderly populations is an urgent requirement.

The experience of aging is highly individual, with physical and mental health playing a pivotal role in shaping personal perception of growing old and level of self-sufficiency [8, 9, 10, 11]. Due to reasons such as the prevalence of chronic disease, small range of social activities, and decreased physiological functions, elderly adults’ psychological problems have their own unique characteristics. The association between depression and cognitive impairment is a complex and multifaceted issue that has significant implications for health care and quality of life of elderly adults. Cognitive dysfunction and dementia caused by senile depression have been observed, but early and mild cognitive dysfunction are difficult to identify by those who are not specialists [12]. Additionally, depressive symptoms are a common neuropsychiatric symptom among elderly adults, along with dementia and mild cognitive impairment [13, 14]. Depression has been associated to alterations in brain structure and function, particularly in brain areas linked with memory and executive functions [12]. Moreover, chronic stress experienced from depression results in the fluctuation of stress hormones, including cortisol, that can affect neuronal functions and impair cognitive processes [11, 14]. Depressed elderly people often perform poorly on tests of episodic memory, executive function, and visuospatial ability [15]. Alternatively, a decrease in cognitive abilities leads to feelings of frustration, helplessness, and social isolation, which in turn contribute to the development of depression [15]. Individuals with dementia and comorbid depressive symptoms suffer from more rapid cognitive decline than those without depressive symptoms [16]. Although the biological mechanism underlying bilateral interaction between depression and cognitive functioning are complex, neurotransmitter imbalance, brain inflammation, and cerebrovascular disease could affect such comorbidity [17]. Mood regulation and cognitive processes are highly connected and cognitive impairment is associated with imbalances in neurotransmitters such as serotonin, dopamine, and norepinephrine, which affect negative signaling pathways that regulate mood in the central nervous system. Moreover, chronic inflammation is associated with neuronal damage and reduced cognitive function, which contribute to both depressive mood and cognitive decline. Aging comorbidity, like hypertension and atherosclerosis, can exacerbate vascular alterations that can decrease the brain’s blood supply, which results in both cognitive impairment and depression. However, few studies have investigated the relationship between subsyndromal depression and cognitive impairment in elderly adults with Chinese Han nationality [18].

Style of care is one of the determining factors behind elderly people’s health [19]. Many elderly people lack auspicious life circumstances, a social environment, and good health. In these circumstances, a person’s social context can increase their exposure to stressful stimuli, and thus have negative repercussions on the perception of aging and quality of life [20]. Style of care (e.g., living in a nursing home or community) may also influence an individual’s adaptation to the changes brought about by old age [7]. However, studies comparing nursing home care with community-dwelling care have produced inconsistent results [21]. These studies have indicated that the quality of life among elderly people living in the community is higher than those living in nursing homes [22]. In addition, leaving one’s own home is one of the most dramatic events in old age [23]. It has the potential to provoke dissatisfaction and depression, which may detract from an individual’s perception of their quality of life. Several studies have confirmed that elderly people living in nursing homes have lower levels of mental and physical health than those living in the community [24]. Cognitive impairment is an irreversible disorder and early detection and prevention of cognitive impairment can ameliorate the prognosis of cognitive decline in elderly adults. Therefore, therapies for depressive symptoms in elderly adults may serve as an effective strategy for cognitive impairment intervention, as an association between depressive symptoms and cognitive impairment has been reported [25]. There have been a few research studies with large sample sizes reporting on the prevalence and correlation between depressive symptoms and cognitive impairment in elderly populations in southern China. However, there is a lack of consistent findings on the association between depressive symptoms and cognitive impairment among elderly adults in the community and nursing homes.

The aim of this study was (1) to elucidate the cognitive status and prevalence of depressive symptoms in elderly adults in both the community and nursing homes, and (2) to identify potential risk factors associated with cognitive impairment in elderly adults living in nursing homes.

2. Materials and Methods

2.1 Study Design and Participants

Participants

We conducted a cross-sectional study from May, 2021 to December, 2021 among nursing homes and the community in the city of Zhongshan in Southern China. Based on physical examinations of elderly people in Zhongshan, we applied a random cluster sampling method to select 4880 eligible elderly people in two communities and conducted a survey of 1825 elderly people living in 25 nursing homes. A total of 6705 individuals were included in this study. The inclusion criteria were: (1) age \ge65 years; (2) residence in nursing institutions or the community for more than 6 months; and (3) subjects were able to cooperate with the study team. Exclusion criteria were: (1) serious mental health conditions, e.g., schizophrenia; (2) unable to care for themselves, e.g., terminally ill or bedridden individuals; and (3) subjects refused to participate in the study. Trained nurses and community staff collected general demographic information and screened the cognitive and depressive symptoms that were determined with self-reported rating scales. Sociodemographic parameters were obtained during face-to-face interviews, including age, gender, and area of residence (urban or rural). Before participation, written informed consent was obtained from all participants. The study was approved by the institutional review board of the Zhongshan Third People’s Hospital.

