Cognitive aging describes the transformation of cognitive function with aging, which is characterized by a decline in attention, information processing speed, executive function, and episodic memory (1). Usually, cognitive decline is slow and acceptable, and does not seriously affect older adults' daily life. Unusual cognitive aging is associated with a variety of neurological diseases, especially dementia, which has been a major cause of disability in older adults and exerts a considerable burden on society and the economy (2). With increase in global aging, dementia has increased rapidly in recent years. An estimated 50 million people worldwide were living with dementia in 2018, and this number is expected to increase to 152 million by 2050 (3). Although dementia is characterized by symptoms of cognitive dysfunction, it is not an inevitable consequence of cognitive aging. Multiple factors result in cognitive dysfunction, which is difficult to reverse; however, its preventability is being explored and supported by an increasing amount of evidence.

It's not just cognitive dysfunction that needs to be improved, and usual cognitive aging also wouldn't be the ultimate goal of cognitive interventions in older adults. Despite not reaching the stage of cognitive dysfunction, significant differences exist among individuals in terms of cognitive aging. Based on the heterogeneity of cognitive aging (4), Rowe and Kahn (5) proposed the concept of successful cognitive aging, which differs from the concept of usual cognitive aging and highlights a higher level of cognitive function preservation and improvement. In the study by Hartley et al. (6), cognitive aging was classified into three grades: unsuccessful, usual, and successful. Exploring the common characteristics of successful cognitive aging could be helpful in providing targets for cognitive intervention and facilitating the individual's transition to successful cognitive aging.

Previous studies have found that usual cognitive aging may be influenced by certain physiological, psychological, behavioral, and social factors; modifying these factors could aid in the prevention or delay of cognitive decline and further prevent dementia (7). Approximately 40% of dementia is attributable to a combination of the following 12 risk factors: less education, hypertension, hearing impairment, smoking, obesity, depression, physical inactivity, diabetes, low social contact, alcohol consumption, traumatic brain injury, and air pollution (8). It is widely recommended to maintain a healthy lifestyle (9), which can help maintain a higher level of cognitive and physical function and reduce neuropathological damage in neurodegenerative diseases associated with cognitive aging (10). Therefore, we propose in hypothesis 1 that adherence to a cognitive-related lifestyle promotes cognitive aging. However, the lifestyle of most people still falls short of the recommended guidelines owing to various barriers between theoretical guidance and practicality (11). Therefore, exploring the internal factors of people's adoption of cognitive-related healthy lifestyles and providing evidence for developing specific intervention strategies are necessary for successful cognitive aging.

The Health Belief Model (HBM) could be helpful in understanding the beliefs and motivations for adopting a cognitive-related healthy lifestyle. The HBM, which is one of the earliest and most widely used theories in the field of health behavior, is capable of exploring internal factors and elucidating the internal decision-making process of the individual's health behavior. HBM is most commonly used for prevention-related and asymptomatic health problems, such as early cancer detection and hypertension screening, in which beliefs are just as or more important than obvious symptoms (12). Six dimensions were described in the HBM, including perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy. Compared with five other behavioral change models (e.g., Health Locus of Control, Theory of Reasoned Action/Theory of Planned Behavior, Self-efficacy Theory, Stage of Change/Transtheoretical Model of Change, and Common Sense Model of Self-regulation), the HBM was considered the best model to elucidate the mechanism of risk reduction of dementia (13). Thus, exploring the related mechanism from the perspective of the HBM is important when establishing a healthy lifestyle for successful cognitive aging.

