The role of anxiety in the association between nutrition literacy and health-related quality of life among college students
Health-related quality of life (HRQOL) reflects the physical and mental health of an individual or group over a given period and is increasingly recognized as an important health outcome, especially in populations undergoing significant life transitions . College students represent one such population, navigating a crucial period of development marked by the transition to adulthood, alongside various personal, academic, and environmental changes . Actively promoting quality of life among college students is key to preventing adverse health outcomes during college and in the long term . However, college students suffer from poor mental health, including highly prevalent, diagnosable psychiatric disorders . This may be due to the prevalence of many predictors and sources of psychological disorders such as stress, depression, and anxiety in the college environment . Thus, the HRQOL of college students does not give cause for optimism. Given the growing number of college students worldwide and the increasing recognition of mental health challenges within this demographic, it is essential to identify modifiable determinants of HRQOL and develop effective interventions to promote it. One modifiable factor that has gained increasing attention is the relationship between nutrition and mental health. Nutrition literacy (NL), the ability to understand and apply nutritional information , can influence food choices that directly impact gut microbiota and overall gut health. Diets rich in fiber, fruits, vegetables, and fermented foods promote the growth of beneficial gut bacteria , , while diets high in processed foods can contribute to dysbiosis , . The microbiota can influence brain function by producing neurotransmitters, modulating stress responses, and interacting with the immune system . Disruptions in gut health, such as dysbiosis (imbalance in gut bacteria), have been associated with increased levels of anxiety and mood disorders . Thus, improving NL may lead to healthier dietary patterns, potentially reducing the risk of anxiety. While these studies suggest a connection between NL and anxiety, no research has directly explored this association. Systematic reviews have indicated that anxiety is an important factor affecting HRQOL . Some studies suggested that anxiety disorders adversely affect the HRQOL of college students , . Moreover, another study found that a high-quality diet may be associated with a lower risk of stress and depression and better HRQOL . These findings suggest a strong connection between NL and HRQOL. Previous research has shown that NL was related to HRQOL in patients . A recent study from Turkey showed the positive impact of improved NL on HRQOL in adults . However, further studies are needed to confirm this in college students. Additionally, the exact factors mediating this association remain unknown. Given that anxiety is associated with NL and HRQOL, we hypothesized that anxiety may be a mediating factor, and there may be an interaction between NL and anxiety on HRQOL. Therefore, we conducted a cross-sectional study to investigate the relationship between NL, HRQOL, and anxiety in college students, to evaluate the mediating effect of anxiety on the association, and to examine the interaction between NL and anxiety on HRQOL. 