2.2 Patient Health Questionnaire-9

We used the Patient Health Questionnaire-9 (PHQ-9) as a reference test to assess the presence of depressive symptoms according to the Diagnostic and Statistical Manual of Mental Disorders 4th Edition (DSM-IV) [26, 27]. International guidelines state that the PHQ-9 is a reliable and effective tool for detecting depressive symptoms in primary care and community populations [28] and is designed to detect depressive symptoms among elderly populations. It is a 9-item screening instrument that corresponds to depressive symptoms over the past 2 weeks. It is scored on a 4-point (never = 0 point; 3 to 4 days = 1 points; 8 to 10 days = 2 points; and 12 to 14 days = 3 points) scale. The scores range from 0 to 27 points, with higher scores indicating more severe depression. In this study, we regarded the presence of depressive symptoms as a score of \ge10 on the PHQ-9. All participants with a score of 10 were grouped in the no depressive symptoms group. The criteria for the presence or absence of depressive symptoms are described in Kroenke’s study [29]. The Cronbach’s alpha coefficient of the PHQ-9 was 0.839 [30].

2.3 Ascertain Dementia-8

Ascertain Dementia 8 (AD-8) is a questionnaire-based scale originally developed in 2005 at the Alzheimer’s Disease Research Center at Washington University in St. Louis. The advantages of AD-8 are that it has a simple scoring system and requires minimal training. It has been used in many residential communities, primary health care centers, and hospitals [31]. The AD-8 has validity and sensitivity in screening for cognitive impairment in elderly adults [32]. This test consists of an 8-item informant-based questionnaire, which detects changes in memory, orientation, judgement, and executive function. The AD-8 has a score from 0 to 8 points depending on the number of positive responses; a score of \ge2 indicates cognitive impairment [33]. The Cronbach’s alpha for the Chinese AD-8 is 0.89 [34].

2.4 Statistical Analysis

All data were analyzed using Excel 2020 version (Microsoft, Redmond, WA, USA) and Statistical Package for the Social Sciences 26.0 version (SPSS IBM, Armonk, NY, USA). The statistical significance level was set as 0.05. Categorical variables, including gender, age group, educational level, and marital status were expressed in terms of numbers and percentages. We conducted descriptive analysis to assess sociodemographic and other factors, and a chi-squared test to compare categorical variables for the group involved. We constructed a stepwise forward logistic regression model to identify the relationship among demographic factors, depressive symptoms, care factor, and cognitive impairment, with p 0.05 considered statistically significant. The study model was composed of model 1, model 2, and model 3. Model 1 adjusted for type of care. Model 2 included model 1 with additional adjustment for age. Model 3 included model 2 with additional adjustment for depressive symptoms.

3. Results

3.1 Characteristics of Participants

Of the 6705 eligible elderly people over 65 years who were included in the investigation, 6348 completed the questionnaire survey, including 4703 elderly people living in the community and 1645 elderly people living in nursing homes, yielding a response rate of 94.6%. The two groups’ average ages were 73.27 \pm 7.08 years and 81.81 \pm 8.44 years, respectively. The average age of nursing home inhabitants was higher than that of those in residential communities (p 0.001). There were no statistical differences in either gender composition or education level between two groups, and there were slightly more women than men. There were more elderly people living in nursing homes alone or widowed than living in residential communities (p 0.001). The results are shown in Table 1.

3.2 Prevalence of Cognitive Impairment and Depressive Symptoms in the two Care Groups

The prevalence of depressive symptoms and cognitive impairment by age group and gender are shown in Tables 2,3. The overall prevalence of depressive symptoms was 3.9% in the community-dwelling group and 2.0% in the nursing home group. The prevalence of depressive symptoms increased with age in the community-dwelling group (p 0.001).

The overall prevalence of cognitive impairment was 12.5% in the community-dwelling group and 52.2% in the nursing home group. Both groups’ cognitive impairment rates increased with age (p 0.001), but the prevalence of cognitive impairment in nursing homes was significantly higher than that in community-dwelling groups for the same age group (\chi² = 1091.23, p 0.001). Females in both groups had higher rates of cognitive impairment than males (p = 0.015 and p = 0.013).

3.3 Cognitive Impairment Risk Factors

The binary logistic regression results showed that in the crude model and the two adjusted models, the two different care modes affected the prevalence of cognitive impairment, and elderly adults in nursing homes had a high risk of cognitive impairment (odds ratio [OR] = 3.528, 95% confidence interval [CI]: 2.209–5.635, p 0.001); depressive symptoms had a significant positive correlation with the odds of cognitive impairment (OR = 1.854, 95% CI: 1.052–3.266, p 0.05); and the cognitive impairment rate increased with age (OR = 1.412, 95% CI: 1.044–1.910, p 0.05). Marital status was not included in the analysis because most elderly people in nursing homes were either living alone or widowed, and the overall care mode was included as an independent variable to mitigate possible interactions or confounders. Results of the statistical analyses are shown in Table 4.

4. Discussion

To the best of our knowledge, this is the first cross-sectional, observational study to investigate the prevalence and correlates of depressive symptoms as well as cognitive impairment in elderly adults in Zhongshan city.

