Factors associated with active aging in Chinese elderly in rural areas of Xiangtan County, China†
Article Category: Original article
Data publikacji: 30 gru 2021
Zakres stron: 407 - 417
Otrzymano: 12 kwi 2021
Przyjęty: 20 maj 2021
DOI: https://doi.org/10.2478/fon-2021-0041
Słowa kluczowe
© 2021 Xue-Lian Fu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Aging has become a global trend. By 2050, 22% of the world's population will be over 60 years old, which is an increase from 11% in 2019. With the rapid increase of the aging population, a series of social problems brought about by the older population, such as health concerns and support and nursing for the aged, is already causing a wide social concern. Positive and effective measures to cope with these problems must be taken and prioritized worldwide.
If everyone can achieve a relatively close life expectancy and healthy lifespan and can spend their old age independently, then the problem of aging can be effectively solved. Under the guidance of this concept, the World Health Organization (WHO) introduced the concept of active aging, which is sometimes translated as “positive aging”. Active aging has been defined as “...
The mining and analysis of the influencing factors of active aging can provide a basis for the realization of active aging on a personal level. The WHO has initially formed a model of active aging determinants, including health and social services (health promotion and disease prevention, curative service, long-term care, mental health services), behavioral factors (tobacco use, physical activity, healthy eating, oral health), personal factors (biology and genetics, psychological factors), physical environment (physical environments, safe housing, falls, clean water, clean air, and safe food), social environment (social support, violence and abuse, education, literacy), and economic factors (income, social protection, work), which are embedded in cultural and gender contexts.1 This model has aroused much attention and controversy among scholars.5 Many of the determinants proved to be entwined, reflecting the transaction between individual and environmental factors in shaping adaptation to the aging process.6 Some of these determinants are policy issues that need to be actively addressed by the government, such as the promotion and integration of health and social services and the construction of suitable aging environments. Some factors have been demonstrated by many studies as good, healthy behavior, and the construction of an aging environment will inevitably make active aging easier to achieve.
Gender and age differences affect the active aging situation.7 The younger the elderly, the higher the level of active aging.8,9,10 However, the effect of gender on active aging is controversial.2,11 Regarding physical environment and economic factors, a high level of education,8,9,12,13 good economic condition,8,14 the absence of chronic disease,8,14,15, and abundant family support15 are linked to high active aging levels. However, specific results vary across studies in different populations.
Good daily living ability and the absence of depressive symptoms have also been classified as indicators of active aging.11 Pham et al. found that active aging is positively associated with perceived health, life satisfaction, and quality of life and negatively associated with falls, loneliness, and frailty.16 A 6-factor model (i.e., health, psychological component, cognitive performance, social relationships, bio-behavioral component, and personality) was formed through interviews with 1322 old people living in the community. Findings reinforced the importance of psychological functioning in active aging in the oldest old.6,17 Active aging is strongly consistent with low depressive symptoms.18
However, due to transportation, language, funding, and other obstacles, the research and promotion of active aging are mostly concentrated in urban areas, involving very few in rural areas. Furthermore, inequalities in the development of health care and social services are apparent among Western countries,19 African countries,20, and China.21 The situation of the elderly in rural areas requires more attention.
Therefore, this study aimed to explore the level and factors associated with active aging in rural areas of Xiangtan County, China, and to provide health management suggestions to the health service sector for the rural elderly.
This research involved a cross-sectional and descriptive study conducted in rural areas of Xiangtan County, China.
The research site of this study was located in rural areas of Xiangtan County, Hunan Province, Southeast China. According to the 2018 national economic and social development statistics bulletin, the total number of people in Xiangtan is 2.865 million, of which 0.61 million (21.3%) were aged 60 years and older.22 The average life expectancy of the Xiangtan area is 78.63 years, which is higher than the national and provincial average levels. In summary, aging is a very important and burning social realistic issue in the region.
Considering previous data showing 36.67% satisfaction of rural elderly pension status23 and according to the formula n = (Zα/2)2 ×
Multistage sampling was adopted. First, according to the per capita annual income of farmers, 17 towns in Xiangtan County were divided into 3 levels: good, medium, and poor. In each level, a township was selected by the random number method. Three towns were selected: Shitan Town (2220 USD per year), Fenshui Town (1855 USD per year), and Zhonglupu Town (1609 USD per year). In each town, 3 villages were selected by random number simple sampling. Finally, 9 administrative villages were selected as the source of the survey objects.