Study participants This cross-sectional study was conducted from September to November 2023 and included college students from any university in Mainland China. The exclusion criteria were a questionnaire completion time of less than 180 s, a weight of less than 30 kg or more than 150 kg with abnormal signs, a height of less than 130 cm or more than 200 cm with abnormal signs, and incomplete basic information. These exclusion criteria were implemented to improve the accuracy and reliability of the findings by ensuring the sample represented a typical population of college students in Mainland China. Potential eligible college students were invited to participate in this survey through several social media platforms (Xiaohongshu, WeChat, QQ, Douban, Sina Weibo), and incentives were offered to complete the questionnaire. Sharing of the questionnaire was also encouraged. A total of 2194 college students completed the online survey. However, 128 participants were excluded based on the criteria, resulting in a sample of 2,066 participants. The survey was organized and implemented via the “Wenjuanxing” platform, which is compatible with computers, mobile phones, and tablets. The survey was conducted anonymously, and participants were required to check a box on their device screen to provide online informed consent. The study was approved by the institutional review board of the Zunyi Medical University (approval # [2023] 1-256). All methods were performed in accordance with the relevant guidelines and the Law on the Rights and Interests of College Students. Assessment of questionnaire This study obtained demographic information from college students, encompassing variables such as sex, major, ethnicity, only-child status, place of origin, grade, father’s occupation, mother’s occupation, academic performance, average monthly household income, expenditure per month (RMB), BMI, and sick leave. NL among college students was assessed using the Food and Nutrition Literacy Questionnaire for Chinese Adults (FNLQ), developed by the Nutritional Literacy Project Group in China. The FNLQ evaluated NL across four dimensions: food and nutrition knowledge (5 items), access to, planning, and selecting food (15 items), preparing and making food (11 items), and eating (19 items). This questionnaire has previously been validated for good reliability and validity in the Chinese population . The total Cronbach’s alpha coefficient for this sample was 0.822 (> 0.7), indicating acceptable internal consistency. All items were scored based on the correctness level, from low to high. For Likert-5 scale items, scores of 0, 0.5, 1, 1.5, and 2 points were assigned; for other items, a correct answer scored 2 points. Higher scores indicated a higher level of food and nutrition knowledge. The total score on the FNLQ scale was 100 points. There is a lack of a sufficient basis for developing cut-off values for NL, so we used the median value as a threshold value to categorize NL into low and high levels, as in previous studies , . The Generalized Anxiety Disorder (GAD-7) scale was used to assess anxiety levels. This scale was structured on a 4-point Likert scale, with each of its 7 items scored from 0 (not at all) to 3 (nearly every day); higher scores indicated more severe symptoms . A score of 10 or above served as the cutoff point for the diagnosis of anxiety disorders . The Chinese version of the GAD-7 has demonstrated good psychometric properties in a sample of internal medicine patients . In this sample, the Cronbach’s alpha coefficient was 0.920. The measurement of HRQOL in our study was based on the SF-12 scale, which was a condensed version of the SF-36 scale . This questionnaire was divided into two dimensions (the Physical Component Summary [PCS] and Mental Component Summary [MCS]) and eight domains. To enable comparison of study results across cultures, we utilized the U.S. population norms for SF-12 to measure PCS and MCS, which had a mean of 50 and a standard deviation of 10 , . HRQOL levels were determined by the sum of the standardized PCS and MCS scores. Higher scores indicated better HRQOL; scores above the median signified a high level, whereas scores below the median indicated a low level. This scale has been frequently used to measure the HRQOL of Chinese college students with good reliability and validity , . Moreover, the SF-12 scale has been validated and found to be both valid and equivalent for use in a Chinese population . Data analysis Data analysis was conducted using SPSS for Windows (version 26.0; IBM Corporation, Armonk, NY, USA), AMOS for Windows (version 24.0; IBM Corporation, Armonk, NY, USA), and R statistical software version 4.3.3 (R Foundation). Categorical variables were expressed as percentages and measurement data were presented as mean ± standard deviation. Differences in categorical variables were compared using the chi-square test. Multiple logistic regression models were used to assess the association of NL and anxiety, NL and HRQOL, and anxiety and HRQOL. Three models were constructed, including Model 1 (crude), Model 2 (adjusted sex, grade), and Model 3 (adjusted sex, major, grade, academic performance, place of origin, sick leave, father’s occupation, BMI). Additionally, subgroup analyses were conducted to explore the heterogeneity in the strength of the association between NL and HRQOL, NL and anxiety. Structural equation modeling (SEM) was used to measure model fit indices and path coefficients (Fig. ), analyzing the mediating role of anxiety. Total scores of NL and anxiety were treated as latent variables, while the four dimensions of NL, seven items of anxiety, and HRQOL were considered measurement variables. Model fit was typically assessed using the CMIN/DF, GFI, AGFI, RMSEA, IFI, CFI, TLI and SRMR , . Reference values are presented in Table . We evaluate additive interaction effects using three different metrics: relative excess risk due to interaction (RERI), interaction proportion (AP), and synergy index (SI). When RERI > 0, AP > 0, and SI > 1, this signified that the combined effects of NL and anxiety on HRQOL exceed the sum of their individual effects, suggesting synergistic effects. We computed the corresponding 95% CIs for these three metrics using the delta method. An alpha level of 0.05 was used, and the tests were two-tailed. 