The overall prevalence of depressive symptoms was 3.9% among elderly adults living in the community and 2.0% among those living in nursing homes in the city of Zhongshan in Guangdong province. Moreover, the prevalence of depressive symptoms increased with age among elderly adults living in the community, but not among those living in nursing homes in the sample from our study. Overall, the prevalence of depressive symptoms in elderly adults living in Zhongshan was lower than that in elderly adults in several other city-based investigations in China [35, 36, 37, 38]. The prevalence of depressive symptoms in the current study was also lower than the pooled prevalence data yielded from a recent systematic review in China [39, 40]. The discrepancies between the studies could be due to the following reasons. First, the geographic location where the investigations were conducted could have influenced the prevalence of depressive symptoms. Findings from previous studies have associated areas with high levels of economic and social development with lower incidence of depressive symptoms. This could partly explain why there is a lower prevalence of depressive symptoms in Southern China than in Central and Northern China [37, 38, 41, 42]. Second, the year in which the data was collected could have contributed to the prevalence of depressive symptoms in elderly adults [40, 43]. In the wake of dramatic social-economic development, a downward trend in the prevalence of depressive symptoms among elderly adults in China started in the 1990s [39, 44]. Furthermore, inconsistencies in the prevalence of depressive symptoms in elderly adults have been detected with the PHQ-9, Geriatric Depression Scale-30 (GDS-30), and Center for Epidemiological Studies Depressive-10 (CES-D-10). However, the PHQ-9’s reliability in evaluating depressive symptoms among elderly adults has been established [43, 45, 46].

Consistent with findings from previous studies, increased age was associated with a high prevalence of depressive symptoms among elderly adults in the current study, although this relationship was not observed in those living in nursing homes [47, 48]. As age increases, so too do the incidences of physical illness, movement disability, and loneliness, which increase the risk of depressive symptoms [49, 50]. However, this association has not been observed among elderly adults living in nursing homes. The severity of cognitive impairment and aging could limit elderly adults’ ability to describe their depressive symptoms [51]. Gender differences could contribute to the prevalence of depressive symptoms in adult populations. However, the gender effect is diminished in elderly adults, as has been reported in previous epidemiological studies, which resulted from confounding factors including physical and socioeconomic status [52, 53].

In the wake of exceptional socioeconomic development and an aging population, diminishing cognitive function among elderly adults has raised considerable public concern. In the present study, the prevalence of cognitive impairment was 12.5% among the community-dwelling elderly. This was consistent with that of elderly adults in Chongqing, which was reported as 12.6% [37], but far less than that of elderly adults in both urban [54, 55] and rural [18] areas, as reported by studies conducted in different areas of China [56]. Such variability may be due to differences in population distribution and screening tools within the studies. Furthermore, socioeconomic development and adequate health resources could contribute to the mitigation of health problems among this population [57]. Zhongshan, located in the Pearl River Delta Economic Zone, is an economically developed city. This could decrease the likelihood of cognitive impairment for this area’s population. Furthermore, most of the participants in this study were elderly adults living in urban areas, while those living in rural areas were more likely to experience cognitive impairment [58]. Conversely, the prevalence of cognitive impairment detected by the Mini-Mental State Exam (MMSE) was higher than that detected by the AD-8 [56, 59]. The reason for this may be that the MMSE is more sensitive to cognitive impairment than the AD-8 scale, which is designed for screening mild dementia in the general elderly population [51].

Consistent with the results of previous studies, we found that the prevalence of cognitive impairment in elderly adults increased with age [37, 60]. Previous studies have confirmed age as an independent risk factor [61]. Moreover, the number and severity of physical illnesses increase along with age, which may increase the risk of developing cognitive impairment [62]. Biologically, cellular, and molecular mechanisms underlie age-related cognitive impairment, including fewer synapses, increased levels of oxidative stress, and mitochondrial dysfunction [63, 64].

Additionally, the current study indicated that elderly women had a higher prevalence of cognitive impairment than elderly men, which is consistent with previous studies [37, 65]. On the contrary, studies from some developed countries have failed to find gender differences in the prevalence of cognitive impairment [66, 67]. This may be moderated by the effects of socioeconomic factors [52].

One intriguing difference identified in the current study was that the prevalence of cognitive impairment among elderly adults in nursing homes was significantly higher than that among those living in the community. This is consistent with studies from developed countries [62, 68], and slightly higher than that reported in other areas in China [58]. The exceptionally high prevalence of cognitive impairment in nursing homes was probably due to indication bias, screening tool selection, and reverse causality. Intriguingly, elderly individuals with cognitive impairment are more likely to be moved into nursing homes to receive the care they need. Moreover, cognitive impairment is influenced by multiple factors, including age, gender, education level, and mental health status. We determined that some independent factors, particularly increased age and depressive symptoms, are associated with a higher level of cognitive impairment. This is consistent with the findings of previous reports [37, 69, 70]. Moreover, we confirmed that depressive symptoms, one of the modifiable risk factors, were positively associated with cognitive dysfunction in elderly adults [71]. Additionally, a growing body of studies has suggested that similar alterations in brain morphology and neuroplasticity are likely associated with depressive, as well as cognitive, impairment symptoms [72]. Furthermore, the pro-inflammatory signaling induced by depressive symptoms inhibits neuroplasticity and neurogenesis, which is associated with cognitive regulation [73]. Our findings suggest that early interventions to improve depressive symptoms could be an efficient way to relieve cognitive impairment in elderly populations, based on currently available evidence.

