Abstract
Background
The increasing prevalence of cognitive impairment poses substantial risks to older adults, particularly those with chronic diseases. While existing studies have examined the connection between the empty nest phenomenon and cognitive function, few have attempted to consider endogeneity issues within this relationship, with limited attention given to older adults with chronic diseases. This study investigates the impact of empty nest status on cognitive function among rural Chinese older adults with chronic diseases and explores the possible mechanisms underlying this effect.
Methods
A cross-sectional study involved 365 older adults aged 60 or above with chronic diseases in rural areas of Shaanxi province, northwest China. Cognitive function was measured using the Mini-Mental State Examination. Multiple regression models and the instrumental variable (IV) method were employed to examine the association between empty nest and cognitive function.
Results
Among the 365 older adults aged 60 or above with chronic diseases, 43% experienced cognitive impairment. Results from both multiple regression and IV analyses consistently demonstrate a significant association between empty nest status and higher cognitive function scores (β = 1.757, p = 0.007; β = 3.682, p = 0.034, respectively). Mechanism analysis further supports that the positive association may arise from empty nesters receiving more social support from children and friends, and perceiving loneliness experiences as inadequate. Heterogeneity analysis reveals that the association between empty nest status and cognitive function is more pronounced among male adults with chronic diseases.
Conclusions
This study challenges the notion that empty nest status is a risk factor for cognitive decline in older adults with chronic diseases in rural China. The positive impact is attributed to the robust social relationships of empty nesters, encompassing sustained support from their social network, and the absence of an increase in loneliness. Therefore, future interventions aimed at improving cognitive function in older adults may benefit from promoting the development of social relationships.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12877-024-05386-3.
Keywords: Empty nest, Cognitive function, Older adults, Chronic disease
Introduction
As our global population ages at an unprecedented rate, the challenge of cognitive decline among older adults, particularly in the rural areas of China, is gaining prominence. Dementia, affecting 50 million individuals worldwide, is projected to reach 152 million by 2050 [1]. In China, home to the world’s largest elderly population with 267 million individuals aged 60 or above, the prevalence of dementia in the general older population is 5.14% [2]. However, the prevalence is notably higher in rural areas (6.05%) compared to urban areas (4.40%) due to limited access to health care and poorer socioeconomic conditions [3]. Diseases related to cognitive decline have become one of the top concerns in the process of population aging [4]. Cognitive decline poses significant threats to the independence, well-being, and quality of life for older adults, consequently amplifying the risk of disability and mortality [5–8]. Furthermore, cognitive decline translates into higher healthcare costs, as illustrated by the estimated annual economic costs of treating dementia in China, reaching US$ 69.0 billion in 2020 and projected to climb to US$ 114.2 billion in 2030 [9].
Older adults with chronic diseases in rural China, representing a specific subgroup, confront distinctive challenges in cognitive function. Approximately 78% of older adults grapple with chronic conditions, and the situation is exacerbated in rural areas [10]. Recent evidence underscores the substantial impact of chronic conditions on the brain’s structure and function, heightening the vulnerability to cognitive decline and dementia, notably affecting memory and executive functions [11]. The prevalence of dementia among older adults with common chronic diseases is alarming, with higher rates observed in conditions such as diabetes [12], hypertension [12], and chronic obstructive pulmonary diseases [13]. Given the elevated risk of cognitive impairment among older adults with chronic diseases, there is an urgent need to direct heightened attention and allocate additional resources to address the distinctive needs of this vulnerable group.
The empty nest, where older adults reside alone or solely with their spouses, is recognized as a crucial influencing factor for the cognitive function of older adults [14]. Rooted in cultural traditions that underscore filial piety, Chinese older adults have historically relied on family support, particularly prevalent in rural areas. However, the landscape is undergoing transformation due to the increasing trends of urbanization, industrialization, and the implementation of the one-child policy in China. Consequently, traditional living arrangements have shifted, leading to a growing number of older adults transitioning into empty nesters, whether by personal choice or circumstantial factors [15]. The rising prevalence of empty nesters in China, constituting 49.3% of the older population, with 45.6% in rural areas, has become a cause for concern [10].
