Abstract
Background
Neuropsychiatric disorders are highly prevalent, significantly impacting patients' Quality of Life. Probiotics can modulate the balance of gut flora, ameliorating neuropsychiatric disorders and ultimately reducing Oxidative Stress (OS) and inflammatory responses. Herein, we aimed to determine the associations of probiotics, prebiotics, synbiotics, and yogurt supplements with Oxidative Balance Scores (OBS) and all-cause and cardiovascular mortalities in neuropsychiatric disorders.
Methods
This study utilized the National Health and Nutrition Examination Survey (NHANES) 2007–2018 data, with 13,857 participants included in the final analysis. Probiotics supplements intakes, OBS values, depression, sleep disturbances, and cognitive function were assessed based on questionnaires and laboratory data. Logistic regression, mediation effects analysis, and COX regression modeling were employed to explore these supplements' associations with OBS values in relation to mortality linked to depression, sleep disorders, and cognitive dysfunction.
Results
The intake of probiotics was positively correlated with OBS, indicating that the subjects who took probiotic supplements had healthier dietary habits and lifestyles. Mediation analysis revealed that probiotics could improve depressive symptoms (mediation effect = 28.03%, p = 0.024) and cognitive function (mediation effects = 9.26%, 14.64%, and 18.63%, respectively; p < 0.05) by reducing inflammatory responses. Furthermore, probiotic intake correlated negatively with all-cause mortality at the levels of depression, sleep disorders, and cognitive functioning [Hazard Ratio (HR) = 0.874, 0.906, and 0.810, respectively] and cardiovascular mortality related to depression and cognitive dysfunction (HR = 0.963 and 0.403, respectively).
Conclusion
Probiotics, prebiotics, synbiotics, and yogurt supplements may reduce inflammatory responses and OS, potentially alleviating neuropsychiatric disorders and improving patients' Survival Rates.
Keywords: Probiotic, Oxidative balance scores, All-cause mortality, Cardiovascular mortality, Neuropsychiatric disorders
Graphical abstract
1. Introduction
Neuropsychiatric disorders (including depression, sleep disorders, and cognitive dysfunction, among others) are highly prevalent, significantly impacting patients' Quality of Life (QoL) and potentially causing death in severe cases. Presently, in the United States alone, the prevalence of these illnesses stands at >10%, further highlighting their significant physical and mental impacts on the global population [1]. Notably, neuropsychiatric disorders have been linked to significantly shorter life spans, a phenomenon somewhat attributable to the patients being more susceptible to Cardiovascular Disease (CVD) and cancer, among other illnesses, which could also lead to poorer treatment outcomes [2], [3]. Furthermore, the high morbidity and mortality rates associated with neuropsychiatric disorders have become the leading cause of disability worldwide, imposing a significant economic burden on society [4], [5]. Moreover, the relationship between neuropsychiatric symptoms and gut microbes is well-documented [6], [7], [8], [9]. In this regard, it is noteworthy that the use of probiotics in targeting gut microbial imbalances has emerged as a potential therapeutic avenue for managing various neuropsychiatric disorders.
The numerous microorganisms in the human gut have a bidirectional communication relationship with multiple body organs or systems [10], [11]. Besides significantly influencing host nutrition, metabolic and immune functions, and redox levels, these gut microbiota could also induce physiological changes in the brain, modulating the Microbiota-Gut-Brain (MGB) axis and ultimately impacting mood and behavior [12]. Furthermore, gut structure damage could lead to the activation of non-specific immune responses, increasing inflammatory factor release and inducing a systemic inflammatory response, phenomena closely linked to the onset of depression, sleep disorders, and cognitive dysfunction [13]. Notably, probiotic supplementation was reported to improve the body's Gastrointestinal (GI) function and maintain MGB homeostasis, reducing stress and neuroinflammation. For instance, Lactobacillus plantarum P8, a probiotic bacterium, reduced pro-inflammatory cytokine concentration in the body, improving depression, memory function, and cognitive symptoms in healthy adults [14]. This finding implies that probiotics and other pertinent interventions could attenuate depression, sleep disorders, and cognitive dysfunction in humans.
Oxidative Stress (OS) is a phenomenon that results from an imbalance between the production of Reactive Oxygen Species (ROS) and their removal via protective mechanisms, potentially leading to chronic inflammation [15]. According to research, OS can activate various Transcription Factors (TFs), leading to the differential expression of certain genes involved in inflammatory pathways [16]. Therefore, monitoring the balance could be essential for disease prevention and health management. The Oxidative Homeostasis Score (OHS) [17], a composite index that combines measures of multiple oxidative and antioxidant factors to provide a composite score, could be used to assess an individual's OS levels. Generally, a higher Oxidative Balance Score (OBS: 0–40 points; The higher the score, the higher the level of antioxidant exposure) value indicates the body's stronger antioxidant defenses, effectively neutralizing ROS and reducing oxidative and inflammatory responses. Notably, appropriate dietary habits and lifestyles could improve the OBS, reducing the body's OS levels, and thus preventing and improving neuropsychiatric symptoms.
