Analysis of factors influencing age and cognitive function in older adults: a cross-sectional study

doi:10.21203/rs.3.rs-4835000/v1

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Analysis of factors influencing age and cognitive function in older adults: a cross-sectional study

https://doi.org/10.21203/rs.3.rs-4835000/v1

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Background Cognitive impairment in the elderly continues to be a serious problem, and existing studies have mostly focused on the elderly as a whole and used multiple linear regression to study the influencing factors, without subdividing them by age, which is a limitation that does not allow us to propose targeted strategies. Therefore, the decision tree and multiple linear regression model were jointly applied in this study to study the cognitive function status and influencing factors of elderly people in different age groups, with other age groups as the research subjects.

Methods Data from the China Health and Aging Tracking Survey (CHARLS) 2020 were used to select older adults aged 60-89 as the study subjects, and SPSS 26.0 was used to analyze the data. The factors affecting cognitive function in older adults of different ages were analyzed using the one-way analysis, linear regression model, and decision tree model.

Results High level of education, good memory status, and living in towns and cities were protective factors for cognitive function in older adults of all ages. Depression and unsocialization were risk factors for cognitive function in 60-79-year-olds, but not in 80-89-year-olds.Women as a protective factor for cognitive function in 60-69-year-olds, but not in 70-89-year-olds. Disability was a risk factor for cognitive function in 70-79-year-olds, not a factor influencing cognitive function in 60-69 and 80-89-year-olds. Low life satisfaction and lack of pension insurance were risk factors for cognitive function in 80- to 89-year-olds, but not in 60- to 79-year-olds.

Conclusion The cognitive condition of older adults deteriorates with age, and there are commonalities and differences in the effects of various factors on the cognitive function of older adults in different age groups. In practice, individualized intervention models should be developed for different age groups to reduce the incidence of cognitive dysfunction in various age groups.

cognitive function

cognitive impairment

cross-sectional study

China has the largest number of dementia patients, accounting for about 25% of the world's patients^[1].In 2021, data from the China Association of Aging's Report on the Current Situation and Development of Cognitive Care Services for the Elderly showed that there are more than 15 million dementia patients aged 60 and above in China, and the number of patients will reach 22.2 million in 2030, which is a huge number of patients with dementia and creates great psychological pressure on the patients, as well as increases the pressure of family care and social and economic burden^[2]. Among them, patients with cognitive impairment are considered to be a high-risk group for dementia and are about 5 to 10 times more likely to convert to Alzheimer's disease (AD) in healthy older adults^[3]. Dementia is progressive and irreversible, and there is currently no effective treatment. Existing research suggests that if risk factors for cognitive function were reduced by 10–25%, the number of patients with cognitive dysfunction could be reduced by 1.1 to 3 million worldwide. The General Office of the National Health and Wellness Commission's Circular on the Prevention and Promotion of Alzheimer's Prevention and Treatment (2023–2025) states that regions with the conditions to carry out screening and intervention of old cognitive function for the elderly, to realize early screening, early detection, and early intervention. Recognition and intervention of cognitive impairment is a “family matter” as well as a “national matter”, which involves the immediate interests of hundreds of millions of people, is a major livelihood project, and is also an issue of the times that must be faced. Therefore, it is important to explore the factors affecting cognitive function and to identify and intervene early to improve cognitive function, reduce the incidence of cognitive impairment, and reduce the risk of dementia in the elderly.