However, empirical studies on the relationship between empty nest and cognitive function of older adults in China have yielded conflicting results. Some studies assert that being an empty nester is detrimental to cognitive function [16, 17], highlighting potential deficits in emotional support, daily care and intergenerational connections. This situation may expose empty nesters to greater health risks compared to their non-empty nesters counterparts [14, 18]. Conversely, other studies propose a positive impact of the empty nest on older adults’ cognitive function, attributing it to increased independence and a slower age-related decline in physical ability, while also minimizing intergenerational conflicts [19, 20]. Meanwhile, research suggests that empty nesters may face fewer concerns in terms of social, economic, and well-being aspects, making them less susceptible to dementia and disability [21, 22]. Additionally, one study found no association between the empty nest and poorer cognitive function, attributing this to social and economic progress, as well as higher education levels among empty nesters [23]. Despite inconsistent findings, a significant limitation of these studies is the lack of consideration for endogenous factors (such as unobserved confounding and selection bias) in the analysis, which may impact the validity and reliability of the results. The challenge lies in determining whether empty nest status leads to cognitive impairment or if older adults with good health are more likely to be empty nesters. However, limited literature has paid attention to relieving endogenous problems [10, 24] and none has specifically addressed the cognitive vulnerability of older adults with chronic diseases. Given that older adults with chronic diseases may experience poorer health conditions, making them more reliant on receiving support from their children, further investigation is necessary to understand the influence of an empty nest on the cognitive function of older adults in this specific group.
The impact of the empty nest on older adults’ cognitive function involves various mechanisms, with social support and loneliness serving as crucial indicators of social relationships [25–27]. Social support, including both tangible assistance (e.g., material support) and intangible support (e.g., emotional assistance), plays a vital role in safeguarding the mental and physical well-being of older adults [28–30]. Unlike non-empty nesters, who can readily access instrumental and emotional support from their co-resident children, empty nesters may face an elevated risk of social isolation and smaller social networks [29]. Research suggests that a limited social support network is linked to poorer cognitive functioning, particularly in older adults who lack family support in Chinese culture [31]. On the other hand, loneliness, characterized by a subjective sense of isolation stemming from deficiencies in the number or quality of social relationships, is suggested as a vital mechanism linking the empty nest phenomenon to health impacts [32]. Studies indicate that empty nesters commonly experience social loneliness [33]. In turn, loneliness is identified as a potential risk factor for cognitive impairment [34]. Lonely individuals tend to engage in health-damaging behaviors, have a higher risk of depression, and exhibit less social involvement, all of which can contribute to an increased risk of dementia or cognitive decline [16, 35]. The role of social support and loneliness may vary among the specific group of older adults with chronic diseases, necessitating further exploration.
This study aims to investigate the relationship between empty nest and cognitive function in older adults with chronic diseases in rural China. Our methodology includes an exploration of these associations through both multiple regression analysis and the instrumental variable (IV) method. Furthermore, we delve into two crucial mechanisms in this relationship: social support and loneliness. Additionally, we conduct a gender-based heterogeneity analysis to uncover potential variations in the observed effects.
Methods
Sampling and data collection
The study gathered survey data in the early months of 2021 from a cross-sectional survey in three designated prefectures of Shaanxi province, located in northwest China. The rural population of Shaanxi province reached 14.37 million, comprising 36.37% of the total population, higher than the national average of 35.28%. By the end of 2021, individuals aged over 60 in Shaanxi Province accounted for 19.58%, higher than the national average of 18.94% [36]. Moreover, the per capita Gross Domestic Product within sampled prefectures was around $7,664 in 2021, which was lower than the Shaanxi province average of $11,682 [36]. Moreover, the number of rural inhabitants in these three prefectures is around 3.75 million, amounting to more than one-fourth of the rural population in Shaanxi province (26.08%) [36]. Thus, our sample can be considered representative of rural areas characterized by a high prevalence of poverty and an aging population in a typical Chinese province.
Within three designated prefectures, we employed a multi-layer random sampling approach. Firstly, 16 counties were randomly selected from 27 counties within the three prefectures. Secondly, townships and villages were randomly selected, excluding the urban township located in the county within each sampled county. Thirdly, households were randomly chosen within each sample village, with a specific focus on individuals aged 60 or above. In total, the study encompassed 607 older adults across 165 villages, with 408 of them having chronic diseases.
However, some older adults have some missing information regarding cognitive function due to physical reasons, such as hand disorders, deafness and dementia, thus 365 older adults in 150 villages were identified as having chronic diseases and included as study subjects. The effective sample rate was 89.46%. Additionally, due to funding and time constraints, a follow-up survey was conducted on the sample from prefecture A one year later.
Measurements
Dependent variable
Cognitive function was assessed by using the Mini-mental State Examination (MMSE), a commonly used test for general cognitive evaluation. The MMSE demonstrates good applicability and is extensively employed within the Chinese population [37], with a reported sensitivity of 85.2% and a specificity of 92.7% [38]. Scores on the MMSE range from 0 to 30, with higher scores reflecting higher levels of cognitive function. The scale consists of five domains: orientation (10 scores), registration (3 scores), attention and calculation (5 scores), recall (3 scores), language and praxis (9 scores). Many studies have consistently highlighted the association between cognitive impairment in older adults and their educational levels in China [39]. Our study adopts cut-off points recommended by the Shanghai Mental Health Center to define cognitive impairment, aligning with the following thresholds: 17/18 for those who are illiterate, 20/21 for those who are educated in primary school, and 24/25 for those who are educated in middle school or above [40].