This cross-sectional study was conducted from September to November 2023 and included college students from any university in Mainland China. The exclusion criteria were a questionnaire completion time of less than 180 s, a weight of less than 30 kg or more than 150 kg with abnormal signs, a height of less than 130 cm or more than 200 cm with abnormal signs, and incomplete basic information. These exclusion criteria were implemented to improve the accuracy and reliability of the findings by ensuring the sample represented a typical population of college students in Mainland China. Potential eligible college students were invited to participate in this survey through several social media platforms (Xiaohongshu, WeChat, QQ, Douban, Sina Weibo), and incentives were offered to complete the questionnaire. Sharing of the questionnaire was also encouraged. A total of 2194 college students completed the online survey. However, 128 participants were excluded based on the criteria, resulting in a sample of 2,066 participants. The survey was organized and implemented via the “Wenjuanxing” platform, which is compatible with computers, mobile phones, and tablets. The survey was conducted anonymously, and participants were required to check a box on their device screen to provide online informed consent. The study was approved by the institutional review board of the Zunyi Medical University (approval # [2023] 1-256). All methods were performed in accordance with the relevant guidelines and the Law on the Rights and Interests of College Students. 

This study obtained demographic information from college students, encompassing variables such as sex, major, ethnicity, only-child status, place of origin, grade, father’s occupation, mother’s occupation, academic performance, average monthly household income, expenditure per month (RMB), BMI, and sick leave. NL among college students was assessed using the Food and Nutrition Literacy Questionnaire for Chinese Adults (FNLQ), developed by the Nutritional Literacy Project Group in China. The FNLQ evaluated NL across four dimensions: food and nutrition knowledge (5 items), access to, planning, and selecting food (15 items), preparing and making food (11 items), and eating (19 items). This questionnaire has previously been validated for good reliability and validity in the Chinese population . The total Cronbach’s alpha coefficient for this sample was 0.822 (> 0.7), indicating acceptable internal consistency. All items were scored based on the correctness level, from low to high. For Likert-5 scale items, scores of 0, 0.5, 1, 1.5, and 2 points were assigned; for other items, a correct answer scored 2 points. Higher scores indicated a higher level of food and nutrition knowledge. The total score on the FNLQ scale was 100 points. There is a lack of a sufficient basis for developing cut-off values for NL, so we used the median value as a threshold value to categorize NL into low and high levels, as in previous studies , . The Generalized Anxiety Disorder (GAD-7) scale was used to assess anxiety levels. This scale was structured on a 4-point Likert scale, with each of its 7 items scored from 0 (not at all) to 3 (nearly every day); higher scores indicated more severe symptoms . A score of 10 or above served as the cutoff point for the diagnosis of anxiety disorders . The Chinese version of the GAD-7 has demonstrated good psychometric properties in a sample of internal medicine patients . In this sample, the Cronbach’s alpha coefficient was 0.920. The measurement of HRQOL in our study was based on the SF-12 scale, which was a condensed version of the SF-36 scale . This questionnaire was divided into two dimensions (the Physical Component Summary [PCS] and Mental Component Summary [MCS]) and eight domains. To enable comparison of study results across cultures, we utilized the U.S. population norms for SF-12 to measure PCS and MCS, which had a mean of 50 and a standard deviation of 10 , . HRQOL levels were determined by the sum of the standardized PCS and MCS scores. Higher scores indicated better HRQOL; scores above the median signified a high level, whereas scores below the median indicated a low level. This scale has been frequently used to measure the HRQOL of Chinese college students with good reliability and validity , . Moreover, the SF-12 scale has been validated and found to be both valid and equivalent for use in a Chinese population . 

