Association between the oxidative balance score and cognitive function: evidence from NHANES 2011-2014

doi:10.21203/rs.3.rs-4863449/v1

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Association between the oxidative balance score and cognitive function: evidence from NHANES 2011-2014

https://doi.org/10.21203/rs.3.rs-4863449/v1

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Background

With the global aging population, the prevalence of Cognitive impairment (CI) has significantly increased. Despite extensive research, the role of oxidative stress in CI remains underexplored, with limited studies directly linking oxidative balance score (OBS) to cognitive function. This study aims to investigate the association between OBS and cognitive function using data from the 2011–2014 National Health and Nutrition Examination Survey (NHANES).

Methods

Data from 2103 participants aged 60 years and older were analyzed in this study. OBS was calculated using 16 dietary components and 4 lifestyle factors.Cognitive function was assessed by a combination of tests such as CERAD, AFT and DSST. The association between OBS and cognitive function was assessed using logistic regression and restricted cubic spline (RCS) analyses after adjusting for confounders such as age, sex, and comorbidities.

Results

Key findings indicate a significant positive association between higher OBS and better cognitive function across all assessed domains, even after adjusting for potential confounders. Subgroup analyses revealed that this association was particularly pronounced in individuals with liver disease and stroke, suggesting that oxidative stress might have a more detrimental impact on cognitive function in these populations.

Conclusion

The present study provides strong evidence that higher OBS is significantly associated with better cognitive function in older adults. Dietary and lifestyle interventions to improve oxidative balance may be an effective strategy to protect cognitive health.

Health sciences/Neurology/Neurological disorders

Health sciences/Neurology

Health sciences/Diseases/Neurological disorders/Dementia

Oxidative balance score

cognitive function

NHANES

older adults

Dietary

Lifestyle

Cognitive impairment (CI) refers to deficits in key brain functions, including memory, learning, attention, and decision-making abilities. As the global population ages, the prevalence of CI, particularly Alzheimer's disease (AD) and related dementias (ADRD), is increasing significantly. Approximately 50 million people worldwide are affected by AD, and this number is expected to rise to 139 million by 2050 ¹. Mild Cognitive Impairment (MCI) is an intermediate stage between normal aging and dementia; it causes cognitive decline with a lesser impact on daily life. It is estimated that approximately 15% of individuals with MCI will progress to AD within two years². Although dementia progression is often considered irreversible, studies suggest that approximately 16% of individuals with MCI may regain normal cognitive functioning ³. CI imposes a substantial burden on individuals, families, and society as a whole. Therefore, early identification and intervention are crucial in slowing the progression of CI.

Research indicates that CI may be associated with age, genetic factors, lifestyle, chronic diseases, and infections, with oxidative stress identified as a key factor in cognitive deterioration ⁴. With aging and disease states, the balance between the production and removal of reactive oxygen species is disrupted, leading to a state of oxidative stress. Nerve cells in the brain are highly sensitive to oxidative stress, and excess oxygen free radicals induce lipid and protein peroxidation, resulting in nerve cell death. Accumulation of these damages impairs memory and learning abilities, contributing to the development of dementia. Mangialasche et al. ⁵found elevated markers of oxidative damage in the brains of patients with AD, and oxidative stress may cause an abnormal accumulation of β-amyloid plaques and the formation of neural protofibrillar tangles, which may lead to the development of AD ⁶.

The Oxidative Balance Score (OBS) is a quantitative index used to assess dietary and lifestyle exposure to antioxidants and pro-oxidants. It reflects the overall level of oxidative stress by integrating the amount and type of antioxidants and pro-oxidants consumed by an individual ⁷. Higher OBS values indicate higher antioxidant exposure, while lower OBS values suggest higher pro-oxidant exposure. Among the indicators for assessing OBS, dietary antioxidants, including vitamin C, vitamin E, carotenoids, along with smoking and alcohol consumption, have been shown to affect cognitive function ^8–10. However, no studies have yet demonstrated a direct association between OBS and cognitive function.