Old adults were recruited in the study if they (1) were aged 60 years or over, (2) continuously lived in the local area for >1 year, and (3) were clear-minded and able to communicate effectively. Residents in hospitals or nursing homes were excluded from the survey.
A general information sheet was used to collect demographic and general health data, including gender, age, education, marital status, living arrangement, number of children, subjective economic status, and number of chronic diseases.
The positive aging questionnaire (PAEQ) compiled by Hu Min et al. in 2012 was used to evaluate the active aging level. The questionnaire was developed based on the concept of active aging and its three pillars, with the aim of developing an individual-level instrument for measuring active aging. The overall Cronbach's α coefficient of the questionnaire was 0.914. The overall semi-reliability of the questionnaire was 0.801. The content validity of the questionnaire was analyzed by the expert judgment method, and the Content Validity Index (CVI) was 1. The correlation between each dimension and the total questionnaire ranged from 0.137 to 0.888, and the construct validity was good in Hu's study.24 The overall Cronbach's α coefficient of the questionnaire in this study was 0.862. The assessment includes physical vitality (i.e., the physical activity of the elderly), life satisfaction (i.e., the spiritual and cultural aspects of the elderly and the status of their own life satisfaction), family support (i.e., family members, friends, or social groups to support and help the elderly), and active participation (i.e., the participation of the elderly in social activities and social services) in 4 dimensions. The assessment included 21 items that involved the use of a 5-point scoring method from “completely inconsistent” (1 point) to “fully qualified” (5 points); the median number is 3. Entries with scores of ≤1, ≥2 but <3, ≥3 but <4, and ≥4 indicate low, moderately low, moderately high, and high scores, respectively. The total score may range from 21 to 105 points, with scores of ≤42, >42 but ≤63, >63 but ≤84, and >84 indicating low, medium–low, medium–high, and high levels of active aging, respectively. A high score indicates a high level of active aging.
Activities of daily living were measured using the activity of daily living scale (ADL) developed by Lawton and Brody in 1969.25 It consists of the physical self-maintenance scale and the instrumental activities of daily living scale. The first part includes 6 items, namely, walking, eating, dressing, grooming, bathing, and toilet use. The second part is an instrumental daily living ability scale that consists of 8 items, namely, using transportation, cooking, doing housework, taking medicine, doing laundry, shopping, using of phone, and administration of their economy. Choices for each item were graded “1 = can do it myself,” “2 = have some difficulty doing,” “3 = need help to do it,” and “4 = cannot do it at all”. The total score of ADL represents the different dependence degrees of the elderly: ≤14 indicates the normal ability of daily living, whereas >14 indicates partial limitation of the ability of daily living. The Cronbach's α of ADL was 0.918 in this study.
The depression in old-age scale (DIA-S) was used to measure symptoms of depression. It was compiled by Heidenblut and Zank, designed specifically for the elderly,26 and has been used in Germany and Iran.27,28 The scale included 10 depression-related items that were to be answered with true or false with a yes/no answer format. The scale ranges from 0 (no depressive symptoms) to 10 (maximal number of depressive symptoms). The total maximum score is 10. A cut-off of ≥3 was considered an indication of depressive symptoms. High scores suggest high levels of severe depressive symptoms. Yang Bing et al.29 produced a translated version of the DIA-S in Chinese. The Chinese DIA-S has a total Cronbach's coefficient of 0.829, a split-half reliability of 0.831, a retest reliability of 0.907 and a content validity index (S-CVI/UA) of 0.9. The content validity index (I-CVI) of item level was 0.833–1. The average content validity index (S-CVI/Ave) was 0.983, and the Pearson correlation coefficient between each entry and the total score was 0.475–0.789. The coefficient of the internal consistency of the scale was 0.787 in this study.
After unified training and assessment, 3 investigators entered the home of the elderly in the countryside and conducted face-to-face investigations with the assistance of the staff in each village. Given the common characteristics of poor eyesight and low education of the elderly in rural areas, the survey was conducted in the form of face-to-face interviews, and all data were recorded by investigators. Approximately 20–30 min were taken to complete a questionnaire. After the investigations were concluded, respondents were thanked for their participation and given some incentives, such as a pack of food. The data collectors performed the necessary checking and verification procedures in time after the participants had completed the questionnaire.
