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The influence of healthy eating index on cognitive function in older adults: chain mediation by psychological balance and depressive symptoms

BMC Geriatrics volume 24, Article number: 904 (2024) Cite this article

Abstract

Background

This study aims to investigate the relationships between the Chinese Healthy Eating Index (CHEI), psychological balance, depressive symptoms, and cognitive function in the rural older population. Additionally, it examines the impact of CHEI on cognitive function and the potential chain mediating roles of psychological balance and depressive symptoms.

Methods

The study utilized data from 2,552 rural older adults aged 65 and above, drawn from the Chinese Longitudinal Healthy Longevity Study (CLHLS). The CHEI was self-reported, with scores ranging from 0 to 50, representing adherence to healthy eating habits. Psychological balance was assessed using status and personality-emotion characteristics recorded in the database, with scores ranging from 6 to 30. Cognitive function was measured using the Mini-Mental State Examination (MMSE), with scores ranging from 0 to 30; higher scores indicated better cognitive function. Depressive symptoms were evaluated using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10), with scores ranging from 0 to 30, where higher scores reflected more severe depressive symptoms.

Results

The median CHEI score was 40.0 (IQR: 34.0–45.0), reflecting moderate adherence to healthy dietary practices. The median Psychological Balance score was 19.0 (IQR: 17.0–21.0), and the median Depressive Symptoms score was 13.0 (IQR: 10.0–15.0), indicating mild depressive symptoms among participants. Additionally, the median Cognitive Function score was 28.0 (IQR: 27.0–29.0), suggesting relatively stable cognitive abilities within the sample. Correlational analysis revealed the following: (1) Depressive symptoms were negatively correlated with both cognitive function (rs = -0.100, p < 0.001) and CHEI (rs = -0.206, p < 0.001), as well as with psychological balance (rs = -0.142, p < 0.001). (2) CHEI was positively correlated with both cognitive function (rs = 0.144, p < 0.001) and psychological balance (rs = 0.131, p < 0.001). (3) Cognitive function was also positively correlated with psychological balance (rs = 0.096, p < 0.001). Mediation analysis demonstrated that both psychological balance and depressive symptoms partially mediated the relationship between CHEI and cognitive function, forming a chain-mediating effect.

Conclusion

The Chinese Healthy Eating Index was found to have a direct positive impact on cognitive function in rural older adults. Furthermore, it exerted an indirect effect through the independent and chain-mediating roles of psychological balance and depressive symptoms. These findings suggest that dietary adherence can influence cognitive health not only directly but also by improving psychological well-being and reducing depressive symptoms.

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Introduction

Cognitive impairment in older adults is often marked by declines in memory, attention, and decision-making abilities, and frequently serves as an early indicator of dementia, including Alzheimer’s disease [1, 2]. While the global prevalence of cognitive impairment varies, it is a particularly pressing health issue in rural older populations [3]. Identifying modifiable factors, such as dietary quality, that impact cognitive function is critical for delaying the onset of dementia in these high-risk groups [4, 5]. Although cognitive impairment can be reversible if detected early [6], timely identification of at-risk older adults is essential to slowing its progression. Thus, recognizing modifiable factors that may prevent or delay cognitive decline in rural older adults is vital for addressing this growing concern.

Rural populations are especially vulnerable to cognitive impairment due to relatively poor living conditions, limited access to healthcare, and inadequate social support. These factors not only heighten the risk of cognitive decline but also restrict access to interventions that could mitigate these risks. Therefore, focusing on rural older adults allows for the development of targeted strategies that could improve cognitive health in this underserved group.

Diet quality, measured through the Chinese Healthy Eating Index (CHEI), has been positively associated with cognitive function in older adults [7]. However, the mechanisms through which diet influences cognition—particularly via psychological factors such as psychological balance and depressive symptoms—are not well understood [8]. This study aims to explore how psychological balance and depressive symptoms mediate the relationship between CHEI and cognitive function, providing new insights for improving cognitive health in rural older populations.