This study, based on two consecutive cycles of National Health and Nutrition Examination Survey (NHANES) data between 2011 and 2014, combined with various demographic information and disease factors, aims to explore the potential association between OBS and cognitive function. The results of this study will provide a scientific basis for a deeper understanding of the protective effects of antioxidant exposure on cognitive function and may serve as a strong reference for public health policy development.

The National Center for Health Statistics (NCHS) leads NHANES, which has been surveying and assessing the health and nutritional status of adults and children in the U.S. since the early 1960s. NHANES maintains a high degree of transparency in its data and survey design, making all public data and detailed survey methodology available on its official website. The NCHS Ethics Review Board approves NHANES research protocols to ensure their compliance with ethical standards. All participants provided written informed consent before participating in the survey. Data for this study were obtained from two consecutive cycles of NHANES (2011–2012 and 2013–2014), comprising a total of 19,931 participants. Exclusion criteria included: (1) age < 60 years (n = 16,299); (2) missing dietary data required for OBS calculation (n = 1,319); (3) missing data for cognitive function assessment (n = 210). Finally, 2,103 participants were included in the final analysis, of whom 1,019 were male and 1,084 were female(Fig. 1).

Definition of OBS

The OBS is a composite index that integrates dietary and lifestyle factors to quantify an individual's exposure to antioxidants and pro-oxidants. The OBS was calculated based on 16 dietary components and four lifestyle factors. Dietary data were primarily obtained from two NHANES 24-hour dietary recall interviews and included dietary fiber, carotenoids, riboflavin, niacin, vitamin B6, total folate, vitamin B12, vitamin C, vitamin E, calcium, magnesium, zinc, copper, selenium, total fat, and iron. Lifestyle factors included physical activity, alcohol consumption, smoking status, and body mass index (BMI). Among these, total fat, iron, BMI, alcohol consumption, and smoking are considered pro-oxidants, while the rest are classified as antioxidants. Cotinine, a major metabolite of nicotine, was used to assess smoking status through serum cotinine levels. Physical activity was quantified by multiplying the frequency and duration of each weekly activity by its corresponding metabolic equivalent (MET) score. Alcohol consumption was categorized into non-drinkers, moderate drinkers (0–15 g/day for women and 0–30 g/day for men), and heavy drinkers (≥ 15 g/day for women and ≥ 30 g/day for men), scoring 2, 1, and 0 points, respectively. The other components were assigned scores based on their tertiles within different gender groups, with scores ranging from 0 to 2 for antioxidants and in reverse for pro-oxidants. The total OBS score was ultimately obtained by summing the scores of individual components.

Cognitive function assessment

In the NHANES (2011–2014) study, participants underwent multiple assessments, including the CERAD Word Learning and Recall Module, the Animal Fluency Test (AFT), and the Digit Symbol Substitution Test (DSST). The CERAD consisted of three consecutive learning trials and one delayed recall trial, where participants were asked to read 10 unrelated words and memorize as many as possible. The delayed recall portion of the test was administered after the Animal Fluency Test and the Digit Symbol Substitution Test. The CERAD test has a maximum total score of 40 points. In the AFT, participants were asked to name as many different animals as possible within 1 minute. The score on the AFT was the total number of animals named by the participant within the time limit, reflecting their ability to generate vocabulary quickly within a specific semantic category. The DSST is a performance module of the Wechsler Adult Intelligence Scale (WAIS-III) that assesses processing speed, sustained attention, and working memory. In this test, participants were required to match 133 numbers with the corresponding symbols within 2 minutes. The DSST not only assesses cognitive processing speed but also examines visual-motor coordination and cognitive agility, with a maximum score of 133 points.

To overcome individual differences across tests and scale decay effects, we standardized the results by calculating the score for each cognitive assessment and integrating them into a single global cognitive score, allowing for a more comprehensive assessment of participants' overall cognitive functioning. The specific formula is Global.Cognition = (x - m) / σ, where x represents the individual's test score, m is the mean score of the test, and σ is the standard deviation.