Existing studies on the factors affecting cognitive function have mostly focused on all older adults without subdividing them by age^[4], which is one of the most important variables affecting changes in various physiological and psychological functions of older adults, and treating older adults as a homogeneous group ignores the differences among older groups^[5], while older adults of different ages may have different life experiences and may have differences in their physical conditions, disease progression, and factors affecting them^[6–7]. Therefore, by subdividing the elderly according to age into three levels, namely, the lower-age elderly (60–69), the middle-aged elderly (70–79), and the higher-age elderly (80–89), we can explore the factors affecting the cognitive function of the elderly in different age groups at a deeper level, which is conducive to the development of more targeted intervention strategies and related policies for the elderly of different age groups. Moreover, most of the existing studies use multiple linear regression to study the influencing factors. Multiple linear regression can quantify the relationship between the influencing factors and the dependent variable, but due to its limitation, it can not put forward targeted countermeasures and suggestions, while the decision tree model can reflect the importance of the influencing factors through the dendrogram by dividing the subgroups with different characteristics, which is conducive to putting forward targeted countermeasures and suggestions for different groups of people. Therefore, the present study jointly utilizes these two models to investigate the cognitive function status of the elderly in different age groups, investigate the influencing factors of each age group, intervene early in controllable conditions, guide the avoidance of risk factors, prevent or even reducing the incidence of cognitive dysfunction in different age groups, improving the quality of life of the elderly, and reducing the burden on the society. We will truly “serve the elderly” and “prepare for the elderly”, realize active and healthy aging, and draw a new picture of healthy aging in Chinese style.

2.1 Sources of information

This study uses data from the China Health and Aging Tracking Survey (CHARLS) 2020, hosted by the National Institute of Development Studies at Peking University, which covers 150 countries/districts and 450 villages/urban communities across China^[8]. The 2020 survey covered a total of 19,395 cases of middle-aged and elderly people aged 45 and above, with high data validity predictive value, and high representativeness. According to the relevant variable indicators selected in this study, 5973 cases of study subjects were finally included.

Inclusion criteria: 1) Age 60-89 years old. 2) Those who answered the questionnaire information on the Cognitive Functioning Scale and general demographic characteristics such as age completely. 3) Those who were able to answer the study questionnaires on their own or with the help of a caregiver. Exclusion criteria: 1) Those who were missing key information on the study variables. 2) Those who refused to participate in this survey. 3) Those who were not age-appropriate. The sample inclusion process is shown in Figure 1.

The study applied to the CHARLS project team for authorization to use the data and was approved by the Ethics Review Board of Peking University (No. IRB00001052-11015)^[9].

2.2 Measurement of variables

2.2.1 Depression

Referring to the CESD-10 scale scoring criteria, the statistical index of CESD-10 is the total score, which is a composite of 10 individual scores, with a total score of <10 as no depression, otherwise depression^[10].

2.2.2 Disability

The ADL scale was used, which consists of six activities, and “no difficulty” and “difficulty but still able to complete” in the questionnaire were referred to as being able to take care of oneself. In the questionnaire, “have difficulty and need help” and “cannot complete” are called unable to take care of themselves. A person who can take care of himself/herself in all of the indicators is considered to be fully capable, while a person who cannot take care of himself/herself in any of the indicators is considered to be incapable^[11].

2.2.3 Cognitive assessment

Cognitive function was assessed using the Chinese version of the Modified Mental State Examination (MMSE), which tests curing ability and variable ability by evaluating situational memory capacity, and mental state co-equalization, with scores ranging from 0 to 31, and the higher the score the better the cognitive function^[12-13].

2.2.4 Control variables

This includes socio-demographic variables, physical and mental health status, socio-economic characteristics, and poor lifestyle habits. See Table 1 for a description of each specific variable and assignment of values.

2.3 Statistical analysis

SPSS 26.0 was applied for statistical analysis of data. Comparison of differences between groups was described by M(P₂₅, P₇₅), and non-parametric Mann-Whitney U test or Kruskal-Wallis H test was used. The CHAID algorithm in the decision tree was utilized for analysis, setting the minimum number of cases in the parent node of the decision tree to 50 and the minimum number of cases in the child nodes to 10. According to the variables screened by the decision tree results to establish the corresponding regression model and test the interaction term, the cognitive scores of the elderly are continuous variables, the least squares method applicable to multiple linear regression is used for the construction of the model and quantitative analysis, the correlation analysis uses Spearman correlation coefficients and variance inflation factors, and the regression analysis is conducted using a linear regression model with a two-sided test, the level of test a = 0.05 The model equations are as follows:

3.1 Basic information

A total of 5973 study participants were included in this study, 3365 (56.3%) were males 2608 (43.7%) were females, 3209 (53.7%) were 60-69-year-olds, 2246 (37.6%) were 70-79-year-olds, and 518 (8.7%) were 80-89-year-olds.