Independent variable
The study categorizes older adults into two groups: empty nesters and non-empty nesters. This classification is based on the responses to two questions: (1) Whether someone has lived with you for more than 6 months in the past year? (2) If yes, were they your spouse, children, or others? Older adults who report living alone or only living with their spouses are considered empty nesters, while those living with others are classified as non-empty nesters.
Covariates
Based on previous literature, the study incorporates the following control variables: demographic variables including age, gender (female = 0, vs. male = 1); socioeconomic status including education (never go to school = 0, primary school = 1, junior high school or above = 2), family assets (the last half (less than mean) = 0, the first half (more than or equal to mean) = 1). “Family assets” refer to the combined value of various household possessions, assessed through a series of appliances owned, and calculated using Principal Component Analysis. Social relations including marital status (single or divorced or widow or widower = 0, married = 1), employment status (unemployed or farmer = 0, employed or retired = 1), health behaviors including exercise (no = 0, yes = 1), NRCMS (the New Rural Cooperative Medical Scheme) (no = 0, yes = 1); chronic disease status including the number of chronic diseases (one disease = 0, two diseases or above = 1), and duration of chronic diseases (years). What’s more, the study controls for medical expenses (first third = 1, middle third = 2, last third = 3) and self-reported health (bad = 0, general or good = 1).
Mechanism variables
The study integrates mechanism variables, specifically social support and loneliness. Social support is evaluated across three dimensions: the number of friends providing support (categorized as no friends = 0, one or two friends = 1, three friends or above = 2), the degree of emotional support from children (categorized as never support = 0, partly support = 1, full support = 2), and the amount of financial support from children. These dimensions collectively contribute to a comprehensive understanding of the social support network available to older adults in the study. Additionally, loneliness is assessed by using the ULS-6 scale, with scores ranging from 6 to 24. Higher scores on the scale indicate greater loneliness. The ULS-6 scale demonstrates good reliability and internal consistency, making it a suitable tool for assessing loneliness among older adults in rural areas of China [41].
Statistical analysis
In this study, all data analyses and processing were carried out using STATA17.0 software. Firstly, descriptive statistics were employed to characterize the study sample, with continuous variables presented as mean (standard deviation(SD)) and categorical variables expressed as number (percentage). To compare characteristics between older adults in non-empty nester and empty nester, t-tests for continuous variables and Chi-square tests for categorical variables were employed. Secondly, Ordinary Least-Squares (OLS) and logit regression analyses were performed to examine the association between empty nest and cognitive function, with clustering at the township level. Thirdly, to address potential endogeneity issues and ensure robust results, we applied the proportion of empty nesters in the village as an IV. Moreover, to enhance the thoroughness and reliability of our research, particularly to address reverse causality issues, we also conducted supplementary analyses by incorporating lagged dependent variable (LDV) into our models. Leveraging the unique advantages of time-series data, we integrated data from a follow-up survey where older adults self-report their dementia status. Participants were asked, “In the past three months, have you experienced any signs or symptoms of dementia?” Responses of “no” were coded as 0, and responses of “yes” were coded as 1. By combining this follow-up data with our initial baseline data, we calculated the change in cognitive status over time as our dependent variable. Finally, we explored the mechanisms underlying the association between empty nest and cognitive function of older adults and analyzed heterogeneity based on seemingly unrelated regressions. The significance for all tests was set at 0.05.
Results
Descriptive statistics
Table 1 provides descriptive statistics for the 365 participants, including 105 empty nesters. The average age was 70.28 years, with 52.3% being female. Approximately half of the participants were uneducated (48.5%), and more than three-quarters were currently married (78.1%). The majority were employed including farming (76.2%), and 78.1% reported never engaging in exercise. Over half (57.8%) reported having bad health. Statistically insignificant differences were observed between the two groups for most variables, except for family assets, where empty nesters mainly came from families with fewer assets (p < 0.001).
Table 1.