Previous studies have focused more on the status and influencing factors of dementia prevention beliefs and their correlation with willingness to engage in health-related behaviors (14–17). Akyol et al. (16) conducted a survey on the dementia prevention beliefs of 284 Turkish people over the age of 40 years; the results demonstrated that age, years of education, family history of dementia, subjective memory complaints, and willingness to understand their own risks were influencing factors of dementia prevention beliefs. Moreover, a study by Seifan et al. (15) demonstrated that individuals' beliefs in dementia prevention would affect their willingness to engage in health-related behaviors, such as actively seeking help from professional doctors, actively identifying personal risk of dementia, and actively learning knowledge of dementia prevention. However, the effect of the individuals' beliefs on cognitive-related behaviors and the characteristics of beliefs deserve attention in dementia prevention. In a recent study, Li et al. (18) found that different health beliefs had either positive or negative effects on health-promoting lifestyle. However, the scale used in Li et al. (18) study was the Chinese version of the Health Promoting Lifestyle Profile-II (HPLP-II), which was lack of pertinence to assess the lifestyles that reduce the risk of dementia. In addition, the belief-lifestyle exploration in this study did not extend to the final cognitive outcome. The contribution of beliefs in dementia prevention on cognitive aging by influencing cognitive-related healthy lifestyles should be explored more deeply.

In this study, our classification of health beliefs referred to the findings revealed by Li et al. (18). Furthermore, according to the HBM (19), as an external cause, cues to action can directly affect health behaviors or indirectly affect health behaviors by acting on other belief dimensions. Based on the study of Li et al. (18), in combination with the theory of HBM, the health belief was re-divided into three dimensions in this study: positive beliefs, negative beliefs, and cues to action. Therefore, we propose in hypothesis 2 that positive beliefs have a promoting effect on lifestyle, negative beliefs have a hindering effect on lifestyle, and cues to action can directly affect lifestyle, and can also indirectly affect lifestyle through positive and negative beliefs. The Reduced Risk of Dementia Lifestyle Measure (LDRR) (20), which measures cognitive-related healthy lifestyles, was designed in our previous studies based on the HPLP-II and the latest evidence on dementia prevention, and has been verified to have good reliability and validity. The LDRR focusing on multiple healthy lifestyles that reduce the risk of dementia, and is suitable for this study to explore the relationship between beliefs, lifestyles and cognitive aging. We propose in hypothesis 3 that health beliefs affect cognitive aging by influencing cognitive-related healthy lifestyle.

Based on the HBM, this study aimed to describe the status of dementia prevention beliefs of the individuals and establish a structural model of beliefs, lifestyle, and cognitive aging. This study aimed to elucidate whether dementia-prevention beliefs have a direct impact on cognitive-related healthy lifestyles; successful cognitive aging is related to a healthy cognitive-related lifestyle; and dementia-prevention beliefs have an indirect effect on cognitive aging through lifestyle. Figure 1 shows our constructed model for the hypothesis testing.

In this study, the participants were divided into three groups: successful cognitive aging, usual cognitive aging, and unsuccessful aging, based on the study of Hartley et al. (6). According to the HBM, this study explored the relationship among beliefs, lifestyle, and cognitive aging grades.

In this study, 8.4% of the participants achieved successful cognitive aging, which was lower than that (16.0%) in the study of Hartley et al. (6). This difference could be related to regional, population, economic, and cultural differences. Currently, no comprehensive and statistical data exist on the proportion of successful cognitive aging in previous studies; however, some studies have demonstrated the proportion of successful memory aging to be approximately 6–40% (29). Univariate analysis showed that the lower the educational level and monthly incomes, the lower the cognitive aging grade. Education status and income are both socioeconomic status (SES) factors. A previous study suggested that low SES is a risk factor for cognitive impairment in older adults (30). Low SES may exacerbate unequal cognitive impairment among older adults, because people with higher SES often have more opportunities to diagnose cognitive impairment, rectify adverse factors, and avoid further deterioration in cognitive function than those with lower SES (31). Such differences in access to medical resources may accumulate over time (32).