The relationship between depressive symptoms and cognitive impairment has been extensively studied in elderly adults [74]. An aging population with depression has a two-fold risk of cognitive impairment [75]. One of the possible reasons is that cognitive alteration initially depends on the age of the frontal lobe, which is also shared with the risk of developing depression [76]. Another possibility is that the severity of depressive symptoms may influence stress-sensitive brain regions, including the hippocampus and prefrontal cortex, making them susceptible to neurodegenerative changes [77]. Based on our findings, managing depressive symptoms in elderly adults as part of an interventional approach to cognitive impairment is essential, and vice versa.

The current study has two notable strengths. It is a single-center, large-scale, population-based, observational study investigating the prevalence and correlates of depressive symptoms as well as cognitive impairment in elderly adults in either the community or care homes in China. Furthermore, we found that depressive symptoms were positively associated with cognitive impairment in elderly adults, particularly those living in nursing homes. Finally, the findings provide clues for the promising early intervention for cognitive impairment in elderly adults, such as utilizing group psychotherapy or music therapy to alleviate depressive symptoms and delay the progression of cognitive impairment.

The results of the current study should be interpreted with caution due to the following limitations. As the study was cross-sectional, we could not confirm whether there was a cause-effect relationship between depressive symptoms and cognitive impairment. Future studies are needed to confirm this. Moreover, we conducted this study among urban residents in Zhongshan, which is a medium-sized city in Guangdong province, in Southern China. This limits the results’ generalizability, particularly for those living in less-developed and rural areas. Furthermore, due to the limited data available, we were unable to analyze the effects of socioeconomic, biological, or environmental factors on depressive symptoms and cognitive impairment, albeit these risk factors for depression and dementia among elderly adults have been established. Diagnostic assessment instead of informant-based questionnaires will improve the validity of evaluation of cognitive impairment in elderly adults, although short-item questionnaires have been regularly employed for large sample-sized, epidemiological studies. Finally, more sensitive detection of depressive symptoms and cognitive impairment would be a welcome methodological improvement in future research, as this may clarify the association between depressive symptoms and degrees of cognitive function.

5. Conclusions

There is an increased prevalence of cognitive impairment as well as depressive symptoms in the elderly population in Zhongshan city. Furthermore, there is an urgent need to implement population-based strategies, including cognitive function screening accompanied by psychological well-being evaluation, among elderly adult populations in nursing homes.

Availability of Data and Materials

The data underlying this article cannot be shared publicly due to the privacy of individuals that participated in the study. The data will be shared on reasonable request to the corresponding author. The part of results from current study were presented at the 2022 Annual Meeting of Guangdong Psychiatrist Association in 11/06/2022 to the psychiatrists from Guangdong province.

References

[1] United Nations. Ageing. 2002. Available at: https://social.desa.un.org/issues/ageing (Accessed: 24 April 2021).

[2] National Bureau of Statistics. National economic and social development statistical bulletin of the people’s Republic of China 2019. 2020. Available at: https://www.stats.gov.cn/sj/zxfb/202302/t20230203_1900640.html (Accessed: 24 March 2021).

[3] Guaita A, Vaccaro R, Davin A, Colombo M, Vitali SF, Polito L, et al. Influence of socio-demographic features and apolipoprotein E epsilon 4 expression on the prevalence of dementia and cognitive impairment in a population of 70-74-year olds: the InveCe.Ab study. Archives of Gerontology and Geriatrics. 2015; 60: 334–343. https://doi.org/10.1016/j.archger.2014.11.006.

[4] Ji Y, Shi Z, Zhang Y, Liu S, Liu S, Yue W, et al. Prevalence of dementia and main subtypes in rural northern China. Dementia and Geriatric Cognitive Disorders. 2015; 39: 294–302. https://doi.org/10.1159/000375366.

[5] Ding D, Zhao Q, Guo Q, Meng H, Wang B, Yu P, et al. The Shanghai Aging Study: study design, baseline characteristics, and prevalence of dementia. Neuroepidemiology. 2014; 43: 114–122. https://doi.org/10.1159/000366163.

[6] Rao D, Luo X, Tang M, Shen Y, Huang R, Yu J, et al. Prevalence of mild cognitive impairment and its subtypes in community-dwelling residents aged 65 years or older in Guangzhou, China. Archives of Gerontology and Geriatrics. 2018; 75: 70–75. https://doi.org/10.1016/j.archger.2017.11.003.

[7] Ritchie SJ, Tucker-Drob EM, Cox SR, Corley J, Dykiert D, Redmond P, et al. Predictors of ageing-related decline across multiple cognitive functions. Intelligence. 2016; 59: 115–126. https://doi.org/10.1016/j.intell.2016.08.007.

[8] Halaweh H, Dahlin-Ivanoff S, Svantesson U, Willén C. Perspectives of Older Adults on Aging Well: A Focus Group Study. Journal of Aging Research. 2018; 2018: 9858252. https://doi.org/10.1155/2018/9858252.