Chinese healthy eating index and cognitive function

The Chinese Healthy Eating Index (CHEI) is a comprehensive measure of dietary quality that reflects adherence to established nutritional guidelines [9]. Studies have shown that higher CHEI scores are associated with better cognitive function, which may be attributed to beneficial dietary components, such as antioxidants and polyphenols. These nutrients are known to support brain health by reducing oxidative stress and inflammation [7, 10, 11]. Additionally, a healthy diet positively affects cardiovascular health, which is closely linked to maintaining cognitive function [12,13,14,15,16]. Based on this evidence, the study proposes Hypothesis 1 (H1): The CHEI positively affects cognitive function.

The mediating role of psychological balance and depressive symptoms

While the direct impact of diet on cognitive function is well-documented, the pathways through which psychological and emotional factors mediate this relationship require further exploration. Psychological balance and depressive symptoms are crucial determinants of cognitive function in older adults [17, 18]. Psychological balance, which encompasses emotional stability and resilience, helps individuals cope with stress, thus protecting cognitive function [19, 20]. A healthy diet can support psychological balance by providing essential nutrients that promote mental well-being. For instance, omega-3 fatty acids and vitamin B6 aid in neurotransmitter regulation, enhancing mood and reducing depressive symptoms, which, in turn, positively affect cognitive function [21, 22]. Furthermore, a healthy diet may reduce depressive symptoms by decreasing inflammation and supporting gut health, both of which are associated with improved cognitive outcomes [23,24,25,26,27,28,29].

Given these relationships, this study proposes that psychological balance and depressive symptoms mediate the relationship between CHEI and cognitive function in older adults. Hypothesis 2 (H2): The CHEI positively affects psychological balance, which subsequently reduces depressive symptoms. Together, psychological balance and depressive symptoms mediate the relationship between CHEI and cognitive function in a chain manner.

This study aims to investigate the impact of the Chinese Healthy Eating Index (CHEI) on cognitive function and to explore the underlying mechanisms through the chain mediation of psychological balance and depressive symptoms. By examining these mediating effects, the study seeks to uncover the pathways through which a healthy diet influences cognitive function, offering new insights and empirical evidence to enhance cognitive health among the rural older population.

Methods

Study participants

The data for this study were sourced from the 8th wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), a large-scale and long-term social science survey conducted by Peking University. The CLHLS, running from 1998 to 2018, spans 23 provinces, municipalities, and autonomous regions in China, with a cumulative sample size of 113,000 respondents. The 8th wave, conducted between 2017 and 2018, surveyed 15,874 individuals.

The inclusion criteria for this study were: (1) rural older adults aged 65 and above; (2) available results from the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10); (3) available cognitive function data, specifically a Mini-Mental State Examination (MMSE) score of greater than 10; (4) available data on the Chinese Healthy Eating Index (CHEI); and (5) available psychological balance data.

After applying these criteria, the following exclusions were made: 8,780 non-rural older adults, 3 individuals without CHEI data, 619 individuals without CESD-10 data, 1,202 individuals without psychological balance data, and 2,718 individuals without cognitive function data. This resulted in a final sample of 2,552 rural older adults. The screening process is illustrated in Fig. 1.

The participants’ ages ranged from 67 to 112 years, with a median age of 77.0 years (IQR: 71.0–85.0). The sample included 468 men and 1,084 women, 1,942 individuals of Han ethnicity, and 610 from other ethnic groups. In terms of education, 905 participants had a primary school education or below, 472 had a middle school education, and 1,175 had a high school education or above. Additionally, 1,069 participants were unmarried, while 1,483 had a spouse.

The CLHLS study was approved by the Research Ethics Committee of Peking University (IRB00001052-13074), and informed consent was obtained from all participants. According to national guidelines in China, secondary analysis of public data does not require additional ethics approval. Further details can be found at the following link: http://www.nhc.gov.cn/qjjys/s7946/202302/c3374c180dc5489d85f95df5b46afaf5.shtml.

Fig. 1
figure 1

Flow diagram of the selection of sample

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Research tools

Depression self-rating scale

In this study, depressive symptoms were assessed using the short form of the Center for Epidemiologic Studies Depression Scale (CES-D-10), which consists of 10 items designed to evaluate depressive symptoms in older adults over the preceding week [30, 31]. Each item is scored on a scale from 0 to 3, with two items requiring reverse scoring. The total depression symptom score, treated as a continuous variable, ranges from 0 to 30, where higher scores indicate more severe depressive symptoms. The CES-D-10 scale has demonstrated good reliability and validity in screening for depressive symptoms among Chinese older adults, with a Cronbach’s alpha coefficient of 0.78.