Covariates

To minimize confounding factors, we reviewed the literature and included relevant covariates in our analysis. Potential covariates included age, sex, race, educational attainment, marital status, poverty-to-income ratio (PIR), hypertension, diabetes, depression, liver disease, lung disease, heart disease, stroke, and arthritis. Sex was categorized as male or female, while race was classified into Mexican American, non-Hispanic Black, non-Hispanic White, other Hispanic, and other races. Marital status was categorized into married or cohabiting, divorced or separated or widowed, and never married. Educational attainment was categorized into less than high school, high school, and more than high school. PIR was classified as low (< 1.3), moderate (1.3–3.5), and high (≥ 3.5). Hypertension was defined as (1) a physician's diagnosis, (2) a mean systolic blood pressure of 130 mm Hg or higher, or a mean diastolic blood pressure of 80 mm Hg or higher, and (3) use of antihypertensive medication. Diabetes mellitus was defined as (1) a physician's diagnosis, (2) a glycosylated hemoglobin (HbA1c) level of 6.5% or higher, and (3) use of diabetes medication or insulin. Depression was defined as a score of ≥ 10 on the Patient Health Questionnaire-9 (PHQ-9). Diagnoses of liver disease, stroke, and arthritis were based on patient self-reports. Individuals diagnosed with congestive heart failure, coronary artery disease, myocardial infarction, or angina pectoris were categorized as having heart disease, whereas those diagnosed with asthma, chronic bronchitis, or emphysema were categorized as having lung disease.

Statistical analysis

Continuous variables were expressed as mean ± standard deviation (SD), while categorical variables were expressed as percentages. T-tests and chi-square tests were used to analyze the significance of the data. OBS was divided into quartiles, with Q1 serving as the reference group. To analyze the relationship between OBS and cognitive functioning, logistic regression was performed on several variables. The crude model was unadjusted; model 1 was adjusted for age, sex, and race; model 2 was further adjusted for education, marital status, PIR, hypertension, diabetes, depression, liver disease, lung disease, heart disease, stroke, and arthritis. Results are expressed as β coefficients with 95% confidence intervals (95% CI). We also performed curve fitting for the dose-response relationship between OBS and cognitive function using a restricted cubic spline approach. In addition, stratified analyses were conducted to further validate the robustness of the results. All analyses were conducted using R (version 4.4.1, http://www.R-project.org) and EmpowerStats software (version 2.0, http://www.empowerstats.com). A two-sided p-value < 0.05 was considered statistically significant.

Baseline characteristics

This study included 2,103 participants aged 60 and above. As shown in Table 1, the mean age of the participants was 69.52 ± 6.76 years, with 49.23% being male. The mean values of CERAD, AFT, DSST, and Global.Cognition were 25.14 ± 6.40, 16.91 ± 5.44, 47.18 ± 16.66, and 0.20 ± 2.34, respectively. Compared to other OBS groups, the 4th group was characterized by higher cognitive scores (CERAD, AFT, DSST, and Global.Cognition), being non-Hispanic white, having education beyond high school, a high PIR, absence of hypertension and diabetes, and the presence of heart disease.