[9] Martinson M, Berridge C. Successful aging and its discontents: a systematic review of the social gerontology literature. The Gerontologist. 2015; 55: 58–69. https://doi.org/10.1093/geront/gnu037.

[10] Puvill T, Lindenberg J, de Craen AJM, Slaets JPJ, Westendorp RGJ. Impact of physical and mental health on life satisfaction in old age: a population based observational study. BMC Geriatrics. 2016; 16: 194. https://doi.org/10.1186/s12877-016-0365-4.

[11] Chan CS, Slaughter SE, Jones CA, Wagg AS. Greater Independence in Activities of Daily Living is Associated with Higher Health-Related Quality of Life Scores in Nursing Home Residents with Dementia. Healthcare. 2015; 3: 503–518. https://doi.org/10.3390/healthcare3030503.

[12] Galluzzi S, Cimaschi L, Ferrucci L, Frisoni GB. Mild cognitive impairment: clinical features and review of screening instruments. Aging. 2001; 13: 183–202. https://doi.org/10.1007/BF03351477.

[13] Park MH, Min JY, Min HY, Lee HJ, Lee DH, Song MS. Subjective memory complaints and clinical characteristics in elderly Koreans: a questionnaire survey. International Journal of Nursing Studies. 2007; 44: 1400–1405. https://doi.org/10.1016/j.ijnurstu.2006.06.001.

[14] Enache D, Winblad B, Aarsland D. Depression in dementia: epidemiology, mechanisms, and treatment. Current Opinion in Psychiatry. 2011; 24: 461–472. https://doi.org/10.1097/YCO.0b013e32834bb9d4.

[15] Elderkin-Thompson V, Boone KB, Hwang S, Kumar A. Neurocognitive profiles in elderly patients with frontotemporal degeneration or major depressive disorder. Journal of the International Neuropsychological Society. 2004; 10: 753–771. https://doi.org/10.1017/S1355617704105067.

[16] Rapp MA, Schnaider-Beeri M, Wysocki M, Guerrero-Berroa E, Grossman HT, Heinz A, et al. Cognitive decline in patients with dementia as a function of depression. The American Journal of Geriatric Psychiatry. 2011; 19: 357–363. https://doi.org/10.1097/JGP.0b013e3181e898d0.

[17] Cui L, Li S, Wang S, Wu X, Liu Y, Yu W, et al. Major depressive disorder: hypothesis, mechanism, prevention and treatment. Signal Transduction and Targeted Therapy. 2024; 9: 30. https://doi.org/10.1038/s41392-024-01738-y.

[18] Deng Y, Zhao S, Cheng G, Yang J, Li B, Xu K, et al. The Prevalence of Mild Cognitive Impairment among Chinese People: A Meta-Analysis. Neuroepidemiology. 2021; 55: 79–91. https://doi.org/10.1159/000512597.

[19] World Health Organization. World Report on Ageing and Health, World Health Organization: Geneva, Switzerland. 2015. Available at: https://www.who.int/publications/i/item/9789241565042 (Accessed: 18 April 2020).

[20] Babazadeh T, Sarkhoshi R, Bahadori F, Moradi F, Shariat F. Prevalence of depression, anxiety and stress disorders in elderly people residing in Khoy, Iran (2014-2015). Journal of Analytical Research in Clinical Medicine. 2016; 4: 122–128.

[21] Boland L, Légaré F, Perez MMB, Menear M, Garvelink MM, McIsaac DI, et al. Impact of home care versus alternative locations of care on elder health outcomes: an overview of systematic reviews. BMC Geriatrics. 2017; 17: 20. https://doi.org/10.1186/s12877-016-0395-y.

[22] Olsen C, Pedersen I, Bergland A, Enders-Slegers MJ, Jøranson N, Calogiuri G, et al. Differences in quality of life in home-dwelling persons and nursing home residents with dementia - a cross-sectional study. BMC Geriatrics. 2016; 16: 137. https://doi.org/10.1186/s12877-016-0312-4.

[23] Roy N, Dubé R, Després C, Freitas A, Légaré F. Choosing between staying at home or moving: A systematic review of factors influencing housing decisions among frail older adults. PloS One. 2018; 13: e0189266. https://doi.org/10.1371/journal.pone.0189266.

[24] Jafari F, Khatony A, Mehrdad M. Self-Esteem Among the Elderly Visiting the Healthcare Centers in Kermanshah-Iran (2012). Global Journal of Health Science. 2015; 7: 352–358. https://doi.org/10.5539/gjhs.v7n5p352.

[25] Shin M. Depressive symptoms with cognitive dysfunction increase the risk of cognitive impairment: analysis of the Korean Longitudinal Study of Aging (KLoSA), 2006-2018. International Psychogeriatrics. 2021; 33: 791–801. https://doi.org/10.1017/S1041610220003622.

[26] Park SC, Lee HY, Lee DW, Hahn SW, Park SH, Kim YJ, et al. Screening for Depressive Disorder in Elderly Patients with Chronic Physical Diseases Using the Patient Health Questionnaire-9. Psychiatry Investigation. 2017; 14: 306–313. https://doi.org/10.4306/pi.2017.14.3.306.