To the best of our knowledge, no studies have examined the relationship between probiotics and OBS, forming the basis of this study. Specifically, using National Health and Nutrition Examination Survey (NHANES) data, we sought to explore the mediating role of OBS in the relationship between probiotics and neuropsychiatric disorders (depression, sleep disorders, and cognitive dysfunction), as well as the relationship between probiotics and all-cause and cardiovascular mortalities in such patients.
2. Methods
2.1. Study population
The Center for Disease Control and Prevention (CDC) oversees NHANES, which assesses the health and nutritional status of the U.S. population across five different dimensions: Demographics, dietary data, screening data, laboratory data, and questionnaires. This cross-sectional study examined a representative sample from the NHANES 2007–2018 dataset. Of the 59,842 individuals initially recruited, only 13,857 were included in the final analysis after applying the exclusion criteria which encompassed: (1) Incomplete data on probiotics, prebiotics, synbiotics, and yogurt; (2) Missing OHS calculation data; (3) Individuals aged ≤20 years; and (4) Incomplete data for other covariates. Fig. 1 shows the study flow chart.
Fig. 1.
Flowchart portryaying research participants.
2.2. Probiotics, prebiotics, synbiotics, and yogurt supplements
Probiotics-containing dietary supplements were assessed using the 30-Day-Individual Dietary Supplement questionnaire [18]. Day 1 and day 2 individual dietary interviews were used to assess yogurt consumption (except frozen yogurt). Participants were then categorized into two groups: Consumption (who consumed one or more of the above supplements) and non-consumption (who did not consume the aforementioned supplements).
2.3. OBS
The OBS in our study is bifurcated into dietary oxidative balance score (DOBS) and lifestyle oxidative balance score (LOBS). DOBS encompasses 16 nutrients derived from the initial dietary review of NHANES, including dietary fiber, carotenoids, riboflavin, niacin, vitamins C, E, B6, B12, total folate, calcium, magnesium, zinc, copper, selenium, total fat, and iron. LOBS factors in physical activity, alcohol consumption, smoking and body mass index (BMI). Among them, 15 are antioxidant factors except total fat, iron, Body Mass Index (BMI), alcohol intake, and cotinine levels. Herein, 16 dietary nutrient factors were assessed using the Dietary Interview-Individual Foods questionnaire and Day 1 and Day 2 Individual Foods files. Physical activity was assessed based on weekly frequency and exercise duration and metabolic equivalent scores for physical activity. Demographic variables were used to calculate BMI data. Smoking was measured based on cotinine levels and alcohol intake was assessed using the Dietary Interview-Individual Foods questionnaire and the Day 1 and Day 2 Individual Foods profiles.
The participants were further categorized into three groups based on their BMI data as outlined in previous literature [19]: Normal (25.6 and <24.3 kg/m2 for men and women, respectively), overweight (25.6–30 and 24.3–30.1 kg/m2 for men and women, respectively), and obese (≥30 and ≥30.1 kg/m2 for men and women, respectively). There was also a BMI-based scale with scores of 2, 1, and 0 for normal, overweight, and obese, respectively. All other components of the OBS were graded per the corresponding data and gender-stratified. Antioxidant and pro-oxidant factors were scored on a scale of 0–2 and 2–0, respectively, with higher scores indicating higher antioxidant exposure. Supplementary Table 1 details the scoring scheme for the OBS.
2.4. Depression, sleep disturbance, and cognitive functioning levels
We assessed depressive symptoms and quantified depression using the PHQ-9, based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. The PHQ-9 is a self-report tool that has been adequately validated in assessing depressive symptoms occurring within the last two weeks and has sensitivity and specificity values of 88% each in defining depression. Herein, subjects with PHQ-9 scores <10 and ≥10 were categorized into the no-depression and depression groups, respectively. Sleep disturbance was assessed using the Sleep Disturbance Questionnaire based on questions such as, “Have you ever been told by a doctor that you have a sleep disturbance?” or “Ever been told by a doctor that you have a sleep disorder?”. Participants underwent three cognitive function tests, including the Creation of the Alzheimer's Registry Association Word Learning Subtest (CERAD W-L), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST). Means and Standard Deviations (SDs) were used to determine standardized scores for each cognitive test, including CERAD W-L immediate memory (IRT), CERAD W-L delayed memory (DRT), AFT, and DSST. The standardized scores for the 4 tests were averaged to obtain the total cognitive functioning scores [20].
2.5. Mortality ascertainment
Mortality data were obtained from the CDC's National Death Index (NDI) database. The follow-up period was from the date of the baseline interview to death or December 31, 2019 (the date of the most recent update to the mortality index database). The International Classification of Diseases, 10th Edition (ICD-10) codes were used, of which codes I00-I09, I11, and I13 I20-I51 identify participants who died of Cardiovascular Diseases (CVDs).