3.2 Univariate analysis of factors influencing cognitive functioning

3.2.1 Analysis of differences in demographic characteristics on cognitive functioning among older adults of different ages

The analysis of differences in cognitive ability due to demographic characteristics showed that age, place of residence, marriage, education, and socialization were statistically significantly associated with cognitive function in the 60-69-year-old age group (P<0.05). There is a statistically significant (P<0.05) difference between current residence, gender, marriage, education, socialization, and cognitive function in the 70-79-year-old age group. Statistical significance exists between current residence, living arrangement, education, socialization, and cognitive function in the 80-89-year-old age group (P<0.05). The details are analyzed in Table 2.

3.2.2 Analysis of differences in physical and mental health status on cognitive functioning among older adults of different ages

The analysis of the differences produced by physical and mental health conditions on cognitive ability showed that the differences in sleep, exercise, incapacitation, depression, health conditions, memory, and life satisfaction were statistically significant (P<0.05) concerning cognitive functioning in the 60-69-year-old age group. Differences in sleep, exercise, incapacitation, depression, hypertension, health status, hearing, memory, and life satisfaction were statistically significant (P<0.05) with cognitive function in the 70-79-year-old age group. Exercise, incapacity, depression, fall, vision, memory, and life satisfaction differences were statistically significant (P<0.05) with the cognitive function of the 80-89 years old age group. The details are analyzed in Table 3.

3.2.3 Analysis of differences in socio-economic characteristics on cognitive functioning among older adults of different ages

The analysis of the differences in cognitive ability produced by socioeconomic characteristics shows that the difference in health insurance is statistically significant (P<0.05) with the cognitive function of the 70-79-year-old group. The difference between pension insurance and medical insurance is statistically significant (P<0.05) with the cognitive function of the elderly group aged 80-89 years. The specific situation is analyzed in Table 4.

3.2.4 Analysis of the differences in adverse lifestyle habits on the cognitive function of older adults of different ages

The analysis of the differences in cognitive ability produced by adverse lifestyle habits showed that the differences in smoking and alcohol consumption were statistically significant (P<0.05) to the cognitive function of the 60-69-year-old age group. The difference in alcohol consumption was statistically significant (P<0.05) with the cognitive function of the 70-79-year-old age group. The details are analyzed in Table 5.

3.3 Decision Tree CHAID Algorithm Analysis of Factors Influencing Cognitive Functions of Elderly People of Different Ages

3.3.1 Decision Tree CHAID Algorithm Analysis of Factors Influencing Cognitive Function in 60-69-Year-Olds

As can be seen in Figure 2, the first stratum is education, indicating that the level of education is the most important factor influencing the cognitive function of 60-69-year-olds. The highest correlation between memory status and cognitive functioning was found among older adults with a middle school education or less. The highest correlation between current residence and cognitive functioning was found among older adults with high school education and above. The effects of depression and gender on cognitive functioning in older adults were mainly found in those with an education level of elementary school and below, where depression was predominantly manifested in a memory status of fair, good, and very good, and gender was predominantly manifested in a memory status of excellent and bad. The effect of socialization on cognitive functioning in the elderly is mainly shown in the level of education as illiterate and mainly in the memory status as bad and good. The effects of hypertension and depression on cognitive functioning in the elderly were mainly in the education level of middle school, where depression was mainly shown in the memory status of bad, and hypertension was mainly shown in the memory status of fair and excellent. The effect of gender on the cognitive functioning of the elderly is mainly manifested in those with an education level of high school and above, and whose gender is predominantly expressed in the towns in which they currently reside. Cognitive scores for 60-69-year-olds were lowest among those with illiteracy, good and bad memory status, and no socialization, and highest among females with high school education and above and living in towns.