Sample characteristics stratified by empty nest status (N = 365)
| Variables | Non-empty nester | Empty nester | Total | P |
|---|---|---|---|---|
| (n = 260) | (n = 105) | (n = 365) | ||
| Dependent variable | ||||
| Cognitive function score | 19.52 (7.45) | 21.73 (6.11) | 20.16 (7.15) | 0.007† |
| Orientation | 7.45 (2.66) | 8.19 (2.19) | 7.66 (2.55) | 0.012† |
| Registration | 2.25 (1.13) | 2.50 (0.94) | 2.32 (1.08) | 0.038† |
| Attention and Calculation | 2.56 (2.04) | 2.76 (2.04) | 2.62 (2.04) | 0.395† |
| Recall | 1.57 (1.25) | 1.94 (1.11) | 1.68 (1.22) | 0.009† |
| Language and Praxis | 5.52 (1.98) | 6.03 (1.72) | 5.67 (1.92) | 0.023† |
| Cognitive impairment | 0.018 | |||
| No | 138 (53.1) | 70 (66.7) | 208 (57.0) | |
| Yes | 122 (46.9) | 35 (33.3) | 157 (43.0) | |
| Sociodemographic characteristics | ||||
| Age(years) | 70.09 (6.42) | 70.77 (5.69) | 70.28 (6.22) | 0.343† |
| Gender | 0.108 | |||
| Female | 143 (55.0) | 48 (45.7) | 191 (52.3) | |
| Male | 117 (45.0) | 57 (54.3) | 174 (47.7) | |
| Education | 0.652 | |||
| Never go to school | 130 (50.0) | 47 (44.8) | 177 (48.5) | |
| Primary school | 52 (20.0) | 24 (22.8) | 76 (20.8) | |
| Junior high school or above | 78 (30.0) | 34 (32.4) | 112 (30.7) | |
| Family assets a | < 0.001 | |||
| The last half | 103 (39.6) | 84 (80.0) | 187 (51.2) | |
| The first half | 157 (60.4) | 21 (20.0) | 178 (48.8) | |
| Marital status | 0.834 | |||
| Single/Divorced/Widow/Widower | 63 (24.2) | 17 (16.2) | 80 (21.9) | |
| Married | 197 (75.8) | 88 (83.8) | 285 (78.1) | |
| Employment status | 0.172 | |||
| Unemployed | 67 (25.8) | 20 (19.0) | 87 (23.8) | |
| Employed | 193 (74.2) | 85 (81.0) | 278 (76.2) | |
| Exercise | 0.262 | |||
| No | 199 (76.5) | 86 (81.9) | 285 (78.1) | |
| Yes | 61 (23.5) | 19 (18.1) | 80 (21.9) | |
| NRCMS | 0.979 | |||
| No | 11 (4.2) | 5 (4.8) | 16 (4.4) | |
| Yes | 249 (95.8) | 100 (95.2) | 349 (95.6) | |
| Number of chronic diseases | 0.691 | |||
| One disease | 108(41.5) | 46 (43.8) | 154 (42.2) | |
| Two diseases or above | 152 (58.5) | 59 (56.2) | 211(57.8) | |
| Duration of chronic diseases | 17.06(12.67) | 16.21(12.62) | 16.81(12.65) | 0.563† |
| Medical expenses b | 0.256 | |||
| First third | 59(22.7) | 30 (28.6) | 89 (24.4) | |
| Middle third | 86 (33.1) | 38 (36.2) | 124 (34.0) | |
| Last third | 115(44.2) | 37 (35.2) | 152 (41.6) | |
| Self-reported health | 0.071 | |||
| Bad | 158 (60.8) | 53 (50.5) | 211 (57.8) | |
| General or good | 102 (39.2) | 52 (49.5) | 154 (42.2) | |
| Mechanism variables | ||||
| Number of friends c | 0.041 | |||
| No friends | 94 (66.7) | 33 (49.3) | 127 (61.1) | |
| One or two friends | 19 (13.5) | 11 (16.4) | 30 (14.4) | |
| Three friends or above | 28 (19.8) | 23 (34.3) | 51 (24.5) | |
| Emotional support from children c | 0.011 | |||
| Never support | 6 (4.3) | 8 (12.0) | 14 (6.8) | |
| Partly support | 41 (29.1) | 9 (13.4) | 50 (24.0) | |
| Full support | 94 (66.6) | 50 (74.6) | 144 (69.2) | |
| Financial support from children (1000RMB) | 2.14 (4.12) | 3.30 (6.39) | 2.47 (4.90) | 0.041† |
| ULS score c | 10.16 (4.71) | 9.07 (3.66) | 9.81 (4.42) | 0.099† |
Note: Data presented as n (%) or mean (SD). a Family assets were divided into dummy variable by mean. 0 represents family assets index is less than mean, while 1 represents family assets index more than or equal to mean. b Medical expenses are categorized into three groups: first third, middle third and last third. Specifically, first third, middle third and last third represent the top third, middle third, and bottom third of the sample population’s medical expenses, respectively. c These variables have missing values, N = 208. † T-test results for continuous variables. Chi-square test results for categorical variables.