Chinese healthy eating index

The Chinese Healthy Eating Index (CHEI) comprises 13 food components [32, 33]. Participants reported their frequency of consumption of these items over the past month, including fruits, vegetables, meat, fish, eggs, beans, pickled vegetables, sugar, tea, garlic, nuts, mushrooms, and milk. For fruits and vegetables, the response options were: almost daily (3 points), quite frequently (2 points), occasionally (1 point), and rarely or never (0 points). For the other items, the options were: almost daily (4 points), at least once a week (3 points), at least once a month (2 points), occasionally (1 point), and rarely or never (0 points). The total score can reach up to 50 points, with higher scores indicating healthier dietary patterns.

Cognitive function scale

Cognitive function among rural older adults was assessed using the Mini-Mental State Examination (MMSE), which was developed by Folstein [34] and adapted for the Chinese cultural and socioeconomic context [35]. The MMSE consists of 24 items across six dimensions, yielding a total score that ranges from 0 to 30. These dimensions include orientation (5 items), registration (3 items), naming (1 item), attention and calculation (5 items), recall (3 items), and language (7 items). One specific item, “Name as many kinds of food as you can in one minute,” has a maximum score of 7 points, while the remaining items each have a maximum score of 1 point. Higher scores signify better cognitive function, with scores below 18 indicating cognitive impairment.

Psychological balance scale

To assess psychological balance, we employed indicators and calculation methods from previous research [36,37,38]. This study evaluated psychological balance through the “Current Status Assessment and Personality-Emotion Characteristics” questionnaire, which captures older adults’ subjective perceptions of their overall quality of life and living standards. The survey includes three questions reflecting positive emotions: “How do you feel about your life now?“, “Can you think about what is happening around you?“, and “Do you feel energetic?” Negative emotions were assessed with three questions: “Do you feel ashamed, regretful, or guilty about things you have done?“, “Do you feel angry towards people or things you dislike?“, and “Do you often feel that people around you are untrustworthy?” Responses to positive emotion questions were reverse scored, ranging from “very good” (5 points) to “very bad” (1 point). In contrast, negative emotion questions were scored directly, with “always” (1 point) to “never” (5 points). This standardization enabled clear data measurement and calculation. Scores for both positive and negative emotions range from 3 to 15, yielding a total psychological balance score between 6 and 30, with higher scores indicating better psychological balance.

Covariates

The covariates considered in this study included age, gender, marital status, self-reported health (“How do you feel about your health now?“), daily sleep duration (in hours), smoking status, alcohol consumption, exercise frequency, economic status (“How do you rate your economic status compared with others in your locality?“), hearing loss (“Do you have any difficulty with your hearing?“), Body Mass Index (BMI), and the number of chronic diseases (including hypertension, dyslipidemia, diabetes, cancer, heart attack, stroke, Parkinson’s disease, arthritis, etc.). Economic factors were assessed through a question on the sufficiency of financial resources (“Is your financial support sufficient to cover daily expenses?“).

Data analysis

Data analysis and processing were conducted using IBM SPSS version 26.0 (IBM Corp, Armonk, NY). Descriptive statistics were first conducted, with measurement data presented as medians and interquartile ranges (IQR) due to the non-normal distribution identified by normality tests. Categorical variables were summarized using frequency and percentage distributions. Spearman correlation was employed to examine relationships between continuous variables.

Given the need for weighting in the dataset, we adjusted for sampling weights in all analyses to account for unequal probabilities of selection, thereby enhancing representativeness. Weight adjustments were applied using the SPSS Complex Samples module to ensure the results were generalizable to the population of interest. These adjustments were incorporated across all descriptive and inferential analyses, including correlation and mediation modeling.