3.3.2 Decision Tree CHAID Algorithm Analysis of Factors Influencing Cognitive Function in 70-79-Year-Olds

As can be seen in Figure 3, the first stratum is education, indicating that the level of education is the most important factor influencing the cognitive function of 70-79-year-olds. The highest correlation between disabling status and cognitive functioning was found among older adults with an illiterate level of education, the highest correlation between depressive status and cognitive functioning was found among older adults with elementary school education or less, the highest correlation between current place of residence status and cognitive functioning was found among older adults with junior high school education, and the highest correlation between socialization status and cognitive functioning was found among older adults with high school education or more. The effects of depression on cognitive functioning in the elderly were mainly in the level of education as illiterate and depression was mainly manifested in the undisabled. The effects of memory status and current residence on cognitive functioning in older adults were mainly found in those with an education level of elementary school and below, where memory status was mainly manifested in depression, and current residence was mainly manifested in the absence of depression. The effects of memory status and smoking on cognitive functioning in the elderly were mainly found in the middle school level of education, where memory status was mainly found in the rural areas of current residence, and smoking was mainly found in the towns and special areas of current residence. The effects of place of current residence and depression on cognitive functioning in older adults were mainly found in education levels of high school and above, where the place of current residence was mainly shown in the presence of socialization and depression was mainly shown in the absence of socialization. Cognitive scores for 70-79-year-olds were lowest among those with illiteracy and disability as their education level, and highest among those with high school education and above, who were socialized and lived in towns and cities.

3.3.3 Decision Tree CHAID Algorithm Analysis of Factors Influencing Cognitive Function in 80-89-Year-Olds

As can be seen in Figure 4, the first stratum is education, indicating that the level of education is the most important factor influencing the cognitive function of 80-89-year-olds. Social status had the highest correlation with cognitive functioning among older adults with an illiterate level of education, current residence had the highest correlation with cognitive functioning among older adults with elementary school education or less, and gender had the highest correlation with cognitive functioning among older adults with junior high school education or more. The influence of memory status and life satisfaction on the cognitive function of the elderly was mainly found in the case of primary education and below, where memory status was mainly found in the case of current residence in the countryside, and life satisfaction was mainly found in the case of current residence in the towns. The effects of pension insurance and education on the cognitive functioning of the elderly are mainly found at an education level of junior high school and above, where pension insurance is mainly manifested among men and education is mainly manifested among women. Cognitive scores for 80- to 89-year-olds were lowest among unsocialized older adults with an illiterate education and highest among older women with a high school education or higher.

3.4 Regression analysis of factors influencing cognitive function in older adults of different ages

3.4.1 Regression analysis of factors influencing cognitive function in 60-69-year-olds

As shown in Table 6, demographic characteristics of high education and female had a positive effect on the cognitive functioning of older adults (P<0.05), living in the countryside and having no socialization hurt the cognitive functioning of older adults (P<0.05), the physical and mental health status of no depression had a positive effect on cognitive functioning of older adults (P<0.05), and low self-assessment score of memory hurt cognitive functioning of older adults (P< 0.05). Among them, the greatest influence on the cognitive status of 60-69-year-olds is the level of education, with each unit increase in education increasing the cognitive status of older adults by 0.369 points, followed by depression, with older adults without depression having a higher cognitive status than older adults suffering from depression by 0.089 points, and the least influence on the cognitive status of 60-69-year-olds is gender, with females having a higher cognitive status than males by an average of 0.049 points. The specific degree of influence of changes in each factor on the cognitive function of the elderly is shown in Figure 5.

3.4.2 Regression analysis of factors influencing cognitive function in 70-79-year-olds

As shown in Table 7, demographic characteristics of the high level of education had a positive effect on the cognitive functioning of older adults (P<0.05), living in the countryside and having no socialization hurt the cognitive functioning of older adults (P<0.05), the physical and mental health status of no depression and no incapacitation had a positive effect on cognitive functioning of older adults (P<0.05), and a low self-assessment score of memory hurt cognitive functioning of older adults (P <0.05). Among them, the greatest influence on the cognitive status of 70-79-year-olds is the level of education, with the cognitive status of older people increasing by 0.35 points for every unit of increase in education, followed by the place of current residence, with older people living in the countryside having a lower cognitive status by 0.14 points than older people living in towns and cities. The least significant effect on the cognitive status of older adults aged 70-79 years was incapacitation, with older adults without incapacitation having a higher cognitive status by 0.052 points than older adults with incapacitation. The specific degree of influence of changes in each factor on the cognitive function of the elderly is shown in Figure 5.