Table 1

Baseline characteristics of the participants divided into quartiles of the OBS in NHANES 2011–2014.
Characteristics	Total (n = 2103)	Quartile 1(n = 520)	Quartile 2(n = 529)	Quartile 3(n = 465)	Quartile 4(n = 589)	P-value
AGE(years)	69.52 ± 6.76	69.72 ± 6.62	69.77 ± 6.85	69.21 ± 6.75	69.36 ± 6.79	0.469
CERAD	25.14 ± 6.40	24.04 ± 6.37	24.95 ± 6.35	25.15 ± 6.53	26.28 ± 6.19	< 0.001
AFT	16.91 ± 5.44	15.29 ± 5.11	16.56 ± 5.16	17.31 ± 5.33	18.33 ± 5.65	< 0.001
DSST	47.18 ± 16.66	41.06 ± 15.53	46.00 ± 16.26	49.02 ± 17.15	52.17 ± 15.75	< 0.001
Global.Cognition	0.20 ± 2.34	-0.61 ± 2.26	0.04 ± 2.26	0.38 ± 2.34	0.93 ± 2.24	< 0.001
Sex, n (%)						0.100
Male	1019	256 (49.23%)	255 (48.20%)	244 (52.47%)	264 (44.82%)
Female	1084	264 (50.77%)	274 (51.80%)	221 (47.53%)	325 (55.18%)
Race, n (%)						< 0.001
Mexican American	177	38 (7.31%)	47 (8.88%)	41 (8.82%)	51 (8.66%)
Other Hispanic	199	52 (10.00%)	57 (10.78%)	44 (9.46%)	46 (7.81%)
Non-Hispanic White	1091	217 (41.73%)	268 (50.66%)	256 (55.05%)	350 (59.42%)
Non-Hispanic Black	464	180 (34.62%)	119 (22.50%)	82 (17.63%)	83 (14.09%)
Other Race	172	33 (6.35%)	38 (7.18%)	42 (9.03%)	59 (10.02%)
Education level, n (%)						< 0.001
Below high school	487	178 (34.23%)	125 (23.63%)	99 (21.29%)	85 (14.43%)
High school	503	142 (27.31%)	141 (26.65%)	101 (21.72%)	119 (20.20%)
Above high school	1113	200 (38.46%)	263 (49.72%)	265 (56.99%)	385 (65.37%)
Marital status, n (%)						0.070
Married or living with partner	1255	291 (55.96%)	301 (56.90%)	293 (63.01%)	370 (62.82%)
Divorced, separated, or widowed	733	198 (38.08%)	203 (38.37%)	148 (31.83%)	184 (31.24%)
Never married	115	31 (5.96%)	25 (4.73%)	24 (5.16%)	35 (5.94%)
Family PIR, n (%)						< 0.001
< 1.3	538	175 (33.65%)	139 (26.28%)	117 (25.16%)	107 (18.17%)
1.3–3.5	921	250 (48.08%)	242 (45.75%)	184 (39.57%)	245 (41.60%)
≥ 3.5	644	95 (18.27%)	148 (27.98%)	164 (35.27%)	237 (40.24%)
Hypertension, n (%)						< 0.001
Yes	1673	441 (84.81%)	422 (79.77%)	378 (81.29%)	432 (73.34%)
NO	430	79 (15.19%)	107 (20.23%)	87 (18.71%)	157 (26.66%)
Diabetes, n (%)						< 0.001
Yes	598	200 (38.46%)	154 (29.11%)	139 (29.89%)	105 (17.83%)
NO	1505	320 (61.54%)	375 (70.89%)	326 (70.11%)	484 (82.17%)
PHQ Score						0.203
< 10	181	52 (10.00%)	52 (9.83%)	35 (7.53%)	42 (7.13%)
≥ 10	1922	468 (90.00%)	477 (90.17%)	430 (92.47%)	547 (92.87%)
Liver disease, n (%)						0.639
Yes	63	18 (3.46%)	12 (2.27%)	16 (3.44%)	17 (2.89%)
NO	2040	502 (96.54%)	517 (97.73%)	449 (96.56%)	572 (97.11%)
Pulmonary disease, n (%)						0.290
Yes	366	105 (20.19%)	88 (16.64%)	76 (16.34%)	97 (16.47%)
NO	1737	415 (79.81%)	441 (83.36%)	389 (83.66%)	492 (83.53%)
Heart disease, n (%)						< 0.001
Yes	371	119 (22.88%)	101 (19.09%)	70 (15.05%)	81 (13.75%)
NO	1732	401 (77.12%)	428 (80.91%)	395 (84.95%)	508 (86.25%)
Stroke,n (%)						0.168
Yes	129	42 (8.08%)	32 (6.05%)	23 (4.95%)	32 (5.43%)
NO	1974	478 (91.92%)	497 (93.95%)	442 (95.05%)	557 (94.57%)
Arthritis,n (%)						0.124
Yes	1051	280 (53.85%)	246 (46.50%)	234 (50.32%)	291 (49.41%)
NO	1052	240 (46.15%)	283 (53.50%)	231 (49.68%)	298 (50.59%)
PIR: Poverty Income Ratio; OBS:Oxidative Balance Score; n: Number of study samples.