Data analysis was conducted using SPSS for Windows (version 26.0; IBM Corporation, Armonk, NY, USA), AMOS for Windows (version 24.0; IBM Corporation, Armonk, NY, USA), and R statistical software version 4.3.3 (R Foundation). Categorical variables were expressed as percentages and measurement data were presented as mean ± standard deviation. Differences in categorical variables were compared using the chi-square test. Multiple logistic regression models were used to assess the association of NL and anxiety, NL and HRQOL, and anxiety and HRQOL. Three models were constructed, including Model 1 (crude), Model 2 (adjusted sex, grade), and Model 3 (adjusted sex, major, grade, academic performance, place of origin, sick leave, father’s occupation, BMI). Additionally, subgroup analyses were conducted to explore the heterogeneity in the strength of the association between NL and HRQOL, NL and anxiety. Structural equation modeling (SEM) was used to measure model fit indices and path coefficients (Fig. ), analyzing the mediating role of anxiety. Total scores of NL and anxiety were treated as latent variables, while the four dimensions of NL, seven items of anxiety, and HRQOL were considered measurement variables. Model fit was typically assessed using the CMIN/DF, GFI, AGFI, RMSEA, IFI, CFI, TLI and SRMR , . Reference values are presented in Table . We evaluate additive interaction effects using three different metrics: relative excess risk due to interaction (RERI), interaction proportion (AP), and synergy index (SI). When RERI > 0, AP > 0, and SI > 1, this signified that the combined effects of NL and anxiety on HRQOL exceed the sum of their individual effects, suggesting synergistic effects. We computed the corresponding 95% CIs for these three metrics using the delta method. An alpha level of 0.05 was used, and the tests were two-tailed. 

Study participant characteristics This study included 2,066 college students. Among these students, 69.5% were female and 30.5% were male. The occurrence of anxiety disorder was 9.8%. The average NL score was 64.01 points. The average HRQOL score was 92.89 points, with 41% and 36.7% meeting the standard for PCS and MCS, respectively. High NL accounted for 49.2%, and high HRQOL accounted for 50.2% of students. College students with high NL and HRQOL were less likely to suffer from anxiety disorders (Table ). Association between NL and HRQOL Using the median as the boundary, the relationship between different levels of NL and HRQOL was further analyzed. The univariate analysis (Model 1) showed a significant association. After adjusting for sex, major, grade, academic performance, place of origin, sick leave, father’s occupation, BMI (Model 3), college students with high NL levels were 2.52 times more likely to have a high HRQOL than college students with low levels (OR = 2.52, 95% CI: 2.09–3.03, p < 0.001) (Table ). After adjusting for potential covariates, subgroup analyses consistently revealed a significant positive correlation between NL and HRQOL levels across all subgroups (all p-interaction > 0.05) (Figure ). Association between NL and anxiety From the univariate analysis, we observed a significant correlation between NL and anxiety among college students (Model 1). After adjusting for sex, major, grade, academic performance, place of origin, sick leave, father’s occupation, BMI (Model 3), Participants with high NL were 47% less likely to suffer from anxiety disorders compared to those with low NL (OR = 0.53, 95% CI: 0.39–0.73, p < 0.001) (Table ). Subgroup analyses consistently revealed a significant negative correlation between NL and anxiety across all subgroups (all p-interaction > 0.05) (Figure S2). Association between HRQOL and anxiety From the univariate analysis, we observed a significant association between anxiety and HRQOL (Model 1). After adjusting for sex, major, grade, academic performance, place of origin, sick leave, father’s occupation, BMI (Model 3), Students with anxiety disorders were 84% less likely to have high HRQOL compared to those without anxiety disorders (OR = 0.16, 95% CI: 0.11–0.24, p < 0.001) (Table ). SEM analysis of NL and HRQOL with anxiety as a mediating variable Owing to the large sample size, the asymptotic distribution-free method was employed to estimate the SEM, with NL as the independent variable, HRQOL as the dependent variable, and anxiety as the mediating variable. The fit indices for the model were CMIN/DF = 3.169, GFI = 0.978, AGFI = 0.964, RMSEA = 0.032, IFI = 0.930, CFI = 0.929, TLI = 0.900, and SRMR = 0.034, indicating a reasonable fit and lending credibility to the model results. The standardized path coefficients (Fig. ) indicated that NL significantly positively predicted the HRQOL of college students (β = 0.258, p < 0.001). Concurrently, NL had a significant negative impact on anxiety (β = −0.204, p < 0.001), which in turn significantly negatively affected HRQOL (β = −0.495, p < 0.001). Based on the SEM, the mediating effect of anxiety was tested using bias-corrected percentile Bootstrap resampling 2000 times , with results shown in Table . The results revealed that the direct, indirect, and total effects of NL on college students’ HRQOL are positive and significant. The direct effect of NL on HRQOL was significant, and anxiety partially mediated the impact of NL on HRQOL. The direct effect accounts for 71.87% of the total effect, while the indirect effect mediated by anxiety accounts for 28.13%, which is less than the direct effect. Interaction analyses of NL and anxiety with HRQOL Significant additive interactions were found between NL and anxiety (RERI = 6.96, 95% CI: 2.74–11.17; AP = 0.51, 95% CI: 0.37–0.64; SI = 2.21, 95% CI: 1.58–3.07), but the significance of the multiplicative interaction was not found (OR = 1.32, 95% CI: 0.49–2.62, p = 0.770) (Table ). 