3.4.3 Regression analysis of factors influencing cognitive function in 80-89-year-olds

As shown in Table 8, demographic characteristics of high education level had a positive effect on cognitive functioning of the elderly (P<0.05), living in the countryside hurt cognitive functioning of the elderly (P<0.05), and physical and mental health status of low self-assessment of memory scores, low satisfaction with life, and no pension insurance hurt cognitive functioning of the elderly (P<0.05). Among them, the level of education has the greatest impact on the cognitive status of the elderly aged 80-89, with the cognitive status of the elderly increasing by 0.286 points for every unit increase in the level of education, followed by the place of current residence, with the cognitive status of the elderly living in the countryside decreasing by 0.14 points compared to the cognitive status of the elderly living in the towns. The least influence on the cognitive status of the elderly aged 80-89 years is pension insurance, and the cognitive status of the elderly without pension insurance is 0.081 points lower than that of the elderly with pension insurance. The specific degree of influence of changes in each factor on the cognitive function of the elderly is shown in Figure 5.

The results of this study show that the state of cognitive functioning deteriorates with age, i.e., cognitive aging, which is consistent with the results of several related studies^[14]. Therefore, it is particularly important to provide early primary screening and intervention to slow down and control the onset and progression of cognitive dysfunction in younger older adults. In response to cognitive aging, the 2020 Notice of the General Office of the National Health and Health Commission on Exploring the Work of Carrying Out Specialized Services for the Prevention and Treatment of Depression and Dementia, and the 2023 Notice of the General Office of the National Health and Health Commission on Carrying Out Dementia Prevention and Treatment Promotion Actions (2023–2025) both state that conditional areas should carry out the following activities for elderly people over 65 years old cognitive function screening and early intervention to realize early screening, early detection and early intervention. Some studies have shown that the incidence and prevalence of dementia increase exponentially after the age of 65, with the incidence of dementia approximately doubling every 6.3 years of age^[15]. The World Health Organization defines the lower limit of the age standard for the elderly as 60 years old, indicating that after 60 years of age, all the functions of human beings continue to decline and begin to enter the stage of old age, and the 2022 National Bulletin on the Development of the Elderly Career shows that the national population of the elderly aged 60 years and above is 280 million, and the population of the elderly aged 60–65 years old amounts to 0.7 billion, accounting for 4.9% of the total population. Therefore, advancing the age of early screening and intervention to 60 years old, conducting early screening and intervention in the low old age period, which has a huge population size, and avoiding risk factors are conducive to reducing the risk of cognitive decline and the exponential increase in the prevalence of cognitive disorders in the middle-aged and high-aged old age period, as well as the transformation rate of dementia, which is more conducive to improving the quality of life of the elderly, and enhancing the quality of life.

Higher education is a protective factor for cognitive function in older adults of all ages, i.e., there is a positive and increasing relationship between education and cognitive scores of older adults of all ages, which may be related to the fact that people with more years of education have higher cognitive reserves and more developed neuronal networks^[16], and their cognitive function will persist longer with age, which is conducive to the protection of cognitive function and slowing down the process of development of cognitive deficits. In this study, we used the data related to the elderly aged 60–89 in 2020, who were born between 1931 and 1960, and given the social status quo at that time, the education level of the residents was generally low. As education is an important influence on cognitive function, the incidence of cognitive impairment may be higher in older adults born in this period, but with the reform and opening up, the restoration of the college entrance examination, and the popularization of nine-year compulsory education, the education level of the population has been increasing, and the influence of education as a protective factor of cognitive function on cognition as well as the incidence of cognitive impairment may be reduced in the future. Poor memory status is a risk factor for cognitive function in older adults of all ages, i.e., older adults with poor memory status have low cognitive scores. The reason for this is that cognitive dysfunction refers to the progressive decline of memory or other cognitive functions, i.e., memory status is a key factor in assessing cognitive function. Therefore, all sectors of society should pay more attention to the memory of the elderly, and actively take various measures such as memory training to improve the level of memory and reduce the incidence of cognitive dysfunction when the elderly tend to memory decline^[17]. Residence in towns and cities is a protective factor for cognitive function in all age groups, and this study found that the cognitive function of older people living in rural areas was significantly weaker than that of older people living in towns and cities. This phenomenon may be related to the fact that older people in rural areas pay less attention to their physical health, engage in heavy physical labor for long periods lack mental training, lack extensive medical and health knowledge and publicity in rural areas, and have relatively poor access to health care, especially low rates of treatment for physical and mental illnesses, which leads to a greater vulnerability to cognitive deterioration^[18].