The PROCESS macro version 3.5 (model 6) by Hayes was utilized for mediation analysis, with the Chinese Healthy Eating Index as the independent variable, Psychological Balance and Depressive Symptoms as mediating variables, and Cognitive Function as the dependent variable. Univariate analysis identified several statistically significant variables (gender, marital status, self-reported health, drinking status, hearing loss, exercise frequency, and BMI) to be included as control variables.

In the univariate analysis, cognitive function was dichotomized into a binary variable (0 = cognitive impairment, 1 = no cognitive impairment), while in other analyses, it was treated as a continuous variable. All models included weight adjustments to maintain accuracy in parameter estimates.

A p-value of 0.05 was deemed statistically significant. We set the bootstrap confidence interval (CI) at 95%, based on a bootstrap sample of 5000. A significant mediation effect was indicated if zero was not included in the 95% confidence interval.

Results

Common method bias test

To assess common method bias, we employed the Harman single-factor test method [39]. An overall analysis of all items related to the four variables was conducted using the factor analysis function in SPSS. The results revealed that the variance explained by the first component was 10.9%, which is below the 30% threshold. Thus, we conclude that there is no significant common method bias in this study.

Basic characteristics and univariate analysis

As detailed in Table 1, a total of 2,552 participants were included in this study. The median score for the Chinese Healthy Eating Index (CHEI) was 40.0, with an interquartile range (IQR) of 34.0 to 45.0, indicating moderate adherence to a healthy diet. The median score for Psychological Balance was 19.0 (IQR: 17.0–21.0), while the median score for Depressive Symptoms was 13.0 (IQR: 10.0–15.0), suggesting generally mild depressive symptoms in the population. Furthermore, the median Cognitive Function score was 28.0 (IQR: 27.0–29.0), reflecting relatively stable cognitive function among participants.

Table 1 Descriptive statistics for Chinese healthy eating Index, Psychological Balance, depressive symptoms and cognitive function (N = 2552)
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The median age of the participants was 77.0 years (IQR: 71.0 to 85.0), 1468(57.5%) males and 1084(42.5%) females. 83.7% of the participants had cognitive impairment. Univariate analysis showed that gender, marital status, self-reported health, drinking, hearing loss, exercises, and BMI had a statistically significant effect on cognitive function (p < 0.05). The detailed data was presented in Table 2. Figure 2 showing the population distribution of the Chinese Healthy Eating Index. Figure 3 depicting the population distribution of the Chinese Healthy Eating Index.

Table 2 Basic characteristics and univariate analysis of the participants by cognitive impairment
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Fig. 2
figure 2

Box plot of the population distribution for the Chinese healthy eating index

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Fig. 3
figure 3

Histogram of the population distribution for the Chinese healthy eating index

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Spearman correlation coefficients (r) between Chinese healthy eating index, psychological balance, depressive symptoms, and cognitive function in rural older adults

Depressive symptoms were negatively correlated with cognitive function (rs = -0.100, p < 0.01), the Chinese Healthy Eating Index (rs = -0.206, p < 0.01), and psychological balance (r = -0.142, p < 0.01). The Chinese Healthy Eating Index was positively correlated with cognitive function (rs = 0.144, p < 0.01) and psychological balance (rs = 0.131, p < 0.01). Cognitive function was positively correlated with psychological balance (rs = 0.096, p < 0.01). See Table 3.

Table 3 Spearman correlation coefficients (rs) between Chinese healthy eating Index, Psychological Balance, depressive symptoms, and cognitive function in rural older adults
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Analysis of chain mediation effect

Psychological balance and depressive symptoms were included as the first and second mediating variables, respectively, in the chain mediation path. The analysis was performed on standardized data for each variable, with results detailed in Table 4.

Table 4 Analysis of the mediation effect of Chinese healthy eating index on cognitive function in rural older adults, Controlling for demographic variables
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The data analysis revealed that in the chain mediation model, the Chinese Healthy Eating Index (CHEI) positively influenced psychological balance (β = 0.033, t = 4.635, p < 0.01) and negatively affected depressive symptoms (β = -0.096, t = -8.191, p < 0.01). Furthermore, psychological balance was found to negatively impact depressive symptoms (β = -0.363, t = -10.321, p < 0.01) and positively influence cognitive function (β = 0.068, t = 3.022, p < 0.01). Additionally, depressive symptoms were negatively associated with cognitive function (β = -0.030, t = -2.276, p < 0.01).