Information from the questionnaires was typed into a computer by 2 researchers according to the serial numbers. SPSS 19.0 was used for data analysis. Categorical variables (gender, age, education, marital status, number of children, subjective economic status, and number of chronic diseases) were presented as frequencies and percentages, whereas continuous variables (positive aging level, activities of daily living, and depression symptoms) were expressed as mean ± standard deviation (SD). Self-care dependence and depressive symptoms in the elderly were also measured as percentages. A single sample
Correlations between PAEQ score, ADL, and depressive symptoms were analyzed using Pearson's correlation analysis. Multiple linear regression was used to explore the influential factors affecting the level of active aging of rural elderly. In the study,
A total of 945 rural elderly were investigated, 10 of which stopped answering due to time shortages during the investigation. Finally, 935 valid questionnaires (98.9%) were collected. Among the participants, 477 (51.0%) were males, and 437 (46.8%) participants were aged 60–69 years. Most of the participants had primary education or below (76.8%, n = 718), married and with a living spouse (70.8%, n = 662) and had 2–3 children (68.8%, n = 643). With regard to financial status, 477 (51%) respondents reported that they were in a fair financial status. In terms of health, 511 (54.6%) participants suffered from 2 or more types of chronic diseases, as shown in Table 1.
Characteristics of participants (
| Variables (theoretical ranges) | % | |
|---|---|---|
| Male | 477 | 51.0 |
| Female | 458 | 49.0 |
| 60–69 | 437 | 46.8 |
| 70–79 | 381 | 40.7 |
| ≥80 | 117 | 12.5 |
| Primary school or below | 718 | 76.8 |
| Junior school | 166 | 17.7 |
| High school | 42 | 4.5 |
| College or higher | 9 | 1.0 |
| Married and with a living spouse | 662 | 70.8 |
| Single or widowed | 266 | 28.5 |
| Divorced or separated | 7 | 0.7 |
| 0 | 40 | 4.3 |
| 1 | 94 | 10.0 |
| 2–3 | 643 | 68.8 |
| ≥3 | 158 | 16.9 |
| Poor | 318 | 34.0 |
| Fair | 477 | 51.0 |
| Good | 140 | 15.0 |
| 0 | 194 | 20.8 |
| 1 | 230 | 24.6 |
| 2–3 | 362 | 38.7 |
| ≥3 | 149 | 15.9 |
The results showed that 44.7% (n = 418) of the elderly suffered from impaired activity of daily living. A higher number of older adults were impaired in instrumental daily living (n = 412, 44.1%) than in self-maintenance ability (n = 177, 18.9%), as shown in Table 2.
ADL of participants (
| Dimensions (Score ranges) | % | |
|---|---|---|
| Independent (=6) | 758 | 81.1 |
| Dependent (>6) | 177 | 18.9 |
| Independent (=8) | 523 | 55.9 |
| Dependent (>8) | 412 | 44.1 |
| Independent (=14) | 517 | 55.3 |
| Dependent (>14) | 418 | 44.7 |
Of those surveyed, 19.7% (n = 184) reported symptoms of depression. Furthermore, 29.5% (n = 276) of older people found difficulty in relaxing, whereas 23.2% (n = 217) recently (nearly 2 weeks) felt spiritless (Table 3).
Selection of items for symptoms of depression (
| Items | % | ||
|---|---|---|---|
| 1. I’ve been feeling down lately. | 217 | 23.2 | |
| 2. I’m worried about saying or doing something wrong. | 50 | 5.3 | |
| 3. It's hard for me to relax. | 276 | 29.5 | |
| 4. My life seems meaningless. | 59 | 6.3 | |
| 5. I have a hard time motivating myself. | 147 | 15.7 | |
| 6. I’m worried about my future. | 167 | 17.9 | |
| 7. When things get tough, I find it hard to continue to enjoy life. | 157 | 16.8 | |
| 8. Difficulties often overwhelm me. | 76 | 8.1 | |
| 9. I’m often immersed in anxiety. | 124 | 13.3 | |
| 10. I’m not very satisfied with my life. | 104 | 11.1 | |
| Depressive symptom | Depression | 184 | 19.7 |
| No depression | 751 | 80.3 | |
A descriptive analysis of active aging is presented in Table 4. The average score of active aging among the rural elderly was 72.81, which belongs to the medium upper level.