2.6. Covariates
Herein, the covariates used were age, gender, race (Mexican American, other Hispanic, non-Hispanic white, non-Hispanic black, and other race), education level (<high school, high school or equivalent, and >high school), marital status (married, unmarried, cohabitating, and others), Poverty-to-Income Ratio (PIR), hypertensive disorders, CVD, and cancer. The Mean Blood Pressure (MBP) equalled the average of the first three measured Blood Pressure (BP) readings. If there was only one BP reading, it was considered as the average, and if there were two BP readings, only their average was calculated. Patients with a Mean Systolic Blood Pressure (MSBP) of ≥140 mmHg or a Mean Diastolic Blood Pressure (MDSP) of ≥90 mmHg were diagnosed with Hypertension (HTN). The following conditions also resulted in an HTN diagnosis: (1) Currently on anti-HTN medication; (2) Answered “yes” to the question “Has a doctor or other health professional told you that you have high blood pressure?”; (3) Answered “yes” to the question “Has a doctor or other health professional ever told you that you have high blood pressure?”; and (4). Answered “yes” to the question “Has a doctor or other health professional ever told you that you have coronary heart disease, angina, stroke, congestive heart failure, or heart attack?” A CVD diagnosis was also made if the patients answered “yes” to a pertinent question. Similarly, answering “yes” to the question “Has a doctor or other health professional ever told you that you have cancer?” or “Have you been told by a doctor or other health professional that you have cancer?” led to a cancer diagnosis.
2.7. Statistical analysis
For baseline characteristics, continuous and categorical variables were expressed as Mean ± Standard Deviation (x ± s) and counts (%), respectively; with their between-group differences and overall characteristics analyzed using t-tests and chi-square tests, respectively. The statistical analyses incorporated sample weights, clustering, and stratification due to the complex multistage stratified probability survey design employed in the NHANES. Three models were used to adjust for confounders in the binary logistic regression analysis: Model 1 (unadjusted), Model 2 (adjusted for age, gender, race, educational attainment, marital status, and poverty ratio), and Model 3 (further adjusted for HTN, CVD, and cancer based on Model 2). Mediation models were constructed with probiotics, prebiotics, synbiotics, and yogurt as the exposure variables, depression, sleep disorders, and cognitive function levels as the outcome variables, and the OBS as a potential mediator. The ratio of indirect effect to total effect indicated the mediating effect's magnitude. Three multivariate Cox regression models were constructed to assess the associations of probiotics with all-cause and cardiovascular mortalities in patients with depression, sleep disorders, and cognitive dysfunction. Kaplan-Meier (K-M) survival analysis was used to examine differences in survival probabilities. All statistical analyses were performed using Empower Stats (version 4.2) and SPSS (version 27.0) software. All tests were two-sided, and results with p < 0.05 were considered statistically significant.
3. Results
3.1. Participants' baseline characteristics
Table 1 summarizes the participants' baseline characteristics [Mean age = 50.05 (17.50) years; Females = 52.3%]. Among the included participants, 2113 consumed products containing probiotics, prebiotics, synbiotics, or yogurt within the past 30 days, while 11,744 did not. Compared to the group that did not eat products containing probiotics, prebiotics, synbiotics, and yogurt, the probiotic, prebiotic, synbiotic, and yogurt supplement eating group was at a lower risk of HTN and CVDs. Except for cancer prevalence, the two groups showed significant differences in other variables (p < 0.05).
Table 1.
The basic characteristics of study participants.
| Total (N = 13,857) | Probiotics, prebiotics, synbiotics, or yogurt consumption (N = 2113) | No probiotics, prebiotics, synbiotics, or yogurt consumption (N = 11,744) | P value | |
|---|---|---|---|---|
| Categorical variable | ||||
| Gender | <0.001 | |||
| Male | 6614 (47.7%) | 703 (33.3%) | 5911 (50.3%) | |
| Female | 7243 (52.3%) | 1410 (66.7%) | 5833 (49.7%) | |
| Ethnicity | <0.001 | |||
| Mexican American | 1886 (13.6%) | 247 (11.7%) | 1639 (14.0%) | |