To assess the significance of the mediation effects, we employed the Bootstrap test [40], examining the confidence intervals of the mediation effects. The 95% confidence intervals for the chain mediation effects did not include zero, indicating that these mediation effects were statistically significant, as presented in Table 5. The analysis also revealed that the mediation effect accounted for 25.0% of the total effect of CHEI on cognitive function among rural older adults, further detailed in Table 5. A path diagram illustrating these relationships is shown in Fig. 4.

Table 5 Chain mediation effects and 95% confidence intervals for the relationship between Chinese healthy eating index and cognitive function in rural older adults
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Fig. 4
figure 4

Path diagram of the impact of Chinese healthy eating index on cognitive function

notes: * p < 0.01

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Discussion

The findings of this study indicate that the Chinese Healthy Eating Index (CHEI) significantly positively affects cognitive function, thus confirming Hypothesis (1) Furthermore, psychological balance and depressive symptoms act as chain mediators in the relationship between CHEI and cognitive function, supporting Hypothesis (2) This inclusion of psychological balance and depressive symptoms as mediating variables elucidates the impact of CHEI on cognitive function and reveals underlying mechanisms, providing new perspectives and empirical evidence for enhancing cognitive health among rural older adults.

Relationship between Chinese healthy eating index and cognitive function in rural older adults

Our analysis demonstrated a significant positive correlation between CHEI and cognitive function in rural older adults (rs = 0.144, p < 0.001). Consistent with findings from Feart et al. in the Three-City Study, which indicated that adherence to the Mediterranean diet—similar to high CHEI scores—can slow cognitive decline, our results support the notion that dietary quality positively influences cognitive performance [10]. Similarly, Akbaraly et al. found a correlation between higher CHEI scores and improved cognitive performance among older adults in the United States [7, 8].

The protective effect of dietary quality on cognitive function may be attributed to the presence of antioxidants, anti-inflammatory substances, and beneficial fatty acids in a healthy diet, which collectively protect brain function and mitigate cognitive decline. Specific dietary components, such as omega-3 fatty acids, vitamin E, and polyphenols, are known to have protective effects on brain health. Omega-3 fatty acids enhance neuronal membrane fluidity, improving neural transmission efficiency, while vitamin E acts as a potent antioxidant that reduces oxidative stress on brain cells [7, 9, 11]. Additionally, polyphenols, particularly flavonoids, exhibit anti-inflammatory and antioxidant properties that contribute to cognitive health through various biological pathways. Consequently, individuals with high CHEI scores are more likely to derive these beneficial nutrients from their diets, supporting better cognitive function.

The mediating role of psychological balance in the impact of Chinese healthy eating index on cognitive function in rural older adults

Our findings indicate that psychological balance partially mediates the relationship between CHEI and cognitive function. Specifically, CHEI has a significant positive effect on psychological balance (β = 0.033, t = 4.635, p < 0.001), while psychological balance significantly positively affects cognitive function (β = 0.068, t = 3.022, p < 0.001). This aligns with the stress process model in psychology [41], which posits that good nutrition can enhance psychological balance, thereby benefiting cognitive function.

Psychological balance is crucial as it can reduce stress responses and bolster psychological resilience. Research suggests that individuals with better psychological balance can effectively regulate their emotions and maintain a positive state when confronted with life stressors [17]. This ability to regulate emotions is vital for cognitive function; prolonged psychological stress can elevate cortisol levels, which may damage the hippocampus and prefrontal cortex, negatively impacting memory and cognitive abilities [19]. Therefore, maintaining psychological balance is essential in mitigating the adverse effects of psychological stress on cognitive function.

Moreover, a healthy diet may also improve sleep quality, further enhancing both psychological balance and cognitive function. Certain dietary components, such as tryptophan, magnesium, and vitamin B6, have been shown to promote better sleep quality [21]. Quality sleep positively impacts psychological balance and is essential for memory consolidation and cognitive maintenance [42]. Thus, a healthy diet fosters psychological balance through various pathways, indirectly promoting cognitive function.