This study included 2,066 college students. Among these students, 69.5% were female and 30.5% were male. The occurrence of anxiety disorder was 9.8%. The average NL score was 64.01 points. The average HRQOL score was 92.89 points, with 41% and 36.7% meeting the standard for PCS and MCS, respectively. High NL accounted for 49.2%, and high HRQOL accounted for 50.2% of students. College students with high NL and HRQOL were less likely to suffer from anxiety disorders (Table ). 

Using the median as the boundary, the relationship between different levels of NL and HRQOL was further analyzed. The univariate analysis (Model 1) showed a significant association. After adjusting for sex, major, grade, academic performance, place of origin, sick leave, father’s occupation, BMI (Model 3), college students with high NL levels were 2.52 times more likely to have a high HRQOL than college students with low levels (OR = 2.52, 95% CI: 2.09–3.03, p < 0.001) (Table ). After adjusting for potential covariates, subgroup analyses consistently revealed a significant positive correlation between NL and HRQOL levels across all subgroups (all p-interaction > 0.05) (Figure ). 

From the univariate analysis, we observed a significant correlation between NL and anxiety among college students (Model 1). After adjusting for sex, major, grade, academic performance, place of origin, sick leave, father’s occupation, BMI (Model 3), Participants with high NL were 47% less likely to suffer from anxiety disorders compared to those with low NL (OR = 0.53, 95% CI: 0.39–0.73, p < 0.001) (Table ). Subgroup analyses consistently revealed a significant negative correlation between NL and anxiety across all subgroups (all p-interaction > 0.05) (Figure S2). 

From the univariate analysis, we observed a significant association between anxiety and HRQOL (Model 1). After adjusting for sex, major, grade, academic performance, place of origin, sick leave, father’s occupation, BMI (Model 3), Students with anxiety disorders were 84% less likely to have high HRQOL compared to those without anxiety disorders (OR = 0.16, 95% CI: 0.11–0.24, p < 0.001) (Table ). 

Owing to the large sample size, the asymptotic distribution-free method was employed to estimate the SEM, with NL as the independent variable, HRQOL as the dependent variable, and anxiety as the mediating variable. The fit indices for the model were CMIN/DF = 3.169, GFI = 0.978, AGFI = 0.964, RMSEA = 0.032, IFI = 0.930, CFI = 0.929, TLI = 0.900, and SRMR = 0.034, indicating a reasonable fit and lending credibility to the model results. The standardized path coefficients (Fig. ) indicated that NL significantly positively predicted the HRQOL of college students (β = 0.258, p < 0.001). Concurrently, NL had a significant negative impact on anxiety (β = −0.204, p < 0.001), which in turn significantly negatively affected HRQOL (β = −0.495, p < 0.001). Based on the SEM, the mediating effect of anxiety was tested using bias-corrected percentile Bootstrap resampling 2000 times , with results shown in Table . The results revealed that the direct, indirect, and total effects of NL on college students’ HRQOL are positive and significant. The direct effect of NL on HRQOL was significant, and anxiety partially mediated the impact of NL on HRQOL. The direct effect accounts for 71.87% of the total effect, while the indirect effect mediated by anxiety accounts for 28.13%, which is less than the direct effect. 