| Other Hispanic | 1339 (9.7%) | 216 (10.2%) | 1123 (9.6%) | |
| Non-Hispanic white | 6500 (46.9%) | 1145 (54.2%) | 5355 (45.6%) | |
| Non-Hispanic black | 2756 (19.9%) | 241 (11.4%) | 2515 (21.4%) | |
| Other race | 1376 (9.9%) | 264 (12.5%) | 1112 (9.5%) | |
| Education | <0.001 | |||
| Less than high school | 2981 (21.5%) | 318 (15.0%) | 2663 (22.7%) | |
| High school | 3123 (22.5%) | 338 (16.0%) | 2785 (23.7%) | |
| More than high school | 7753 (56.0%) | 1457 (69.0%) | 6296 (53.6%) | |
| Marital status | <0.001 | |||
| Married | 7365 (53.2%) | 1233 (58.4%) | 6132 (52.2%) | |
| Single | 2397 (17.3%) | 315 (14.9%) | 2082 (17.7%) | |
| Living with a partner | 1060 (7.6%) | 106 (5.0%) | 954 (8.1%) | |
| Other | 3035 (21.9%) | 459 (21.7%) | 2576 (21.9%) | |
| Hypertension | <0.001 | |||
| Yes | 5936 (42.8%) | 803 (38.0%) | 5133 (43.7%) | |
| No | 7921 (57.2%) | 1310 (62.0%) | 6611 (56.3%) | |
| Cardiovascular disease | <0.001 | |||
| Yes | 1440 (10.4%) | 166 (7.9%) | 1274 (10.8%) | |
| No | 12,417 (89.6%) | 1974 (92.1%) | 10,470 (89.2%) | |
| Cancer | 0.140 | |||
| Yes | 1417 (10.2%) | 235 (11.1%) | 1182 (10.1%) | |
| No | 12,440 (89.8%) | 1878 (88.9%) | 10,562 (89.9%) | |
| Continuous variable | ||||
| Age | 50.05 (17.50) | 50.57 (16.81) | 49.95 (17.62) | <0.001 |
| Poverty to income ratio | 2.60 (1.63) | 3.07 (1.64) | 2.51 (1.62) | <0.001 |
| OBS | 17.59 (6.76) | 19.75 (6.54) | 17.20 (6.73) | <0.001 |
Furthermore, participants who consumed probiotics, prebiotics, synbiotics, and yogurt supplements were predominantly female, white, high school-educated, and married. This might be related to the fact that women pay more attention to their own health, and it could also be due to the fact that highly educated white people have more opportunities to obtain probiotics. Moreover, the consuming group had a greater mean OBS than the non-consuming group (p < 0.001), highlighting consumers' healthier eating habits and lifestyles compared to non-consumers.
3.2. Associations of probiotics, prebiotics, synbiotics and yogurt supplements with OBS
Correlations of OBS with probiotics, prebiotics, synbiotics, and yogurt supplements were assessed using weighted binary logistic regression. In the unadjusted model, the Odds Ratio (OR) [95% Confidence Interval (CI)] for the probiotic consumption group was 2.702 (2.407–2.996), with a P value <0.001 (Table 2). In Model 2 adjusted for age, sex, race, education level, marital status, and PIR, the OBS was greater in the consumption group (OR = 2.274, 95% CI: 1.981–2.567, p < 0.001) than in the non-consumption group. In the fully adjusted model, daily probiotic consumption correlated positively with OBS values (OR = 2.222, 95% CI: 1.929–2.515, p < 0.001), implying that consumption group individuals had a higher OBS, thus highlighting their higher antioxidant capacity compared to the non-consumption group.
Table 2.
The relationship between probiotics, prebiotics, synbiotics or yogurt supplements and the Oxidative Balance Score.
| No probiotics, prebiotics, synbiotics, or yogurt consumption | Probiotics, prebiotics, synbiotics, or yogurt consumption | P value | |
|---|---|---|---|
| OBS | |||
| Model1 | Ref. | 2.702 (2.407–2.996) | <0.001 |
| Model2 | Ref. | 2.274 (1.981–2.567) | <0.001 |
| Model3 | Ref. | 2.222 (1.929–2.515) | <0.001 |
| DOBS | |||
| Model1 | Ref. | 2.572 (2.191–2.846) | <0.001 |
| Model2 | Ref. | 1.868 (1.533–2.204) | <0.001 |
| Model3 | Ref. | 1.867 (1.533–2.204) | <0.001 |
| LOBS | |||
| Model1 | Ref. | 0.175 (0.108–0.242) | <0.001 |
| Model2 | Ref. | 0.176 (0.110–0.242) | <0.001 |
| Model3 | Ref. | 0.176 (0.110–0.242) | <0.001 |
Model 1: Unadjusted.
Model 2: Adjusted for age, gender, ethnicity, education, married status and PIR.
Model 3: Model 2 plus hypertension, CVD and cancer.
Furthermore, we also conducted a more detailed analysis of the relationship between probiotics and DOBS as well as LOBS (Table 2). The results showed that there was a positive correlation between probiotics and both of these two factors. However, the correlation between DOBS and probiotics is greater than that between LOBS. We also analyzed the relationships between taking only probiotics, taking only yogurt, and OBS, DOBS, and LOBS. Yogurt showed a positive correlation with OBS, DOBS, and LOBS (Supplementary Table 2). However, in the group that only took probiotics, we found that taking only probiotics was negatively correlated with OBS, DOBS, and LOBS(Supplementary Table 3).