Mean scores of dimensions of PAEQ and comparison (
| Dimensions | Items | Mean scores of each item | Scores from Cao's study12 | ||
|---|---|---|---|---|---|
| Physical vitality | 6 | 3.28 ± 0.98 | 3.78 ± 0.62 | −15.660 | <0.001 |
| Life satisfaction | 7 | 3.70 ± 0.78 | 3.85 ± 0.48 | −5.790 | <0.001 |
| Family support | 3 | 4.40 ± 0.94 | 3.34 ± 0.83 | 34.392 | <0.001 |
| Active participation | 5 | 2.81 ± 0.95 | 3.58 ± 0.75 | −24.980 | <0.001 |
| Total of PAEQ | 21 | 72.81 ± 13.63* | 77.60 ± 11.59* | −10.744 | <0.001 |
=Total average;
PAEQ, positive aging evaluation questionnaire.
The mean scores of the 4 dimensions (physical vitality, life satisfaction, family support, and active participation) of PAEQ were 3.28 (SD = 0.98, scale range 1–5), 3.70 (SD = 0.78, scale range 1–5), 4.40 (SD = 0.94, scale range 1–5), and 2.81 (SD = 0.95, scale range 1–5), respectively. The total score and dimensions of life satisfaction and physical vitality were significantly lower than those in Cao's findings12 (
The results of the correlation analysis among the independent variables and active aging are summarized in Table 5. Significant differences in active aging were found for gender (
Factors associated with active aging.
| Variables | PAEQ mean scores | ||
|---|---|---|---|
| Male | 73.86 ± 14.36 | 2.404 | 0.016 |
| Female | 71.72 ± 12.76 | ||
| 60–69 | 73.12 ± 13.52 | 1.175 | 0.309 |
| 70–79 | 73.00 ± 13.88 | ||
| ≥80 | 71.01 ± 13.23 | ||
| Primary school or below | 71.34 ± 13.30 | 15.348 | <0.001 |
| Junior school | 76.28 ± 13.29 | ||
| High school | 81.79 ± 14.44 | ||
| College or higher | 84.56 ± 10.42 | ||
| Married and with spouse alive (A) | 74.21 ± 13.246 | 13.687 | <0.001 |
| Single or widowed (B) | 69.65 ± 13.989 | ||
| Divorced or separated (C) | 60.86 ± 11.639 | ||
| A vs. B | <0.001 | ||
| A vs. C | 0.009 | ||
| B vs. C | 0.088 | ||
| 0 | 61.50 ± 15.74 | 11.484 | <0.001 |
| 1 | 73.23 ± 15.17 | ||
| 2–3 | 73.84 ± 13.34 | ||
| ≥3 | 71.25 ± 11.87 | ||
| Poor | 66.76 ± 13.29 | 73.227 | <0.001 |
| Fair | 74.25 ± 12.38 | ||
| Good | 81.66 ± 12.35 | ||
| 0 | 81.28 ± 11.728 | 61.257 | <0.001 |
| 1 | 74.82 ± 12.83 | ||
| 2–3 | 70.71 ± 12.76 | ||
| ≥3 | 63.77 ± 12.19 | ||
In addition, we analyzed the correlation between active aging and activities of daily living and found a moderate negative correlation (
Correlation analysis for ADL, DIS-A, and PAEQ (N = 935).
| Dimensions | Physical self-maintenance | Instrumental activities | ADL | DIA-S |
|---|---|---|---|---|
| Physical vitality | −0.314** | −0.369** | −0.370** | −0.378** |
| Life satisfaction | −0.181** | −0.283** | −0.264** | −0.603** |
| Family support | −0.017 | −0.066* | −0.050** | −0.188** |
| Active participation | −0.179** | −0.260** | −0.244** | −0.147** |
| Total of PAEQ | −2.74** | −0.377** | −0.361** | −0.495** |
Multiple linear regression models were constructed to evaluate the factors which affect active aging. In the model, total PAEQ score was the dependent variable, whereas gender, education, marital status, number of children, total score of ADL, subjective economic status, depression, and number of chronic diseases were the independent variables. The results showed that depressive symptoms (β = −0.321,
Regression analysis of active ageing (N = 935).