[27] Byeon H. Relationship between Physical Activity Level and Depression of Elderly People Living Alone. International Journal of Environmental Research and Public Health. 2019; 16: 4051. https://doi.org/10.3390/ijerph16204051.

[28] Costantini L, Pasquarella C, Odone A, Colucci ME, Costanza A, Serafini G, et al. Screening for depression in primary care with Patient Health Questionnaire-9 (PHQ-9): A systematic review. Journal of Affective Disorders. 2021; 279: 473–483. https://doi.org/10.1016/j.jad.2020.09.131.

[29] Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine. 2001; 16: 606–613. https://doi.org/10.1046/j.1525-1497.2001.016009606.x.

[30] Sun Y, Kong Z, Song Y, Liu J, Wang X. The validity and reliability of the PHQ-9 on screening of depression in neurology: a cross sectional study. BMC Psychiatry. 2022; 22: 98. https://doi.org/10.1186/s12888-021-03661-w.

[31] Chen HH, Sun FJ, Yeh TL, Liu HE, Huang HL, Kuo BIT, et al. The diagnostic accuracy of the Ascertain Dementia 8 questionnaire for detecting cognitive impairment in primary care in the community, clinics and hospitals: a systematic review and meta-analysis. Family Practice. 2018; 35: 239–246. https://doi.org/10.1093/fampra/cmx098.

[32] Yang YH, Galvin JE, Morris JC, Lai CL, Chou MC, Liu CK. Application of AD8 questionnaire to screen very mild dementia in Taiwanese. American Journal of Alzheimer’s Disease and other Dementias. 2011; 26: 134–138. https://doi.org/10.1177/1533317510397330.

[33] Galvin JE, Roe CM, Powlishta KK, Coats MA, Muich SJ, Grant E, et al. The AD8: a brief informant interview to detect dementia. Neurology. 2005; 65: 559–564. https://doi.org/10.1212/01.wnl.0000172958.95282.2a.

[34] Ham Y, Bae S, Lee H, Ha Y, Choi H, Park JH, et al. Item-level psychometrics of the Ascertain Dementia Eight-Item Informant Questionnaire. PLoS ONE. 2022; 17: e0270204. https://doi.org/10.1371/journal.pone.0270204.

[35] Ma X, Xiang YT, Li SR, Xiang YQ, Guo HL, Hou YZ, et al. Prevalence and sociodemographic correlates of depression in an elderly population living with family members in Beijing, China. Psychological Medicine. 2008; 38: 1723–1730. https://doi.org/10.1017/S0033291708003164.

[36] Yu J, Li J, Cuijpers P, Wu S, Wu Z. Prevalence and correlates of depressive symptoms in Chinese older adults: a population-based study. International Journal of Geriatric Psychiatry. 2012; 27: 305–312. https://doi.org/10.1002/gps.2721.

[37] Giri M, Chen T, Yu W, Lü Y. Prevalence and correlates of cognitive impairment and depression among elderly people in the world’s fastest growing city, Chongqing, People’s Republic of China. Clinical Interventions in Aging. 2016; 11: 1091–1098. https://doi.org/10.2147/CIA.S113668.

[38] Liu A, Peng Y, Zhu W, Zhang Y, Ge S, Zhou Y, et al. Analysis of Factors Associated With Depression in Community-Dwelling Older Adults in Wuhan, China. Frontiers in Aging Neuroscience. 2021; 13: 743193. https://doi.org/10.3389/fnagi.2021.743193.

[39] Wang F, Zhang QE, Zhang L, Ng CH, Ungvari GS, Yuan Z, et al. Prevalence of major depressive disorder in older adults in China: A systematic review and meta-analysis. Journal of Affective Disorders. 2018; 241: 297–304. https://doi.org/10.1016/j.jad.2018.07.061.

[40] Tang T, Jiang J, Tang X. Prevalence of depressive symptoms among older adults in mainland China: A systematic review and meta-analysis. Journal of Affective Disorders. 2021; 293: 379–390. https://doi.org/10.1016/j.jad.2021.06.050.

[41] Liu Q, Cai H, Yang LH, Xiang YB, Yang G, Li H, et al. Depressive symptoms and their association with social determinants and chronic diseases in middle-aged and elderly Chinese people. Scientific Reports. 2018; 8: 3841. https://doi.org/10.1038/s41598-018-22175-2.

[42] Jin Y, Si H, Qiao X, Tian X, Liu X, Xue QL, et al. Relationship Between Frailty and Depression Among Community-Dwelling Older Adults: The Mediating and Moderating Role of Social Support. The Gerontologist. 2020; 60: 1466–1475. https://doi.org/10.1093/geront/gnaa072.

[43] Li D, Zhang DJ, Shao JJ, Qi XD, Tian L. A meta-analysis of the prevalence of depressive symptoms in Chinese older adults. Archives of Gerontology and Geriatrics. 2014; 58: 1–9. https://doi.org/10.1016/j.archger.2013.07.016.

[44] Chen R, Copeland JR, Wei L. A meta-analysis of epidemiological studies in depression of older people in the People’s Republic of China. International Journal of Geriatric Psychiatry. 1999; 14: 821–830. https://doi.org/10.1002/(sici)1099-1166(199910)14:10<821::aid-gps21>3.0.co;2-0.