3.3. Relationships of probiotics, prebiotics, synbiotics, and yogurt supplements with the levels of depression, sleep disturbance, and cognitive functioning
Probiotics correlated negatively with depression prevalence and positively with cognitive functioning levels (Supplementary Table 4). In Models 1 and 2, the consumption group exhibited a lower depression prevalence than the probiotic non-consumption group (OR = 0.791 and 0.812, respectively; P < 0.05). However, in the fully adjusted model, the two groups showed a non-significant difference in depression prevalence (P = 0.078). In the 3 models, daily probiotic consumption correlated positively with total cognitive functioning levels (OR = 0.526, 95% CI: 0.158–0.894, P = 0.005), AFT values (OR = 0.182, 95% CI: 0.044–0.321, P = 0.010), and DSST values (OR = 0.159, 95% CI: 0.045–0.273, P = 0.006). However, in the fully adjusted model, the two groups showed non-significant differences in the levels of transient (P = 0.346) and delayed (P = 0.067) memory. Furthermore, the correlation between probiotic supplementation and sleep disorders was non-significant in all models (P > 0.4).
3.4. Intermediary analysis
The OBS had a significant mediating effect on the relationship between probiotic intake and depression, as well as the relationship between probiotic intake and cognitive functioning (including the total cognitive function, AFT and DSST scores; Fig. 2). In Model 2, the OBS-mediated effect accounted for 28.03% of the total association between probiotics and depression (indirect effect = −0.004, P = 0.024). On the other hand, in Model 3, the OBS-mediated effect accounted for 9.26% of the total association between probiotics and total cognitive functioning (indirect effect = 0.049, P = 0.024). Finally, the OBS-mediated effects accounted for 14.6 and 18.63% of probiotics' total associations with AFT and DSST, respectively (indirect effects = 0.027 and 0.030 and P values = 0.014 and 0.012, respectively).
Fig. 2.
Estimated proportion of the association between probiotics, prebiotics, synbiotics or yogurt supplements and depression (A) and cognitive function (B,C,D) by Oxidative Balance Score. AFT, Animal Fluency Test; DSST, Digit Symbol Substitution Test.
We further explored the mediating roles of DOBS and LOBS respectively in the relationship between depression and cognitive function. We found that it was mainly DOBS that mediated the effect of probiotics in improving depression and cognitive function (Supplementary Fig. 2). However, no mediating role of LOBS was observed.
3.5. Correlations of probiotics, prebiotics, synbiotics and yogurt supplements with all-cause and cardiovascular mortalities in depressed patients
This study involved 1828 depressed patients. Among them, 565 died, of which 145 deaths were CVD-related. Compared to the non-consumption group, the probiotic consumption group exhibited a significantly lower all-cause mortality in depressed patients (Table 3). Furthermore, in all models, depressed patients in the probiotic, prebiotic, synbiotic, and yogurt consumption groups had a significantly lower risk of all-cause mortality than the non-consumption group (P < 0.001). Supplementary Fig. 1 details the K-M survival model. Probiotics also reduced cardiovascular mortality in depressed patients (Table 4). In the unadjusted model, the Hazard Ratio (HR) [95% CI] for the consumption group was 0.942 (0.939–0.945). The HRs (95% CIs) in models 2 and 3 were 0.942 (0.939–0.944) and 0.963 (0.960–0.966), respectively. Moreover, the risk of cardiovascular death was reduced by 3.7% after fully adjusting for the consumption of probiotics, prebiotics, synbiotics, and yogurt supplements. Supplementary Fig. 3 details the K-M survival model.
Table 3.
The relationship between probiotics, prebiotics, synbiotics or yogurt supplements and all-cause mortality among depression patients, sleep disturbance patients, and cognitive function participants.
| No probiotics, prebiotics, synbiotics, and yogurt consumption | Probiotics, prebiotics, synbiotics, and yogurt consumption | P value | |
|---|---|---|---|
| Depression | |||
| Model1 | Ref. | 0.766 (0.764–0.768) | <0.001 |
| Model2 | Ref. | 0.880 (0.878–0.883) | <0.001 |
| Model3 | Ref. | 0.874 (0.871–0.876) | <0.001 |
| Sleep disturbance | |||
| Model1 | Ref. | 0.846 (0.845–0.847) | <0.001 |
| Model2 | Ref. | 0.891 (0.890–0.892) | <0.001 |
| Model3 | Ref. | 0.906 (0.905–0.907) | <0.001 |
| Cognitive function | |||
| Model1 | Ref. | 0.703 (0.702–0.704) | <0.001 |
| Model2 | Ref. | 0.810 (0.809–0.811) | <0.001 |
| Model3 | Ref. | 0.810 (0.809–0.811) | <0.001 |
Model 1: Unadjusted.
Model 2: Adjusted for age, gender, ethnicity, education, married status and PIR.
Model 3: Model 2 plus hypertension, CVD and cancer.
Table 4.