Association Between OBS and Cognitive Function

Multiple linear analyses of OBS, both as a continuous variable and a four-category variable, demonstrated significant positive correlations (p < 0.05) between OBS and the four cognitive functioning assessment scores, as shown in Table 2. The final adjusted model 2 showed that for each 1-unit increase in OBS, CERAD scores increased by 0.051 [β (95% CI) = 0.051 (0.015, 0.087)], AFT scores increased by 0.083 [β (95% CI) = 0.083 (0.053, 0.114)], DSST scores increased by 0.185 [β (95% CI) = 0.185 (0.109, 0.261)], and Global.Cognition scores increased by 0.034 [β (95% CI) = 0.034 (0.022, 0.045)]. The positive correlation between OBS and cognitive function was more significant in the highest quartile group compared to the lowest quartile group. In the fourth quartile group, each 1-unit increase in OBS was associated with a 0.775 increase in CERAD score [β (95% CI) = 0.775 (0.066, 1.483), ptrend = 0.054], a 1.534 increase in AFT score [β (95% CI) = 1.534 (0.938, 2.131), ptrend < 0.001], and a 3.252 increase in DSST score [β (95% CI) = 3.252 (1.765, 4.740), ptrend < 0.001]. Additionally, Global.Cognition scores increased by 0.586 [β (95% CI) = 0.586 (0.365, 0.808), ptrend < 0.001]. The dose-response relationship between OBS and cognitive function was further analyzed using restricted cubic spline (RCS), with results shown in the Fig. 2. OBS was found to be linearly and positively correlated with CERAD, AFT, DSST, and Global.Cognition (P for nonlinearity > 0.05).

Table 2

Association between OBS and cognitive function in NHANES 2011–2014.
Characteristics	β (95% CI)
	Model 1	p-value	Model 2	p-value	Model 3	p-value
CERAD
OBS continuous	0.134 (0.097, 0.172)	< 0.001	0.101 (0.065, 0.137)	< 0.001	0.051 (0.015, 0.087)	0.006
OBS quartiles
Quartile 1	0[Reference]		0[Reference]		0[Reference]
Quartile 2	0.910 (0.142, 1.679)	0.02	0.789 (0.077, 1.501)	0.03	0.376 (-0.323, 1.075)	0.292
Quartile 3	1.108 (0.313, 1.903)	0.006	0.788 (0.047, 1.529)	0.037	0.220 (-0.510, 0.950)	0.555
Quartile 4	2.236 (1.487, 2.985)	< 0.001	1.669 (0.964, 2.373)	< 0.001	0.775 (0.066, 1.483)	0.032
P for trend		< 0.001		< 0.001		0.054
AF
OBS continuous	0.167 (0.135, 0.199)	< 0.001	0.128 (0.098, 0.159)	< 0.001	0.083 (0.053, 0.114)	< 0.001
OBS quartiles
Quartile 1	0[Reference]		0[Reference]		0[Reference]
Quartile 2	1.271 (0.626, 1.916)	< 0.001	0.956 (0.353, 1.560)	0.002	0.572 (-0.016, 1.160)	0.057
Quartile 3	2.021 (1.354, 2.688)	< 0.001	1.399 (0.771, 2.027)	< 0.001	0.875 (0.261, 1.489)	0.005
Quartile 4	3.045 (2.416, 3.673)	< 0.001	2.348 (1.751, 2.945)	< 0.001	1.534 (0.938, 2.131)	< 0.001
P for trend		< 0.001		< 0.001		< 0.001
DSST
OBS continuous	0.634 (0.538, 0.730)	< 0.001	0.441 (0.357, 0.526)	< 0.001	0.185 (0.109, 0.261)	< 0.001
OBS quartiles
Quartile 1	0[Reference]		0[Reference]		0[Reference]
Quartile 2	4.939 (2.985, 6.893)	< 0.001	3.757 (2.078, 5.436)	< 0.001	1.509 (0.042, 2.976)	0.044
Quartile 3	7.966 (5.946, 9.986)	< 0.001	5.586 (3.838, 7.333)	< 0.001	2.602 (1.070, 4.133)	< 0.001
Quartile 4	11.115 (9.211, 13.020)	< 0.001	7.799 (6.138, 9.461)	< 0.001	3.252 (1.765, 4.740)	< 0.001
P for trend		< 0.001		< 0.001		< 0.001
Global Cognition
OBS continuous	0.088 (0.074, 0.101)	< 0.001	0.064 (0.052, 0.076)	< 0.001	0.034 (0.022, 0.045)	< 0.001
OBS quartiles
Quartile 1	0[Reference]		0[Reference]		0[Reference]
Quartile 2	0.656 (0.381, 0.931)	< 0.001	0.512 (0.272, 0.752)	0.184	0.249 (0.030, 0.468)	0.026
Quartile 3	0.998 (0.714, 1.283)	< 0.001	0.698 (0.449, 0.948)	< 0.001	0.344 (0.115, 0.572)	0.003
Quartile 4	1.539 (1.271, 1.807)	< 0.001	1.134 (0.897, 1.371)	< 0.001	0.586 (0.365, 0.808)	< 0.001
P for trend		< 0.001		< 0.001		< 0.001
β : regression coefficient; 95% CI: 95% Confidence Interval. Crude model: Unadjusted for covariates. Model 1: Adjusted for age, sex, and race. Model 2: Adjusted for age, sex, race ,education, marital status, PIR, hypertension, diabetes, depression, liver disease, lung disease, heart disease, stroke, and arthritis.