The mediating role of depressive symptoms in the impact of Chinese healthy eating index on cognitive function in rural older adults

The study also found that depressive symptoms significantly mediate the relationship between CHEI and cognitive function. CHEI negatively influences depressive symptoms (β = -0.096, t = -8.191, p < 0.001), while depressive symptoms adversely affect cognitive function (β = -0.030, t = -2.276, p < 0.001). These findings are consistent with prior research that identifies depressive symptoms as a risk factor for cognitive decline [23].

Healthy eating may reduce depressive symptoms through multiple mechanisms, thus safeguarding cognitive function. Nutritional components can directly influence neurotransmitter synthesis and metabolism. For instance, adequate intake of omega-3 fatty acids, vitamin D, and B vitamins can elevate dopamine and serotonin levels in the brain, which are crucial for emotional stability [26]. Additionally, a healthy diet may attenuate inflammatory responses; chronic inflammation is closely linked to depressive symptoms, and anti-inflammatory dietary components, such as polyphenols, can significantly lower inflammation levels [18].

Furthermore, healthy eating can regulate mood by improving gut microbiota. Recent studies have highlighted the bidirectional communication between the gut and brain, referred to as the “gut-brain axis.” A healthy gut microbiota can produce neurotransmitter precursors and short-chain fatty acids that influence brain function and mood [28]. Thus, a healthy diet can positively impact depressive symptoms through its effects on gut health, thereby protecting cognitive function.

The chain mediating role of psychological balance and depressive symptoms in the impact of Chinese healthy eating index on cognitive function in rural older adults

The results indicate a chain-mediating effect of psychological balance and depressive symptoms in the relationship between CHEI and cognitive function. Chain mediation analysis demonstrated that CHEI first influences psychological balance, which subsequently affects depressive symptoms, ultimately impacting cognitive function. This chain mediation pathway suggests that psychological balance and depressive symptoms collectively constitute the complex mechanisms through which healthy eating affects cognitive function.

The stress process model posits that stressors, including poor diet and mental health issues, can directly and indirectly influence cognitive health through various pathways [41]. This model provides a theoretical framework for understanding how psychological balance and depressive symptoms mediate the relationship between diet and cognitive function. Additionally, these findings align with the Theory of Planned Behavior [43], which emphasizes that individual behaviors are influenced by attitudes, subjective norms, and perceived behavioral control, subsequently impacting cognitive function through mental health. Specifically, healthy dietary habits can enhance psychological balance and reduce depressive symptoms, thereby improving cognitive abilities. This process can be conceptualized as a positive behavioral cycle, where healthy eating fosters improved psychological balance, which in turn is associated with reduced depressive symptoms. A positive mental health state may further support the maintenance of healthy behaviors [44]. However, it is important to note that these associations may be influenced by other measured or unmeasured factors, preventing definitive causal conclusions.

In summary, CHEI exerts both direct and indirect effects on cognitive function among rural older adults, with the chain mediation roles of psychological balance and depressive symptoms further enhancing this impact. To effectively promote cognitive health among this population, policymakers and public health practitioners should encourage healthy dietary habits and provide psychological support to help older adults maintain psychological balance and reduce depressive symptoms. This comprehensive approach will contribute to improving the quality of life and health among older adults. Future research should leverage longitudinal analyses to track dietary patterns, psychological health, and cognitive function across multiple waves of data collection. Such studies would provide a clearer understanding of the temporal dynamics involved and enable more accurate causal inferences, particularly regarding how family-based factors and shared environments contribute to these health outcomes over time.

Potential clinical implications

The findings of this study have important clinical implications for managing cognitive function and mental health among rural older adults. The positive association between the Chinese Healthy Eating Index (CHEI) and cognitive function suggests that dietary interventions aimed at improving dietary habits could enhance cognitive health among rural older adults. Healthcare providers should implement personalized nutrition counseling to promote diets rich in vitamins, minerals, and antioxidants, focusing on whole grains, vegetables, fruits, and healthy fats while reducing high-sugar and processed foods. Additionally, the identified chain mediation effect involving psychological balance and depressive symptoms underscores the necessity for a comprehensive care approach, integrating dietary strategies with psychological support services. Regular psychological assessments and counseling within community healthcare settings can help older adults manage stress and emotional challenges. Routine screening for depressive symptoms is also advisable, as it facilitates early detection and management of depression, thereby protecting cognitive function. By incorporating these assessments into a comprehensive care plan, healthcare providers can better address the complex health needs of older adults and improve overall health outcomes.