The relationship between probiotics, prebiotics, synbiotics or yogurt supplements and cardiovascular mortality among depression patients, sleep disturbance patients, and cognitive function participants.
| No probiotics, prebiotics, synbiotics, and yogurt consumption | Probiotics, prebiotics, synbiotics, and yogurt consumption | P value | |
|---|---|---|---|
| Depression | |||
| Model1 | Ref. | 0.942 (0.939–0.945) | <0.001 |
| Model2 | Ref. | 0.942 (0.939–0.944) | <0.001 |
| Model3 | Ref. | 0.963 (0.960–0.966) | <0.001 |
| Sleep disturbance | |||
| Model1 | Ref. | 1.160 (1.158–1.163) | 0.519 |
| Model2 | Ref. | 1.128 (1.126–1.130) | 0.402 |
| Model3 | Ref. | 1.128 (1.126–1.130) | 0.439 |
| Cognitive function | |||
| Model1 | Ref. | 0.277 (0.275–0.278) | <0.001 |
| Model2 | Ref. | 0.301 (0.300–0.302) | <0.001 |
| Model3 | Ref. | 0.403 (0.402–0.405) | <0.001 |
Model 1: Unadjusted.
Model 2: Adjusted for age, gender, ethnicity, education, married status and PIR.
Model 3: Model 2 plus hypertension, CVD and cancer.
3.6. Correlations of probiotics, prebiotics, synbiotics and yogurt supplements with all-cause and cardiovascular mortalities in patients with sleep disorders
This study involved 6356 patients with sleep disorders. Among them, 721 died, with 187 deaths being CVD-related. Probiotic intake correlated negatively with all-cause mortality in patients with sleep disorders (Table 3). In the unadjusted model, the HR (95% CI) for the consumption group was 0.846 (0.845–0.847). In models 2 and 3, the HRs (95% CI) were 0.891 (0.890–0.892) and 0.906 (0.905–0.907), respectively. We further modeled the K-M survival analysis of all-cause mortality in patients with sleep disorders, revealing a significant difference in all-cause mortality between the two groups (Fig. 3). In the 3 Cox models, the HRs (95% CIs) for the probiotic, prebiotic, synthetic bacteria, and yogurt consumption groups were 1.160 (1.158–1.163), 1.128 (1.126–1.130), and 1.128 (1.126–1.130), respectively. However, all models had P > 0.05, indicating a non-significant difference in cardiovascular mortality between the two groups (Table 4).
Fig. 3.
Kaplan-Meier estimates of all cause mortality according to probiotics, prebiotics, synbiotics, and yogurt consumption in sleep disturbance patients.
3.7. Associations of probiotic, prebiotic, synbiotic, and yogurt supplements with all-cause and cardiovascular mortalities in participants with cognitive dysfunction
This study involved 2287 participants with cognitive dysfunction. Among them, 446 died, with 122 deaths being CVD-related. Probiotic intake significantly reduced all-cause mortality in participants with cognitive dysfunction (Table 3). In the unadjusted model, the HR (95% CI) for the consumption group was 0.703 (0.702–0.704). In models 2 and 3, the HRs (95% CIs) were 0.810 (0.809–0.811) and 0.810 (0.809–0.811) respectively. The K-M survival analysis model revealed a significant difference in all-cause mortality between the two groups (Fig. 4). The probiotic consumption and non-consumption groups also showed a significant difference in cardiovascular mortality (Table 4). In the unadjusted model, the HR (95% CI) for the consumption group was 0.277 (0.275–0.278). In models 2 and 3, the HRs (95% CIs) were 0.301 (0.300–0.302) and 0.403 (0.402–0.405), respectively. In all 3 models, the risk of cardiovascular death was reduced by >50% after consuming probiotics, prebiotics, synbiotics, and yogurts, implying that consumption group participants were at a significantly lower risk of CVD death than nonconsumption group participants. Supplemental Fig. 4 details the K-M survival model.
Fig. 4.
Kaplan-Meier estimates of all cause mortality according to probiotics, prebiotics, synbiotics, and yogurt consumption in cognitive function participants.
4. Discussion
To the best of our knowledge, this is the first NHANES-based large-sample assessment of the probiotic-OBS correlation, OBS's mediating role in the associations of probiotics with depression, sleep disorders, and cognitive functioning, and the link between probiotics and survival outcomes in patients with neuropsychiatric disorders. Our final analysis included 13,857 participants from across six NHANES cycles, with preliminary results revealing a positive correlation between probiotic intake and OBS, thus implying healthier eating habits and lifestyle behaviors among subjects who consumed probiotic supplements. Furthermore, mediation analyses revealed that probiotic intake could reduce inflammatory responses, thereby lowering depression incidence and improving cognitive functioning. Similarly, probiotic intake correlated negatively with all-cause (at the levels of depression, sleep disorders, and cognitive dysfunction) and cardiovascular (related to depression and cognitive dysfunction) mortalities. Overall, supplements such as probiotics could prevent and treat neuropsychiatric disorders.