The mean cognitive function score for all participants was 20.16 out of 30, with empty nesters scoring significantly higher than non-empty nesters (p < 0.01). Utilizing the indicator of cognitive impairment, the results revealed a significantly lower prevalence of cognitive impairment in empty nesters (33.3%) than non-empty nesters (46.9%). Besides, across the four dimensions of cognitive function (excluding attention and calculation), empty nesters demonstrated significantly higher scores compared to non-empty nesters (p < 0.05).
The association between empty nest and cognitive function
Table 2 presents the association between empty nest and cognitive function scores of older adults. Regardless of the inclusion of control variables, empty nesters exhibited higher cognitive function scores than non-empty nesters (β = 2.210, p = 0.001; β = 1.757, p = 0.007, respectively). Across the five dimensions of cognitive function, it is observed that, except for registration as well as attention and calculation, empty nesters significantly outperformed non-empty nesters in the domain of orientation (β = 0.560, p = 0.022), recall (β = 0.377, p = 0.006) and language and praxis (β = 0.405, p = 0.025). To ensure the robustness of these findings, cognitive impairment was included as a dependent variable in the analysis, and the results remained consistent. Specifically, non-empty nesters were significantly associated with an increased risk of cognitive impairment (β = -0.658, p = 0.011). Additionally, several control variables were found to be associated with higher cognitive function scores, including being younger, male, more educated, engaging in exercise, and reporting good self-reported health.
Table 2.
The association between empty nest and cognitive function
| Variables | Cognitive function | Orientation | Registration | Attention and calculation | Recall | Language and praxis | Cognitive impairment | ||
|---|---|---|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
| Empty nest | 2.210** | 1.757** | 0.560* | 0.213 | 0.194 | 0.377** | 0.405* | -0.570** | -0.658* |
| (0.661) | (0.630) | (0.241) | (0.122) | (0.229) | (0.134) | (0.178) | (0.217) | (0.260) | |
| Age | -0.234** | -0.082** | -0.016 | -0.034* | -0.040** | -0.041* | 0.079** | ||
| (0.061) | (0.023) | (0.012) | (0.017) | (0.013) | (0.019) | (0.021) | |||
| Gender | 2.143** | 1.209** | 0.039 | 0.345 | -0.127 | 0.437* | -0.841** | ||
| (0.646) | (0.225) | (0.124) | (0.211) | (0.113) | (0.174) | (0.250) | |||
|
Education Never go to school (Reference) |
|||||||||
| Primary school | 4.729** | 1.347** | 0.222 | 1.123** | 0.456** | 1.186** | -0.656* | ||
| (0.707) | (0.255) | (0.153) | (0.269) | (0.158) | (0.226) | (0.285) | |||
| Junior high school or above | 6.002** | 1.545** | 1.569** | 0.332* | 1.623** | 0.503** | -0.302 | ||
| (0.864) | (0.294) | (0.133) | (0.253) | (0.157) | (0.254) | (0.308) | |||
| Family assets | 0.061 | -0.011 | -0.067 | 0.304 | -0.087 | 0.117 | -0.195 | ||
| (0.632) | (0.233) | (0.118) | (0.191) | (0.144) | (0.166) | (0.237) | |||
| Marital status | 0.577 | 0.149 | 0.173 | -0.069 | -0.110 | 0.156 | -0.026 | ||
| (0.943) | (0.334) | (0.162) | (0.286) | (0.162) | (0.269) | (0.293) | |||
| Employment status | 0.116 | 0.086 | -0.103 | -0.076 | -0.279 | 0.200 | 0.116 | ||
| (0.832) | (0.295) | (0.143) | (0.248) | (0.141) | (0.256) | (0.296) | |||
| Exercise | 1.563* | 0.116 | 0.461** | 0.152 | 0.256 | 0.395 | -0.357 | ||
| (0.737) | (0.280) | (0.116) | (0.222) | (0.143) | (0.210) | (0.309) | |||
| NRCMS | 0.455 | -0.070 | 0.319 | -0.208 | 0.481 | 0.027 | -0.187 | ||
| (1.332) | (0.551) | (0.342) | (0.351) | (0.322) | (0.322) | (0.555) | |||
|
Number of chronic diseases One disease (Reference) |
|||||||||
| Two diseases or above | 0.794 | 0.098 | 0.058 | 0.390* | 0.105 | 0.102 | -0.251 | ||
| (0.601) | (0.258) | (0.115) | (0.194) | (0.150) | (0.165) | (0.247) | |||
| Duration of chronic diseases | 0.035 | 0.025* | -0.006 | 0.009 | -0.004 | 0.008 | -0.251 | ||
| (0.026) | (0.011) | (0.005) | (0.009) | (0.005) | (0.007) | (0.247) | |||
| Medical expenses | |||||||||
| First third (Reference) | |||||||||
| Middle third | -1.230 | -0.031 | -0.079 | -0.642* | -0.118 | -0.308 | 0.367 | ||
| (0.788) | (0.307) | (0.124) | (0.262) | (0.177) | (0.206) | (0.295) | |||
| Last third | -0.997 | 0.039 | -0.019 | -0.742* | 0.194 | -0.381 | 0.072 | ||