This study has several strengths, including its large sample size, which allows for valuable insights into the relationships among the Chinese Healthy Eating Index (CHEI), psychological balance, depressive symptoms, and cognitive function in rural older adults. The use of data from the Chinese Longitudinal Healthy Longevity Study (CLHLS) enhances the generalizability of the findings to broader rural populations in China. Additionally, the employment of a chain mediation model provides a comprehensive understanding of the indirect effects of psychological balance and depressive symptoms on the relationship between CHEI and cognitive function, offering advantages over traditional single mediation models. The findings also contribute to the existing literature on elderly health, highlighting potential areas for intervention and informing the development of dietary and psychological strategies to enhance cognitive health. Moreover, the longitudinal family-based nature of the CLHLS data offers a unique perspective on intergenerational and intrafamilial health influences. While this study primarily utilizes cross-sectional data, future analyses incorporating longitudinal data could deepen our understanding of how dietary habits, psychological health, and cognitive function evolve within families over time, potentially revealing generational patterns and the impacts of shared family environments and genetics on these relationships.

This study has several limitations. First, the reliance on cross-sectional data restricts the ability to draw causal inferences regarding the associations between the Chinese Healthy Eating Index (CHEI), psychological balance, depressive symptoms, and cognitive function, as observed relationships may be confounded by other factors. Additionally, the assessment of CHEI and psychological balance is based on self-reported measures, which can introduce reporting bias and affect the accuracy of findings. The measurement of psychological balance relies on current status assessments, potentially limiting the construct’s validity. Furthermore, the specific rural older population sampled may restrict the generalizability of the findings to other populations or cultural contexts, and the absence of weight adjustments for the CLHLS data could influence representativeness, although tests suggest reasonable representation. Residual confounding may also exist, as unaccounted factors could affect the observed relationships, leading to potential over- or underestimation of associations. Lastly, while this study analyzes a cross-sectional snapshot, the longitudinal nature of the CLHLS dataset presents opportunities for future research to explore changes and patterns over time within families, which could enhance understanding of the causal relationships and long-term effects of CHEI on cognitive function, as well as the roles of psychological balance and depressive symptoms throughout the aging process.

In conclusion, while the current study provides valuable insights into the relationships among diet, mental health, and cognitive function in rural older adults, future research utilizing longitudinal data will further illuminate these complex interactions, supporting the development of more effective interventions.

Data availability

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This research utilized data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We appreciate the support of the project team.

Funding

The research was supported by the Support Program for Liaoning Province Social Science Planning Fund Youth Project (L24BSH004).

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Authors and Affiliations

  1. School of Nursing, Jinzhou Medical University, No.40, Section 3, Songpo Road, Linghe District, Jinzhou City, Liaoning Province, People’s Republic of China

    Zhaoquan Jiang, Zhaoxu Xu, Mingyue Zhou, Zhang Huijun & Shixue Zhou

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  1. Zhaoquan Jiang
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  2. Zhaoxu Xu
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Contributions

Zhaoquan Jiang. wrote the main manuscript text and Zhaoquan Jiang. Zhaoxu Xu. Mingyue Zhou. Zhang Huijun. Zhou Shixue. Figures 1, 2 and 3. All authors reviewed the manuscript.

Corresponding author

Correspondence to Shixue Zhou.

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Ethics approval and consent to participate

The data from the CLHLS survey already obtained ethical approval and informed consent and was approved by the Ethics Committee of Peking University (IRB00001052-13074). All participants or their surrogate respondents provided written informed consent.

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Not applicable.

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The authors declare no competing interests.

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Jiang, Z., Xu, Z., Zhou, M. et al. The influence of healthy eating index on cognitive function in older adults: chain mediation by psychological balance and depressive symptoms. BMC Geriatr 24, 904 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-024-05497-x

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Keywords

BMC Geriatrics

ISSN: 1471-2318

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