We also found that subjects in the probiotic intake group showed significantly higher OBS values than those in the non-intake group. We found that there was a positive correlation between yogurt and OBS, but a negative correlation existed only between the consumption of probiotics and OBS. This might be due to the fact that yogurt is more readily available, so it is widely used by the general public. On the other hand, probiotics are more difficult to obtain, and only those with unhealthy diets are likely to prefer taking probiotics to improve their health. This resulted in the observation in the data that the use of probiotics was associated with low OBS. In fact, a large number of scientific studies have confirmed that probiotics not only do not disrupt the oxidation balance, but are actually a powerful ally in combating oxidative stress. Probiotics can interact with microbiota normally present in the gut, exerting antioxidant and anti-inflammatory effects [21]. Lactobacilli can produce antioxidant enzymes (glutathione, superoxide dismutase, and c-radicals), reducing oxidative damage, decreasing lipid peroxides, and scavenging free radicals [22]. They could also suppress pro-inflammatory cytokines [Interleukin-6/IL-6, Tumor Necrosis Factor-α/TNF-α, Cyclooxygenase-2/COX-2, and inducible Nitric Oxide Synthase/iNOS] at the transcriptional level while increasing the relative expression of anti-inflammatory cytokine Interleukin-10/IL-10 mRNA. This modulation of immune responses could further inhibit Nitric Oxide (NO) production through phagocytosis [22], [23].
The prevalence of depression was previously reported to be lower in the probiotic group compared to the non-consumption group; however, after adjusting for covariates such as HTN, CVD, and cancer, the difference between the two groups was non-significant [18]. In another study, compared to the non-consumption group, a positive correlation trend was observed between daily probiotic intake and total cognitive functioning scores, AFT values, and DSST values [20]. Consistent with previous research, our findings revealed a lower depression prevalence in the probiotic consumption group than in the non-consumption group in both Models 1 and 2, although the difference was not statistically significant in Model 3. Furthermore, total cognitive functioning scores, AFT values, and DSST values were significantly higher in the probiotic-consuming group than in the probiotic-non-consuming group. It is also noteworthy that Yang et al. reported that yogurt-based probiotic intake correlated negatively with sleep disorders after adjusting for gender, race, education, BMI, alcohol consumption, smoking, diabetes, HTN, and stroke [24]. Conversely, our findings revealed no such negative associations in any of the 3 models, potentially attributable to the different NHANES cycles included and covariates selected. Previous studies have only observed the correlation between probiotics and sleep disorders in fully adjusted models. This might suggest that the correlation between probiotics and sleep disorders is not significant in this database.
Alterations in microbial diversity and reduced relative abundance of specific bacterial taxa are some of the potential influencing factors in the pathogenesis of neuropsychiatric disorders. Patients with depression previously exhibited an increased abundance of pro-inflammatory species (Bacillus and Egglococcus) and a decreased abundance of Short Chain Fatty Acid (SCFA)-producing bacteria (Coccidioides faecalis, Serratia mucilaginosa, and Serratia marcescens) [25]. Additionally, cognitively impaired patients showed reduced diversity in the intestinal flora, exhibiting an increased abundance of Acidobacter, Mycobacterium florescens, and Zygomycetes, and a decreased abundance of Thick-walled cocci including Bacillus, Clostridium, and Gram-negative cocci [26]. Moreover, owing to increased epithelial barrier permeability resulting from the increased Lipopolysaccharide (LPS) count in the body, certain gram-negative bacteria could enter the bloodstream through the damaged intestinal mucus barrier function, causing intestinal bacterial translocation, which ultimately directly or indirectly affects brain function [27]. It has also been established that probiotics could enhance the expression of tight junction proteins in intestinal tissues, reducing the inflammatory response and decreasing intestinal permeability [28].
Herein, we found that probiotic intake in humans could lower inflammatory responses, reducing depression incidence and improving cognitive functioning. The gut ecological imbalance and neurological impairment have been linked through chronic low-grade inflammatory responses, encompassing processes such as direct inflammatory stimulation and stress response modulation via Hypothalamic-Pituitary-Adrenal (HPA) axis activation [29], [30]. Furthermore, peripherally injected LPS can induce a systemic inflammatory response in mice via Toll-like receptor 4 signaling channels. This response might activate Anterior Cingulate Gyrus (ACC) microglia via CX3CR1 upregulation, increasing microglial phagocytosis of ACCGlu neurons and potentially leading to depressive-like behaviors in mice [31], [32]. Inflammatory factors could also stimulate the tryptophan-kynurenine pathway, thus increasing the production of the endogenous neurotoxin, Quinolinic Acid (QUIN) [33]. In chronic inflammatory states, pro-inflammatory cytokines could directly suppress Brain-Derived Neurotrophic Factor (BDNF) expression and reduce neurotrophic support, impacting synaptic plasticity and neuronal function, ultimately decreasing learning and memory function [34], [35]. Additionally, BDNF binding to TrkB receptors could stimulate phospholipase Cγ1 (PLCγ1)/protein kinase C (PKC) signaling. This phenomenon could further activate the kinases IKKα and IKKβ, leading to the phosphorylation and ubiquitination-mediated degradation of IκBα (the inhibitory unit of nuclear factor-κB/NF-κB). This process then results in the release of the NF-κB dimer, allowing for its translocation to the nucleus, where it binds to the promoter regions of target genes and initiates the transcription of inflammatory factors and chemokines, ultimately leading to apoptosis of neurons and glial cells [36], [37].