The results of this study suggest that a cognitive-related healthy lifestyle has a direct and positive impact on cognitive aging grades. The cognitive-related healthy lifestyle explained 18.2% of the variation in cognitive aging in this study. Notably, dementia is mainly controlled by age and genetic factors (33). Only 40% of cases of dementia are attributable to a combination of modifiable risk factors, including not only lifestyle factors but also traumatic brain injury, air pollution, and other chronic diseases (8). Therefore, the explanation of the rate of variation in this study (18.2%) is reasonable and understandable. Although the impact of lifestyle interventions on individuals may be modest, modifying the individual's lifestyle could have a greater social impact owing to its superior cost-effectiveness compared with other modifiable factors. An increasing number of studies (9, 34–36) have focused on lifestyle interventions for cognitive improvement, and modifying the lifestyle concerning physical activity, smoking, alcohol consumption, diet, social activities, and the management of chronic diseases, such as hypertension, diabetes, obesity, and dyslipidemia, is widely recommended. The LDRR used in this study was also developed according to the recommendations of related studies and guidelines and was more targeted than the general lifestyle scale.

In this study, the health beliefs were divided into three dimensions, including positive beliefs, negative beliefs, and cues to action, based on the study by Li Hua et al. (18), and the HBM. The path analysis in this study showed the specific path and mechanism of these beliefs on lifestyle and cognitive aging grades, as well as the direct and indirect influences among them. Health beliefs accounted for 39.3% of the variation in lifestyle, suggesting that interventions with health beliefs may effectively promote the adoption of cognitive-related healthy lifestyles. In this study, positive beliefs included perceived benefits, general health motivation, and self-efficacy, which described people's concerns about their own health, recognition of the benefits of changing lifestyles, and confidence in adhering to the lifestyle (13). We found that these positive beliefs have a direct and positive impact on lifestyle and indirectly contribute to successful cognitive aging.

This study also showed that negative beliefs had a direct and negative impact on lifestyle and further indirectly impeded the achievement of successful cognitive aging, which was different from the usual cognition of the HBM. According to the HBM (19), perceived susceptibility and perceived severity are used to describe people's perception of threats to diseases, which could stimulate the adoption of a healthier lifestyle to reduce threats. However, considering cognitive aging and dementia prevention, perceived susceptibility and perceived severity may have a hindering effect rather than a promoting effect on people's adoption of healthy behaviors. This could be explained by the concept of dementia worry (DW). DW is defined as an emotional response to the perceived threat of dementia (37). A moderate level of DW leads to adaptive responses, whereas a high level of DW leads to maladaptive responses. Thus, people who perceive acceptable fear and risk of dementia may be more willing to adopt a cognitive-related healthy lifestyle; in contrast, people who are too fearful concerning dementia and even engage in dementia risk reduction may be more willing to avoid behavioral change (17). In addition, previous studies have found that negative perceptions of dementia and aging are associated with DW, including dementia stigma and negative age-related stereotypes (38–40), which may further influence cognitive-related lifestyle changes. The results of this study suggest that the negative effects of negative beliefs on health behaviors should be considered in educational programs for dementia prevention and cognitive aging, especially for people at a high risk of dementia (e.g., those with a family history of dementia). When people present obvious perceived threat (susceptibility and severity) and concern for dementia, medical focus should be transferred to provide feasible interventions on the perceived benefits and self-efficacy to enhance the belief that dementia can be prevented and controlled.

This study found that both positive and negative beliefs were promoted by cues to action. Cues to action are factors that remind individuals to participate in healthy behaviors. Few studies have explored the role of cues to action. Some studies have found that cues to action may indirectly affect behaviors through other health beliefs or may directly affect behaviors (41). Cues to action reportedly work mainly through perceived threats (19). In the MCLHB-DRR, cues to action include amnesia symptoms, dementia risk, media publicity of dementia-related knowledge, and family history of dementia. In this study, cues to action may promote negative beliefs through amnesia symptoms, dementia risk, and a family history of dementia, which may trigger people's perception of dementia threat (perceived susceptibility and severity). Furthermore, cues to action may promote positive beliefs through media publicity, which could provide information on how to adhere to healthy lifestyles and reduce the risk of dementia. However, the overall effect of cues on lifestyle could be weakened because positive and negative beliefs have opposing effects on lifestyle. These results further suggest that, in lifestyle intervention programs, education and advocacy should be used as incentives to reduce negative beliefs and promote positive beliefs.