[45] Ye X, Shu HL, Feng X, Xia DM, Wang ZQ, Mi WY, et al. Reliability and validity of the Chinese version of the Patient Health Questionnaire-9 (C-PHQ-9) in patients with psoriasis: a cross-sectional study. BMJ Open. 2020; 10: e033211. https://doi.org/10.1136/bmjopen-2019-033211.

[46] Kim AR, Park JH, Park HY. Analysis of Factors Affecting Depression in Older Adults in South Korea. International Journal of Environmental Research and Public Health. 2021; 18: 9887. https://doi.org/10.3390/ijerph18189887.

[47] Kaburagi T, Hirasawa R, Yoshino H, Odaka Y, Satomi M, Nakano M, et al. Nutritional status is strongly correlated with grip strength and depression in community-living elderly Japanese. Public Health Nutrition. 2011; 14: 1893–1899. https://doi.org/10.1017/S1368980011000346.

[48] Yoshimura K, Yamada M, Kajiwara Y, Nishiguchi S, Aoyama T. Relationship between depression and risk of malnutrition among community-dwelling young-old and old-old elderly people. Aging & Mental Health. 2013; 17: 456–460. https://doi.org/10.1080/13607863.2012.743961.

[49] Jorm AF. Does old age reduce the risk of anxiety and depression? A review of epidemiological studies across the adult life span. Psychological Medicine. 2000; 30: 11–22. https://doi.org/10.1017/s0033291799001452.

[50] Cole MG, Dendukuri N. Risk factors for depression among elderly community subjects: a systematic review and meta-analysis. The American Journal of Psychiatry. 2003; 160: 1147–1156. https://doi.org/10.1176/appi.ajp.160.6.1147.

[51] Xu S, Jin X, Liu C, Jin Y, Xu Y, Chen L, et al. Investigating the Prevalence of Dementia and Its Associated Risk Factors in a Chinese Nursing Home. Journal of Clinical Neurology. 2017; 13: 10–14. https://doi.org/10.3988/jcn.2017.13.1.10.

[52] Veijola J, Puukka P, Lehtinen V, Moring J, Lindholm T, Väisänen E. Sex differences in the association between childhood experiences and adult depression. Psychological Medicine. 1998; 28: 21–27. https://doi.org/10.1017/s0033291797006089.

[53] Park JH, Lee JJ, Lee SB, Huh Y, Choi EA, Youn JC, et al. Prevalence of major depressive disorder and minor depressive disorder in an elderly Korean population: results from the Korean Longitudinal Study on Health and Aging (KLoSHA). Journal of Affective Disorders. 2010; 125: 234–240. https://doi.org/10.1016/j.jad.2010.02.109.

[54] Cheng Y, Xiao S. Recent research about mild cognitive impairment in China. Shanghai Archives of Psychiatry. 2014; 26: 4–14. https://doi.org/10.3969/j.issn.1002-0829.2014.01.002.

[55] Ding D, Zhao Q, Guo Q, Meng H, Wang B, Luo J, et al. Prevalence of mild cognitive impairment in an urban community in China: a cross-sectional analysis of the Shanghai Aging Study. Alzheimer’s & Dementia. 2015; 11: 300–309.e2. https://doi.org/10.1016/j.jalz.2013.11.002.

[56] Yang L, Jin X, Yan J, Jin Y, Xu S, Xu Y, et al. Comparison of prevalence and associated risk factors of cognitive function status among elderly between nursing homes and common communities of China: A STROBE-compliant observational study. Medicine. 2019; 98: e18248. https://doi.org/10.1097/MD.0000000000018248.

[57] Liu LJ, Guo Q. Life satisfaction in a sample of empty-nest elderly: a survey in the rural area of a mountainous county in China. Quality of Life Research: an International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation. 2008; 17: 823–830. https://doi.org/10.1007/s11136-008-9370-1.

[58] De Ronchi D, Palmer K, Pioggiosi P, Atti AR, Berardi D, Ferrari B, et al. The combined effect of age, education, and stroke on dementia and cognitive impairment no dementia in the elderly. Dementia and Geriatric Cognitive Disorders. 2007; 24: 266–273. https://doi.org/10.1159/000107102.

[59] Chio OI, Yip PK, Liu YC, Chen LH, Wang PC, Tsai TH, et al. Detection of cognitive impairment using self-rated AD8 and informant-reported AD8. Journal of the Formosan Medical Association. 2018; 117: 42–47. https://doi.org/10.1016/j.jfma.2017.02.015.

[60] Rodríguez-Sánchez E, Mora-Simón S, Patino-Alonso MC, García-García R, Escribano-Hernández A, García-Ortiz L, et al. Prevalence of cognitive impairment in individuals aged over 65 in an urban area: DERIVA study. BMC Neurology. 2011; 11: 147. https://doi.org/10.1186/1471-2377-11-147.

[61] Zhang ZX, Zahner GEP, Román GC, Liu XH, Wu CB, Hong Z, et al. Socio-demographic variation of dementia subtypes in china: Methodology and results of a prevalence study in Beijing, Chengdu, Shanghai, and Xian. Neuroepidemiology. 2006; 27: 177–187. https://doi.org/10.1159/000096131.