No socialization is a risk factor for cognitive function in 60–69 and 70-79-year-olds, while socialization is not an influential factor in 80-89-year-olds. The reason for this is that because of the rapid deterioration of physiological functions, the physical health status and the ability to interact and communicate with the outside world have declined, and the heterogeneity of the elderly in terms of socialization has been decreasing, which has gradually become a non-influential factor for cognitive function. As for the 60–69 and 70-79-year-olds who are in relatively good physical health, the ability to interact and communicate with the outside world is stronger, and the heterogeneity of different older adults in socialization is strong, in which older adults who lack socialization for a long period have fewer social contacts and lower gray matter volume in temporal, frontal and regional areas in socially isolated individuals, and the low gray matter volume associated with social isolation is associated with the lack of expression of genes down-regulated by Alzheimer's disease and genes involved in mitochondrial dysfunction and oxidative phosphorylation, affecting cognitive function in older adults^[19]. Depression is a risk factor for cognitive function in 60–69 and 70-79-year-olds, but not an influencing factor in 80-89-year-olds, The reason for this may be related to the relationship between depression and age, existing research shows that the risk of depression in the elderly decreases with age, the low and middle-aged elderly people due to the social identity role change and physical function decline and produce a sense of old age uselessness, the sense of old age uselessness further triggered by the occurrence of depression, and depression not only exacerbates the structural damage to the brain but also cause damage to the hippocampus and the temporal lobe, which affects the cognitive ability of the elderly patient's cognitive ability^[20].

Women are a protective factor for cognitive function in 60-69-year-old rather than an influencing factor in 70–79 and 80-89-year-old, which may be related to the social roles and activities of 60–69 year old women, who are in better physical condition at this age, and women take on more responsibilities such as taking care of the household and grandchildren after retirement, and participate in social activities with a high frequency and are subjected to a high level of cognitive stimulation, which is conducive to to increase serum levels of brain-derived neurotrophic factor and hippocampal volume, and the time spent in household physical activities is positively correlated with brain volume, especially gray matter volume, all of which are conducive to promoting the improvement of memory function, whereas older adults in the age groups of 70–79 and 80–89 years old are less heterogeneous from males in this age group due to the deterioration of their physical health with age and their diminished ability to take care of household chores and grandchildren. Gender gradually becomes a non-influential factor in cognitive function^[21–22]. At present, the relationship between disability and cognitive function in the elderly is still controversial at home and abroad, and some studies conclude that disability is an influential factor for cognitive function in the elderly of all ages^[23], while others conclude that there is no correlation between disability and cognitive function^[24], and the present study concludes that disability is a risk factor for cognitive function in the elderly of age 70–79 years old, rather than an influential factor for the elderly of age 60–69 and 80–89 years old. The main reason for the controversy is that the mechanism of the association between incapacitation and cognitive function in the elderly has not yet been finalized, and secondly, the samples included in the present study may be affected by other confounding factors, so it is necessary to further investigate the physiological mechanism through clinical trials. Low life satisfaction is a risk factor for cognitive function in 80-89-year-olds, rather than an influencing factor for 60–69 and 70-79-year-olds. The reason for this is that life satisfaction, as a comprehensive subjective evaluation index, not only reflects the physical condition and quality of life of the research subjects but also the fact that frequent participation in rich leisure activities such as outings and cultural activities tends to be more optimistic about one's health, which, to a certain extent, can map the individual's psychological health and have an impact on cognitive conditions. However, due to the rapid decline of physiological functions, the weakening of self-care ability, the increased dependence on the outside world, and the increasing age of the elderly, the heterogeneity of the elderly in other aspects are weakened, and their cognitive functions are more likely to be affected by the life satisfaction. The lack of pension insurance is a risk factor for cognitive function in the 80-89-year-olds, rather than an influencing factor for the 60–69 and 70-79-year-olds. The reason for this is that 80-89-year-old seniors have a higher prevalence of disease compared to 60–69 and 70-79-year-old seniors due to age-related decline in physical function, and the lack of pension insurance to some extent reflects a lack of funds, which means that their investment in health is also insufficient, and the need for healthcare services is not transformed into demand and utilization, with an increased risk of adverse health outcomes or even death. Moreover, older people without pension insurance are more worried about their future income and economic level, which consumes a large amount of cognitive resources and leads to a shortage of resources for other tasks, which in turn affects task processing and hinders cognitive ability.