This study provided evidence for the development of public health interventions. First, community cognitive health management should pay more attention to older adults with limited SES. It would be better to develop targeted healthy lifestyle interventions for older adults with limited SES based on their specific conditions, available resources, and barriers to maximize their use of public medical resources. Moreover, reducing the negative impact of negative beliefs on healthy lifestyles should be recommended in media publicity and health education programs. Targeted interventions on general health motivation, perceived benefits, and self-efficacy may be better for people with high perceived susceptibility and severity (e.g., people with a family history of dementia). It may be necessary to employ these targeted interventions to improve people's awareness of the preventability and controllability of dementia and promote positive belief for adhering to a healthy lifestyle. Finally, interventions can be designed from a more positive perspective to promote successful cognitive aging and encourage people to adopt a more positive attitude toward a cognitive-related healthy lifestyle.

This study had certain limitations. First, owing to the lack of the earlier cognitive function data of the participants, this study only explored the cognitive aging grades from a cross-sectional perspective and classified the cognitive aging grades based on the general cognitive function of community residents who were middle aged and older. With regard to measurement tools, MoCA, as a cognitive screening scale, is inadequate in measuring the general cognitive function of subjects. Moreover, the classification of cognitive aging grade was based on standard score of MoCA, which is the relative standard distance between an individual's cognitive score and the average cognitive score of the group. The cutoff value of cognitive aging grade divided by this method was not constant, and it will vary with samples of different characteristics, which is not conducive to comparison with other studies. Additionally, this classification could hardly explore the rate and trajectory of cognitive decline, and could be biased for different individuals. Second, a single-center survey and limited sample size were employed in this study owing to the limitation of human and economic resources, as well as the barriers brought about by the coronavirus disease 2019. Lastly, considering accessibility, only community residents who had attended free physical examinations in the community health service center were recruited in this study. Compared with those who had not attended free physical examination in the community health service center, participants in this study may have possessed higher levels of health literacy and higher acceptance of cognitive-related healthy lifestyles, which could have resulted in some overestimation in this study for the lifestyle among community residents who were middle aged and older. In the future, the follow-up studies are warranted to further explore successful cognitive aging in individuals from a longitudinal perspective. And additional studies with a larger sample size and wider sampling area, and more fine-grained neuropsychological assessment methods (e.g., attention, speed of information processing, executive function, and episodic memory) should be conducted to further test the model.

In this study, a limited number of participants achieved successful cognitive aging based on the criteria of this study. Moreover, lifestyle had a direct and positive impact on the cognitive aging grades. Positive beliefs had a positive effect on lifestyle, thus promoting successful cognitive aging. Negative beliefs had a negative effect and hindered the realization of successful cognitive aging. The results suggested that primary medical staff could strengthen the positive beliefs of community residents and weaken their negative beliefs to guide them to adhere to cognitive-related healthy lifestyles and promote successful cognitive aging.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the Ethics Committee of the Army Medical University. The patients/participants provided their written informed consent to participate in this study.

YY developed the ideas, administrated the project, provided significant academic guidance on manuscript, and revised the manuscript critically for intellectual content. JZ and XL collected the data, conducted the data analysis, interpreted the results, drafted, and revised the manuscript. DG and YP collected the data, edited, and revised the manuscript. HL collected the data and edited the manuscript. All authors agreed to be accountable for the content of the work, read, and approved the final manuscript.

This study was supported by a grant from the National Social Science Foundation of China (No. 20BRK039). The funders had no role in the study design, data collection, analysis, and decision to publish or preparation of the manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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