In animal studies, the oral administration of Bifidobacterium shortum CCFM 1025 supplementation significantly decreased depression-like behavior in mice exposed to chronic stress [38]. Specifically, CCFM.CCFM 1025 modulated glucocorticoid receptor (Nr3c1) expression, thus attenuating HPA axis overactivation. It also lowered IL-6 concentration in the hippocampus and TNF-α expression in the periphery. Collectively, these impacts reduced the inflammatory response in chronic stress-exposed mice in vivo. In human studies, Bacillus coagulans MTCC 5856 reduced serum Myeloperoxidase (MPO) levels, decreased free radical production, and lowered cellular OS, significantly attenuating depressive symptoms [39]. Another study that included 63 healthy older adults reported that probiotics improved brain function and psychological stress in participants [40]. Compared to the placebo group, the probiotic group exhibited significantly higher serum BDNF levels at week 12. Notably, probiotic supplementation resulted in a significant negative correlation between the relative abundance of beneficial bacteria (Clostridium species) in the gut and serum BDNF expression. Additionally, Fructooligosaccharide (FOS) treatment significantly reduced plasma and urinary corticosterone levels in stressed rats, eventually restoring them to levels observed in control rats. This phenomenon aligns with the effect of fluoxetine, an antidepressant, in lowering cortisol levels under stress [41]. Although both FOS and fluoxetine can promote the growth of beneficial bacteria with antidepressant properties (e.g., Flagellates and Lactobacillus), FOS induces more pronounced changes in the gut's microbial composition than fluoxetine.
In this study, we found that the probiotic consumption group had higher survival rates following neuropsychiatric disorders and that the gut microbe-derived metabolites trimethylamine N-oxide (TMAO) and branched-chain amino acids were positively associated with cardiovascular disease/all-cause mortality, whereas tryptophan was negatively associated with all-cause mortality [42]. In another meta-analysis of data collected from prospective studies, participants with high TMAO levels had a 62% increased risk of experiencing major adverse cardiovascular events and a 63% increased risk of mortality compared with participants with low TMAO levels [43]. It has been reported that TMAO concentrations can be reduced by modulating gut microbiota via dietary supplements, providing a window for reducing all-cause mortality and cardiovascular disease mortality [44]. Increased taurine in the gut may extend the life span of the organism by improving physical dysfunction associated with aging [45], [46]. In this study, taurine levels were most significantly elevated in feces from aged mice in the probiotic-fed group compared to the control group. This is because probiotics can release more taurine in the gut by increasing bile salt hydrolase detoxification (BSH), thereby increasing taurine-bile salt uncoupling.
This study has the following three limitations: (1) despite adjusting for potential confounders in our multivariate model, we cannot rule out the influence of other factors (for instance, the influence of other comorbidities such as diabetes or stroke, as well as economic factors such as the annual household income. When discussing the correlation between probiotics and OBS, dietary factors such as total energy intake can be adjusted); and (2) the data for this study were obtained exclusively from the U.S. population, which may limit the generalizability of the findings to other populations.
5. Conclusion
In conclusion, we found a positive correlation between OBS and probiotics consumption, and observed that probiotics in the body can reduce the incidence of depression and improve participants' level of cognitive functioning by suppressing inflammatory response. In addition, probiotics, prebiotics, synbiotics, and yogurt intake reduced all-cause mortality in patients with sleep disorders as well as in participants with levels of cognitive functioning and cardiovascular mortality in patients with depression, sleep disorders, and cognitive functioning.
CRediT authorship contribution statement
Yihan Liu: Writing – review & editing, Writing – original draft, Data curation. Yuanyuan Liu: Software, Data curation. Guangming Wang: Visualization, Validation. Haixia Zhang: Supervision, Conceptualization. Zhenguang Li: Project administration. Jinbiao Zhang: Project administration, Methodology, Conceptualization.
Ethics statement
Review and approval by an ethics committee were not needed for this study, because the data in this study are from public databases.
Funding
This research obtained financing from The Shandong Provincial Medical and Health Science and Technology Plan (202403071352) and Neurological Diseases and Nutrition Health Research Project of National Health Commission of the PRC (W2024SNKT40).
Declaration of competing interest
The authors declare that they have no competing interests.
Acknowledgments
Thanks to all the individuals and organizations that provided help and support during this research. We thank MJEditor for its contribution in enhancing the language presentation of the paper.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.ahjo.2026.100767.
Appendix A. Supplementary data
Supplementary material
Data availability
Publicly available datasets were analyzed in this study. Data used for this study are available on the NHANES website: https://www.cdc.gov/nchs/nhanes/index.htm.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary material
Data Availability Statement
Publicly available datasets were analyzed in this study. Data used for this study are available on the NHANES website: https://www.cdc.gov/nchs/nhanes/index.htm.