[62] Hoffmann F, Kaduszkiewicz H, Glaeske G, van den Bussche H, Koller D. Prevalence of dementia in nursing home and community-dwelling older adults in Germany. Aging Clinical and Experimental Research. 2014; 26: 555–559. https://doi.org/10.1007/s40520-014-0210-6.

[63] Yao J, Brinton RD. Targeting mitochondrial bioenergetics for Alzheimer’s prevention and treatment. Current Pharmaceutical Design. 2011; 17: 3474–3479. https://doi.org/10.2174/138161211798072517.

[64] Graham SH, Liu H. Life and death in the trash heap: The ubiquitin proteasome pathway and UCHL1 in brain aging, neurodegenerative disease and cerebral Ischemia. Ageing Research Reviews. 2017; 34: 30–38. https://doi.org/10.1016/j.arr.2016.09.011.

[65] Miyawaki CE, Liu M. Gender differences in cognitive impairment among the old and the oldest-old in China. Geriatrics & Gerontology International. 2019; 19: 586–592. https://doi.org/10.1111/ggi.13666.

[66] Chodosh J, Reuben DB, Albert MS, Seeman TE. Predicting cognitive impairment in high-functioning community-dwelling older persons: MacArthur Studies of Successful Aging. Journal of the American Geriatrics Society. 2002; 50: 1051–1060. https://doi.org/10.1046/j.1532-5415.2002.50260.x.

[67] Mielke MM, Vemuri P, Rocca WA. Clinical epidemiology of Alzheimer’s disease: assessing sex and gender differences. Clinical Epidemiology. 2014; 6: 37–48. https://doi.org/10.2147/CLEP.S37929.

[68] Magaziner J, German P, Zimmerman SI, Hebel JR, Burton L, Gruber-Baldini AL, et al. The prevalence of dementia in a statewide sample of new nursing home admissions aged 65 and older: diagnosis by expert panel. Epidemiology of Dementia in Nursing Homes Research Group. The Gerontologist. 2000; 40: 663–672. https://doi.org/10.1093/geront/40.6.663.

[69] Cherubini A, Ruggiero C, Dell’Aquila G, Eusebi P, Gasperini B, Zengarini E, et al. Underrecognition and undertreatment of dementia in Italian nursing homes. Journal of the American Medical Directors Association. 2012; 13: 759.e7–759.e13. https://doi.org/10.1016/j.jamda.2012.05.015.

[70] Jiang F, Kong F, Li S. The Association between Social Support and Cognitive Impairment among the Urban Elderly in Jinan, China. Healthcare. 2021; 9: 1443. https://doi.org/10.3390/healthcare9111443.

[71] Aznar S, Knudsen GM. Depression and Alzheimer’s disease: is stress the initiating factor in a common neuropathological cascade? Journal of Alzheimer’s Disease. 2011; 23: 177–193. https://doi.org/10.3233/JAD-2010-100390.

[72] Hussain M, Kumar P, Khan S, Gordon DK, Khan S. Similarities Between Depression and Neurodegenerative Diseases: Pathophysiology, Challenges in Diagnosis and Treatment Options. Cureus. 2020; 12: e11613. https://doi.org/10.7759/cureus.11613.

[73] Réus GZ, Titus SE, Abelaira HM, Freitas SM, Tuon T, Quevedo J, et al. Neurochemical correlation between major depressive disorder and neurodegenerative diseases. Life Sciences. 2016; 158: 121–129. https://doi.org/10.1016/j.lfs.2016.06.027.

[74] Ly M, Karim HT, Becker JT, Lopez OL, Anderson SJ, Aizenstein HJ, et al. Late-life depression and increased risk of dementia: a longitudinal cohort study. Translational Psychiatry. 2021; 11: 147. https://doi.org/10.1038/s41398-021-01269-y.

[75] Villarreal AE, Grajales S, Lopez L, Britton GB, Panama Aging Research Initiative. Cognitive Impairment, Depression, and Cooccurrence of Both among the Elderly in Panama: Differential Associations with Multimorbidity and Functional Limitations. BioMed Research International. 2015; 2015: 718701. https://doi.org/10.1155/2015/718701.

[76] Rashedi V, Rezaei M, Gharib M. Prevalence of cognitive impairment in community-dwelling older adults. Basic and Clinical Neuroscience. 2014; 5: 28–30.

[77] Wilson RS, Mendes De Leon CF, Bennett DA, Bienias JL, Evans DA. Depressive symptoms and cognitive decline in a community population of older persons. Journal of Neurology, Neurosurgery, and Psychiatry. 2004; 75: 126–129.

Funding

Social Welfare Science and Technology Research Project in Zhongshan(2021B1113)

Social Welfare Science and Technology Research Project in Zhongshan(2021B1114)

Social Welfare Science and Technology Research Major Project in Zhongshan(2021B3019)

Social Welfare Science and Technology Research Major Project in Zhongshan(2022B3017)

Medical Science and Technology Research Fund Project of Guangdong(A2021205)

Medical Science and Technology Research Fund Project of Guangdong(A2023194)