| Independent variables | β | 95%CI | ||||
|---|---|---|---|---|---|---|
| LL | UL | |||||
| Number of chronic diseases | 0 = 1 | −0.281 | −4.526 | −3.205 | −11.486 | <0.001 |
| 1 = 2 | ||||||
| 2–3 = 3 | ||||||
| ≥3 = 4 | ||||||
| Depression symptom | Ture score | −0.321 | −2.413 | −1.763 | −12.612 | <0.001 |
| Subjective economic status | Poor = 1 | 0.239 | 3.863 | 5.806 | 9.769 | <0.001 |
| Fair = 2 | ||||||
| Good = 3 | ||||||
| Total score of ADL | Ture score | −0.198 | −0.618 | −0.372 | −7.923 | <0.001 |
| Education | Primary school or | 0.126 | 1.786 | 3.954 | 5.195 | <0.001 |
| below = 1 | ||||||
| Junior school = 2 | ||||||
| High school = 3 | ||||||
| College or higher = 4 | ||||||
| Number of children | 0 = 1 | 0.097 | 1.011 | 2.969 | 3.989 | <0.001 |
| 1 = 2 | ||||||
| 2–3 = 3 | ||||||
| ≥3 = 4 | ||||||
| Marital status | Married (control group) | |||||
| Divorced or separated | −0.060 | −16.975 | −2.084 | −2.512 | 0.0120 | |
| Single or widowed | −0.102 | −4.501 | −1.654 | −4.242 | <0.001 | |
| 0.486 | ||||||
| Adjusted |
0.481 | |||||
| 109.309 | ||||||
In this study, the average score of active aging of rural elderly is 72.81, which belongs to the upper–middle level. The results of this study are similar to those of Jiang's.14 This result is closely related to the implementation of the rural medical insurance system, endowment insurance system, social relief system, and other security systems since the founding of new China, which had greatly improved the living standards of the elderly in rural areas.30 However, compared with the elderly in urban communities,12 the rural elderly showed a relatively low level of activity, especially in the two dimensions of physical vitality and life satisfaction (Table 4). Due to the limitations of rural medical conditions and the generally low level of education of the elderly, rural elderly have lower life satisfaction, self-care ability, and cognitive ability than urban elderly.31,32,33,34 In the national level, the local financial and health allocation in rural areas is only 53.98% of that in cities.35,36 Therefore, the allocation of rural health institutions, beds, and health technicians is relatively small.35 The quality of life of the elderly in rural areas needs further attention and improvement. Health and social service systems in rural areas need to be further strengthened.
Symptoms of depression showed great relevance to active aging in the present study, which is consistent with previous findings.17 A good mental state may contribute to more positive attitudes toward health, facilitate functionality and enable the elderly to better integrate themselves.6 The prevalence rate of depression among those aged >60 years is in the range of 11–57%.37 Moreover, the proportion of untreated depressed patients in rural areas is very high – double that in cities.38 According to the biological–psychological–social medical model,39 health personnel should pay attention not only to the physical diseases of the elderly but also to their psychological problems. In the government's free medical examination program for the elderly, the focus is on the assessment and examination of physiological disease. Psychological problems are ignored. As a result, mental disorders are likely under-recognized and under-treated. This situation suggests that psychological problems should be taken into account when providing health services for the elderly in rural areas.
The number of chronic diseases and ADL are also predictors of active aging. In our study, 79.3% of the elderly had one or more chronic diseases. This result may be related to the low awareness of disease prevention among the elderly in rural areas. At the same time, it is related to the narrow scope of rural primary health services. Rural primary medical care mostly focuses on the treatment of diseases. However, the publicity of knowledge on disease prevention is relatively little. Furthermore, guidance on the rehabilitation of chronic diseases is minimal. Chronic diseases seriously affect people's quality of life due to high morbidity, disability, mortality, and high medical expenses.40,41,42. As chronic diseases cannot be prevented and controlled, the ability of daily life is impaired. In the study, the incidence of elderly people with impaired instrumental daily life ability is relatively high, especially in the use of public vehicles and mobile phones, which may be related to inconvenient rural transportation and underdeveloped information technology. Health is an important pillar of the concept of active aging.1 The unhealthy state of the body caused by chronic diseases and the inability to participate in society caused by impaired daily life ability have greatly reduced the active aging level of the elderly in rural areas.