| (0.905) | (0.325) | (0.165) | (0.285) | (0.193) | (0.231) | (0.331) | |||
| Self-reported health | 1.846* | 0.587 | 0.272* | 0.356 | 0.342* | 0.408 | -0.520 | ||
| (0.860) | (0.331) | (0.119) | (0.219) | (0.140) | (0.223) | (0.331) | |||
| Constant | 19.523** | 29.938** | 11.087** | 2.774** | 4.171** | 3.849** | 6.963** | -0.123 | -4.464* |
| (0.484) | (5.318) | (1.823) | (0.999) | (1.342) | (1.052) | (1.639) | (0.117) | (1.765) | |
| R-squared | 0.020 | 0.373 | 0.298 | 0.136 | 0.227 | 0.165 | 0.323 | 0.012 | 0.117 |
| Observations | 365 | 365 | 365 | 365 | 365 | 365 | 365 | 365 | 365 |
Note: Column (1) and (2) show the regression results without and with control variables using OLS regression. Column (3) to (7) show the results of regressing the different dimensions of cognitive function using OLS regression. Column (8) and (9) show the results of regressing cognitive impairment using logit regression. Cluster effect at the township level; Standard errors in parentheses. *P < 0.05; **P < 0.01
To mitigate potential endogeneity concerns stemming from older adults’ choices to live with their children based on health conditions, introducing potential bias into the regression results, an IV method is implemented. Following existing literature [42], the proportion of empty nesters in the village is employed as the IV. This choice is considered reasonable because the empty nest status of parents may be influenced by the living arrangements of older adults in the same village, while the living arrangements of these fellow villagers do not directly impact the cognitive function of parents. Table 3 displays the two-stage regression results of the IV analysis mainly. The F-test values from the first stage regression were 26.560, exceeding the typical critical value of 10, indicating that weak IV is not a threat to this study. The IV significantly affected the decision of older adults to become empty nesters, with stable and statistically significant estimated coefficients. In the second stage, the IV analysis revealed that empty nesters had significantly higher cognitive function scores than non-empty nesters (β = 3.682, p = 0.034), consistent with our OLS regression (β = 1.757, p = 0.007). Moreover, the IV estimate implies that OLS regression analysis may have underestimated the positive effects of empty nest on the cognitive function of older adults.
Table 3.
Results of the instrumental variable method
| Cognitive function | First stage | Second stage | |
|---|---|---|---|
| (1) | (2) | (3) | |
| Empty nest | 1.757** | - | 3.682* |
| (0.630) | - | (2.12) | |
| IV | 0.400*** | - | |
| (6.35) | - | ||
| Control variables | Yes | Yes | Yes |
| F-statistics | - | 26.560 | - |
| R-squared | 0.373 | 0.225 | 0.334 |
| Observations | 365 | 365 | 365 |
Note: Column (1) showed the results of OLS regression. Column (2) and (3) reported the estimation results for the first and second stages of the instrumental estimation, respectively. We use the empty nester probability of the same village as the instrumental variable; Control variables include age, gender, education, family assets, marital status, employment status, exercise, NRCMS, number of chronic diseases, duration of chronic diseases, medical expenses and self-reported health. Cluster effect at the township level; Standard errors in parentheses. *P < 0.05; **P < 0.01; ***P < 0.001
Furthermore, including the LDV in our models allows us to account for historical influences and unobserved characteristics among older adults [43]. The results of the supplementary analyses using the follow-up survey, presented in Appendix Table 1, are consistent with our primary findings and underscore positive associations between empty nest status and cognitive function.
Mechanisms
Table 4 delves into the mechanisms underlying the relationship by assessing the impact of empty nest status on social support and loneliness. Regarding social support, the results indicated that empty nesters had more friends (p = 0.001), received more emotional care (p = 0.046), and experienced increased financial support from children (p = 0.028). This suggests a positive association between empty nest status and a robust social support network, potentially contributing to higher cognitive function scores. Regarding loneliness, the results showed that the ULS scores of empty nesters were significantly lower than those of non-empty nesters (p = 0.046).
Table 4.