This paper has the following limitations: due to the use of only national cross-sectional 2020 annual data, it is not able to reflect the dynamics of the study indicators on the cognitive function of older adults of different ages. Based on the literature study, this study included numerous correlates of cognitive function in older adults, but the limited nature of the data in the CHARLS 2020 questionnaire led to the possibility that there may be correlates that were not included in this study, which needs to be improved at a later stage.

The cognitive condition of the elderly deteriorates with age, and there are commonalities and differences in the cognitive function of the elderly in different age groups, as well as differences in the extent to which each factor affects the cognitive function of the elderly in different age groups. Early identification and intervention should be carried out for common influencing factors such as education, memory, and place of current residence in the 60–69 age group, and attention should be paid to older persons with a low level of literacy, especially the younger ones, by providing them with access to education, and by strengthening the popularization of medical and health knowledge among rural older persons, as well as by increasing the investment in health care and raising the older persons' concern for their physical health status. It is also important to pay attention to the mental health of older persons, organize and encourage them to develop social circles and hobbies and reduce negative emotions such as anxiety and autism, which are essential to improving cognitive function in older persons of all ages and reducing the incidence of cognitive impairment and the risk of dementia in middle-aged and older persons. In addition to common factors, gender is an influential factor in the cognitive function of older people aged 60–69 years, disability is a risk factor for the cognitive function of older people aged 70–79 years, and the cognitive function of older people aged 80–89 years is mainly influenced by pension insurance and life satisfaction. Therefore, in carrying out relevant preventive work in the elderly population in the future, the gate will be moved forward, early screening and intervention will be carried out in the low old age stage, and at the same time, personalized and precise interventions will be formulated for the elderly of different ages according to their influencing factors, and clinical medical care, families and communities will work closely together to formulate early strategies for coping with incapacitation, improve the basic medical care insurance system, screen somatic functions regularly, and strengthen preventive health care work for the population with no old-age insurance population, improve life satisfaction, reduce risk factors, enhance protective factors, delay and control the occurrence and progress of cognitive dysfunction, truly realize healthy aging, and compile a network of health and happiness for the elderly.

CHARLS	China Health and Retirement Longitudinal Study
CESD-10	Center for Epidemiologic Studies Depression-10
ADL	Activity of Daily Living
MMSE	Mini-Mental State Examination
CHAID	chi-squared automatic interaction detector

Acknowledgments

We thank the CHARLS project team for supporting this study in terms of data.

Author contributions

All authors made substantial contributions to the conceptualization, design, data processing, and writing of this study. All authors read and approved the final manuscript.

Funding

Not applicable.

Data Availability

The access policy and procedures are available at https://charls.pku.edu.cn/.

Ethics approval and consent to participate

This study applied to the CHARLS project team to obtain authorization for the use of data and was approved by the Ethics Review Board of Peking University (No. IRB00001052-11015).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Author Details

First authors :

Xiaomin Li , female, born in 2000, School of Public Health, Xinjiang Medical University, [email protected],master's degree, research interests: mainly engaged in geriatric health management.

Corresponding author :

Guixiang He,School of Public Health, Xinjiang Medical University,[email protected].

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Analysis of factors influencing age and cognitive function in older adults: a cross-sectional study

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1 Background

2 Methodology

3 Results

4 Discussion

5 Conclusions

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