Significant additive interactions were found between NL and anxiety (RERI = 6.96, 95% CI: 2.74–11.17; AP = 0.51, 95% CI: 0.37–0.64; SI = 2.21, 95% CI: 1.58–3.07), but the significance of the multiplicative interaction was not found (OR = 1.32, 95% CI: 0.49–2.62, p = 0.770) (Table ). 

To the best of our knowledge, we are the first to report a positive association between NL and HRQOL, and a negative association between NL and anxiety in college students. Additionally, anxiety partly mediated the association between NL and HRQOL. Moreover, there was a synergy between NL and anxiety. College students may develop poor dietary habits, which increases their future risk of chronic diseases , . Research highlights the crucial role of NL in shaping the dietary behaviors of college students and their adaptation to the university food environment . Furthermore, college students are key in disseminating nutritional knowledge . Our findings provide a scientific basis for nutritional intervention among college students to improve their HRQOL. Although no study has investigated the association between NL and HRQOL among college students, a few studies report the impact of NL on HRQOL in other populations. Recently, a cross-sectional study of 1,379 adults in Turkey found that as the NL level of the participants increased, their quality of life also increased. This suggests that improving NL may positively affect quality of life . A positive association was also observed in patients. Li et al. noted that NL was not only associated with nutritional status but also with quality of life in patients with end-stage kidney disease undergoing dialysis . Another study also reported that NL was highly positively correlated with quality of life in diabetic patients . Our study confirmed these results. We found that college students with high NL levels were 2.52 times more likely to achieve high HRQOL than those with low levels. However, how NL affects HRQOL remains unclear. Low NL means overall less access to healthy foods, which increases the pressure on college students to adapt and succeed on campus, while a decrease in diet quality also contributes to brain damage . Vajdi et al. revealed correlations between healthy dietary patterns and better HRQOL dimension scores, whereas unhealthy dietary patterns are associated with lower life quality scores . In addition, an unhealthy diet had a negative impact on the weight status of college students, which may lead to a lack of self-confidence . We are also the first to find a negative association between NL and anxiety. College students with high NL were 0.53 times more likely to suffer from anxiety disorders than those with low NL. This result was consistent with the association between NL and depression. A pilot cross-sectional study from Pakistan showed that individuals with a high NL were less likely to be depressed (OR = 0.48; 95% CI = 0.24, 0.95) than those with a low NL . Additionally, some studies observed that health literacy exerted a protective effect in reducing anxiety and stress , . Therefore, we believe that NL plays an important role in the prevention of anxiety among college students. Good NL is considered a determining factor in following a healthy diet . Unhealthy diets, such as those containing processed foods, are rich in excess saturated and trans fatty acids, which increase the risk of inflammation and induce gut microbiota dysfunction . Pro-inflammatory foods, higher inflammatory marker levels, and gut microbiota dysfunction play a role in the development of anxiety , . However, the specific mechanism needs further study. A novel finding in this study was that NL indirectly affected HRQOL through anxiety, in addition to its direct effect, that is, there was an indirect positive correlation mediated by anxiety. As MacKinnon and others suggest , a mediating variable reduces the magnitude of the direct effect and highlights the significance of the mediator. In this study, when the mediating effect of anxiety was not considered, the standardized path coefficient of NL on the HRQOL of college students was 0.37, with the model explaining 13% of the variance in HRQOL. However, upon incorporating the mediating variable of anxiety, the standardized path coefficient was reduced to 0.26, but the explanatory power of the model for HRQOL increased to 36%. This underscores the significance of anxiety as a mediating variable in elucidating the HRQOL among college students. The mediating effect of anxiety on quality of life has been widely validated in previous studies. Zhang et al. confirmed that anxiety symptoms were a significant mediating factor between adult attention-deficit/hyperactivity disorder and quality of life . Another study observed that less social deprivation was directly, and indirectly through less anxiety, associated with better HRQOL in asthma . Although we