Mechanism analysis of the impact of empty nest on cognitive function
| Social support | Loneliness | |||
|---|---|---|---|---|
| Number of friends | Emotional support from children | Financial support from children (1000RMB) | ULS score | |
| (1) | (2) | (3) | (4) | |
| Empty nest | 1.260** | 0.702* | 1.797* | -1.489* |
| (0.370) | (0.352) | (0.804) | (0.721) | |
| Control variables | Yes | Yes | Yes | Yes |
| Constant | 6.644* | 17.684** | ||
| (3.171) | (5.773) | |||
| R-squared | 0.098 | 0.067 | 0.102 | 0.134 |
| Observations | 208 | 208 | 365 | 208 |
Note: Column (1) and (2) used ordered logit regression. Column (3) and (4) used OLS regression. Control variables include age, gender, education, family assets, marital status, employment status, exercise, NRCMS, number of chronic diseases, duration of chronic diseases, medical expenses and self-reported health. Cluster effect at the township level. Standard errors in parentheses. *P < 0.05; **P < 0.01
Heterogeneity analysis
To understand potential variations in the impact of empty nest based on gender, further exploration was conducted, and the results are presented in Table 5. Within the male group, empty nesters had cognitive function scores 3.209 points higher than non-empty nesters (p = 0.000). This indicates that the impact of empty nest status on cognitive function in male adults is greater than in female adults (p = 0.017).
Table 5.
Heterogeneity analysis of the impact of empty nest on cognitive function
| Female | Male | P | |
|---|---|---|---|
| (1) | (2) | ||
| Empty nest | 0.386 | 3.209*** | 0.017 |
| (1.028) | (0.872) | ||
| Control variables | Yes | Yes | |
| Constant | 42.572*** | 21.617** | |
| (7.229) | (6.540) | ||
| R-squared | 0.399 | 0.287 | |
| Observations | 191 | 174 |
Note: Control variables include age, gender, education, family assets, marital status, employment status, exercise, NRCMS, number of chronic diseases, duration of chronic diseases, medical expenses and self-reported health. Cluster effect at the township level. Standard errors in parentheses. *P <0.05; **P < 0.01; ***P < 0.001
Discussion
Our study, utilizing both multiple regression analyses and IV methods, reveals a positive association between empty nest status and cognitive function among older adults with chronic diseases in rural China. This investigation, to our knowledge, marks the first exploration of the link between empty nest status and cognitive impairment in this population. Specifically, empty nesters exhibited significantly higher cognitive function scores and a lower prevalence of cognitive impairment compared to non-empty nesters. Mechanism analysis suggests that this enhanced cognitive function in empty nesters is associated with heightened support from children and friends, and this positive impact occurs with a significant decrease in loneliness experiences.
In our study, we observed that approximately 43% of older adults with chronic diseases in rural China experienced cognitive impairment. This prevalence exceeded both the rates observed among the general older population within the same rural areas (30%) and those reported in earlier studies focusing on rural older populations in China, which ranged from 20 to 38% [44–46]. Notably, the prevalence of cognitive impairment among the overall older population in our study (30%) closely mirrored findings from other research (20–38%). These results underscore the heightened susceptibility of older adults with chronic diseases to cognitive impairment, as some studies suggested [47]. In the rural sample, nearly 58% of older adults have more than one type of chronic disease, with 34% having three or more chronic diseases, further increasing their vulnerability to cognitive impairment. This susceptibility may be attributed to the interplay of pathological states among multiple chronic diseases, leading to cognitive decline and dementia in the older adult population [48].
Results from both multiple regression, IV and LDV-controlled analyses consistently suggest that empty nest status is significantly associated with cognitive function among older adults with chronic diseases in rural China. Notably, empty nesters in this population demonstrated higher scores in cognitive function. Our findings support the perspective that being an empty nester is not a risk condition of cognitive decline. We found positive associations between empty nest status and cognitive function in older adults [49, 50], particularly for those with chronic diseases. Contrary to traditional notions suggesting that living with adult children provides interaction opportunities and additional care, our research challenges this belief. As previous literature suggested, cohabitating with adult children may not consistently benefit older adults and could potentially lead to intergenerational conflict and negative relationships, offsetting any positive effects or even being harmful to the health of older adults [51]. Importantly, living in an empty nest may lead to increased isolation from family, but it does not necessarily result in greater isolation from friends [52]. Moreover, it may result in receiving more support and attention from one’s spouse [14]. Empty nesters are more likely to have additional time to enjoy life [53], engage in regular social activities [52] and have a lower risk of activities of daily living disability [20] — all contributing to improving their cognitive function, especially from those with chronic diseases.