Subjective economic status, education level, marital status, and number of children have certain effects on active aging. This result is consistent with that of a South Korean study.16 The self-perception of good economic conditions not only brings self-esteem to the elderly but also makes the elderly more likely to spend money on high-quality food, medical care, and social activities.43 Thus, older people can better protect their health, maintain self-esteem at a higher level, and adopt a more positive attitude toward life. A prior study also found that active aging is higher in elderly people with a higher education level.44 Elderly people with high education levels in rural areas usually have fixed jobs, retirement pension, wide social contact, and more opportunities to participate in social activities. In addition, their information literacy is also high, and they can effectively access a variety of health resources to ensure their own health.45 The arrival of information society makes the realization of active aging inseparable from network technology. The establishment and implementation of information and communication technology training for the elderly can improve the satisfaction and quality of life of participants.46
Respondents who have no children, no spouse, and are living with collateral relatives are also the key objects to which medical workers should pay attention. Socio-emotional selectivity theory maintains the focus of older people's social interactions on family relationships to enhance their positive experiences.47 Influenced by traditional Chinese concepts, the rural elderly put most of their energy into the care of their families, and their emotional support mainly comes from their families. Due to their relatively closed social contacts, rural elderly have higher family needs than urban elderly.48 Spouses, children, and other immediate family members are an important source of affection.
Notably, gender and age are not included in the model of influencing factor analysis. No statistical difference was found in the level of active aging between the elderly and the young (Table 5), which is inconsistent with our conventional view. The possible explanations are as follows: (1) since the concept of equality between men and women is deeply rooted in the hearts of the people, elderly women's awareness of participation and health care has gradually improved; and (2) some elderly people were not included in our survey because they could not communicate well for various reasons. This requires further research and exploration.
The influencing factors of active aging were discussed to realize the active aging of the rural elderly at the personal level, and the direction of further efforts was defined to meet the following objectives: (1) increase the construction of the rural environment suitable for the elderly so that the rural elderly have more places for sports and fitness and to provide basic facilities for their physical health; (2) strengthen the mental and physical disease prevention propaganda of prevention and disease screening; (3) provide different security conditions according to different physical conditions of rural elderly in different areas; for example; for the elderly with poor physical condition, the government needs to adopt different forms of old-age support to ensure their dignified life; (4) create opportunities to solve the employment problem of young rural people, help rural entrepreneurs, and encourage more young people be with their parents, which can greatly reduce the labor burden of the rural elderly, enhance emotional exchange between generations, and reduce the occurrence of depression; and (5) facilitate the elderly to engage in literacy activities, not only in writing but also in the application of electronic products. If possible, skills or knowledge training can be carried out for the elderly according to their own conditions.
Active aging is rooted in healthy life and behavior in the pre-old-age period. Attention to active and healthy aging needs to be focused on middle- and young-aged populations.49 Chronic diseases, depression, economic status, and education level are not just immediately acquired by the elderly but are accumulated in the young. Therefore, from another aspect, attention should also be paid to the physical health status of the young and middle-aged populations in rural areas to promote the active aging of the elderly in rural areas in the future.
The study provides a profile of active aging among Chinese rural elders in Xiangtan County. The active aging of the elderly in China's rural areas in Xiangtan County is at a medium–upper level but lower than that of the urban elderly. The regression model indicates that depressive symptoms, ADL, number of chronic diseases, subjective economic status, and education are the most important predictors of active aging. The focus group of active aging in rural areas should be elderly people suffering from chronic diseases, physical decline, poor education and economic conditions, child-lessness, and who have no partner. These results suggest some tentative recommendations for the elders, primary health personnel, and departments. A more rigorous longitudinal design is necessary to investigate the causality of the related factors and active aging.
In this study, the active aging questionnaire was used to investigate the active aging status of the elderly in rural areas at the personal level, and relevant information on the status quo and influencing factors of the elderly in rural areas was provided. The results provided not only suggestions for the elderly in rural areas to achieve active aging and improve the quality of life but also direction on the elderly work of primary health workers. The research also provides a certain reference value for the implementation of an active aging policy for the rural elderly.
We affirm that the study has certain limitations. First, the research object only consisted of 9 villages and towns in Xiangtan County, and the results can only have a certain reference value. Second, because it is only a cross-sectional survey, the causal relationship between various influencing factors and active aging is difficult to explain.