found the direct effect accounts for most of the total effect, reiterating the crucial role of NL in determining quality of life, the mediating effect of anxiety could not be ignored. Recent studies have identified a higher incidence of anxiety symptoms among college students, compared to the general population . A systematic review of longitudinal observational studies also proved that all anxiety disorders were associated with reduced quality of life . We also observed that college students with anxiety disorders were 0.16 times as likely to have high HRQOL than college students without anxiety disorders. College students with anxiety disorders may not be able to handle interpersonal relationships well, thus failing to maintain good relationships with family, friends, teachers, and students. It can even lead to an increase in suicidal thoughts, which are important factors that threaten the HRQOL . Additionally, sources of stress, such as academic burden, persistent success pressure, peer competition, and lack of leisure time , inevitably contribute to lower levels of student quality of life. Low NL levels imply poorer quality dietary patterns, which are associated with increased risk of anxiety . Our study uncovers a novel pathway that NL can enhance HRQOL by alleviating anxiety in college students. Another novelty of our study is to examine the interaction between NL and anxiety. Our study observed there was a synergistic effect between NL and anxiety on HRQOL due to significant additive interaction. It indicated the combined effect of low NL and anxiety was greater than the sum of their individual effects on poorer HRQOL. As studies revealed an association between less anxiety and more dietary constituent , it suggests that there are many students with coexisting low nutritional status and psychological disorders, who may have more serious HRQOL. Taking nutritional intervention measures to improve HRQOL, we should pay more attention to college students with coexisting low NL and anxiety. In addition, since anxiety is difficult to intervene in, we should reduce the effect of anxiety on HRQOL by intervening in NL. However, more research is needed to further explore the interaction between nutrition and mental health and the underlying mechanisms. Limitations We acknowledge some study limitations. First, this was a cross-sectional study; therefore, a causal relationship of NL with the HRQOL and anxiety could not be established and should be verified by further longitudinal studies. Second, this study was conducted during the fall semester; thus, the HRQOL and anxiety measures may not represent the average health and well-being throughout an academic year. Additionally, this investigation was limited to China, and the findings cannot be generalized to other populations. Third, the data were collected through electronic self-reporting, which may introduce response biases. Finally, although we have adjusted for several confounding factors, residual confounding remains unavoidable owing to missing adjustments for some unmeasured factors. Conclusion Higher levels of NL are associated with better HRQOL and lower risk of anxiety among college students. Additionally, anxiety partly mediates the association between NL and HRQOL, and our study is a crucial first step toward elucidating this important mediating role. Furthermore, there is a synergistic effect between NL and anxiety. This suggests that we should pay more attention to individuals with coexisting low nutrition and psychological disorders. 

We acknowledge some study limitations. First, this was a cross-sectional study; therefore, a causal relationship of NL with the HRQOL and anxiety could not be established and should be verified by further longitudinal studies. Second, this study was conducted during the fall semester; thus, the HRQOL and anxiety measures may not represent the average health and well-being throughout an academic year. Additionally, this investigation was limited to China, and the findings cannot be generalized to other populations. Third, the data were collected through electronic self-reporting, which may introduce response biases. Finally, although we have adjusted for several confounding factors, residual confounding remains unavoidable owing to missing adjustments for some unmeasured factors. 

Higher levels of NL are associated with better HRQOL and lower risk of anxiety among college students. Additionally, anxiety partly mediates the association between NL and HRQOL, and our study is a crucial first step toward elucidating this important mediating role. Furthermore, there is a synergistic effect between NL and anxiety. This suggests that we should pay more attention to individuals with coexisting low nutrition and psychological disorders. 

Below is the link to the electronic supplementary material. Supplementary Information. 