Mechanism analysis reveals that the positive association between empty nest and cognitive function in older adults may stem from the protective role of social relationships. Our study indicates that empty nesters receive increased social support both from children and friends and their experiences of loneliness are perceived as insufficient, positively impacting cognitive function [25, 34]. This contrasts with some previous research in China, which suggested that being an empty nester was associated with greater social isolation and psychological distress [16]. One potential explanation for our findings is the reduced responsibilities (e.g., household chores, caring for grandchildren) in an empty nest, allowing older adults more freedom and leisure time to cultivate friendships through activities such as exercise or social events [54]. In this process, older adults efficiently expand their friend networks and guard against the onset of loneliness by embracing new experiences and engaging in communication. This aligns with previous findings suggesting that loneliness is not synonymous with objective social isolation, as individuals may be isolated with limited social contacts without feeling lonely [52]. Additionally, the widespread use of communication technology and the emphasis on filial piety in China may enhance family social support for empty nesters, including emotional and financial assistance [55], exerting a positive impact on cognitive development [50, 51]. In the context of chronic diseases, social support plays a crucial role in reducing the morbidity and mortality of older adults [56]. The challenges posed by illness, medication costs, and medical expenses contribute to the economic and psychological burdens on older individuals with chronic conditions [58]. Offering emotional and financial support can improve health outcomes, alleviating these burdens and potentially reducing the risk of non-comorbid patients developing additional health issues [59] This underscores the importance of considering family, friends, and other significant individuals as diverse sources of support in interventions aimed at enhancing the cognitive function of older adults.
Additionally, heterogeneity analysis showed that the impact of empty nest status on cognitive function in male adults is greater than in female adults. On the one hand, the relatively lower socio-economic status of empty-nest women may hinder the development of their cognitive function [57]. On the other hand, due to the traditional division of family labor in China, women are expected to shoulder the responsibility of caring for their spouses, placing them under greater psychological and physical pressure and may impair their health [60]. According to the role strain theory, women may experience more significant stress than men in meeting various demands [61]. Consequently, the benefits and significance provided by an empty nest woman may diminish due to role pressure and strain.
This study has several limitations. Firstly, because our data were cross-sectional, we cannot fully identify causal relationships. Secondly, its focus on older adults in northwest China may limit the generalizability of observed cognitive impairment prevalence to national trends. Thirdly, the evaluation of cognitive function scores and the prevalence of cognitive impairment relied on the MMSE scale, which may have limitations in accurately assessing the true levels of cognitive impairment among older adults. Finally, there might be additional potential mechanisms, such as older adults’ medical behaviors, social activities, and health-related activities, which could be explored in future studies.
Despite these limitations, this study contributes to the literature in two key areas. Firstly, it provides crucial insights into cognitive function among older adults with chronic diseases in developing countries by examining the association between empty nest status and cognitive function in rural China. Focusing on older adults with chronic diseases adds significance, addressing a group deserving of increased attention. Secondly, employing an IV method enhances the study’s prospective nature, reducing the possibility of reverse causation bias.
Conclusions
In summary, our study revealed a positive association between empty nest and cognitive function among older adults with chronic diseases in rural China. Additionally, when comparing empty nesters to non-empty nesters, older adults with chronic conditions in empty nests were more likely to receive social support from children and friends. They also experienced less social loneliness, contributing to the overall benefit of their cognitive function. We recommend implementing interventions that specifically target enhancing social support to mitigate the potential negative effects of empty nest isolation on cognitive function among older adults.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We are grateful to all respondents who participated in this study and the enumerators for data collection efforts.
Abbreviations
- IV
Instrumental variable
- LDV
Lagged dependent variable
- OLS
Ordinary least-squares
- NRCMS
The new rural cooperative medical scheme
Author contributions
QF G, XF W, XT W were responsible for designing the study and the study’s statistical design, supervising the data collection and analysis and revising the manuscript. XF W CY L and XT W reviewed the literature and performed the data analysis and manuscript draft. QF G, A Y and AQ W gave critical feedback and conducted quality control. QF G, XF W, CY L, XT W and R H reviewed the results and revised the manuscript. All authors critically reviewed the article for important intellectual content. The authors read and approved the final manuscript.
Funding
This research was supported by the National Natural Science Foundation of China (Grant No. 72203134; Grant No. 71903149), and the National Social Science Foundation of China (Grant No. 22BGL212).
Data availability
Public availability of data would compromise the privacy of participants. Data will be made available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
The study was approved by “Ethics Committees of Xi’an Jiaotong University in China (2020 − 1239) and Xi’an Gaoxin Hospital in China” (2019-KY005). Verbal informed consent was obtained from all participants.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
Public availability of data would compromise the privacy of participants. Data will be made available from the corresponding author upon reasonable request.