Subgroup Analysis

We performed subgroup analyses stratified by age, gender, hypertension, diabetes, stroke, and liver disease to determine whether the relationship between OBS and cognitive function remained stable across these subgroups. As shown in the Fig. 3, the results indicated that the effect (β) of OBS on cognitive function (CERAD, AFT, DSST, and Global.Cognition) was generally stable across age, gender, hypertension, and diabetes subgroups (P for interaction > 0.05). The positive correlation between OBS and DSST was more pronounced in the liver disease group compared to those without liver disease. Similarly, the positive correlations between OBS and AFT, DSST, and Global.Cognition were more significant in the stroke group compared to those without stroke (P for interaction < 0.05).

As the global population ages, cognitive impairment is emerging as a significant public health challenge. The OBS is a novel and comprehensive index that assesses an individual's overall oxidative homeostasis by integrating multiple oxidative and antioxidant factors. Previous studies have demonstrated that OBS is inversely associated with the incidence of stroke, kidney stones, and depression ^7,11,12. Our study is the first comprehensive retrospective analysis to investigate the association between OBS and cognitive function. The study included 2,103 participants aged 60 years or older from the 2011–2014 NHANES. Results revealed a positive association between OBS and cognitive function after adjusting for all confounders. This finding underscores the importance of maintaining antioxidant status to prevent cognitive decline, particularly in individuals with liver disease and stroke.

The effects of oxidative stress on cognitive function involve multiple complex biological mechanisms. The brain consumes approximately 20% of the body's oxygen intake to maintain normal function, and this high level of oxygen consumption generates free radicals ¹³. In aging and pathological conditions, the production of oxygen free radicals significantly increases, directly attacking and damaging the cell membranes of CNS cells, ultimately leading to impaired cellular function. Additionally, oxygen free radicals can impair the energy supply of nerve cells by damaging mitochondrial DNA and membrane proteins, leading to neuronal death ¹⁴. Oxidative stress can induce an inflammatory response in the brain. This response activates microglia and astrocytes, which are responsible for maintaining normal neuronal function under normal conditions ¹⁵. However, sustained activation of these cells leads to the release of pro-inflammatory cytokines such as tumor necrosis factor alpha (TNF-α), interleukin-1β (IL-1β), and C-C motif chemokines that mediate neuroinflammation and neurodegeneration, while peripheral inflammatory mediators cross the defective blood-brain barrier, further exacerbating the inflammatory response ¹⁶. These inflammatory responses further damage neurons, ultimately leading to neural network dysfunction.

AD is one of the most common neurodegenerative diseases, with cognitive decline as its central symptom. The prevailing hypotheses on the etiology of AD include the cholinergic hypothesis and the extracellular amyloid-β plaque deposition hypothesis ¹⁷. Acetylcholine is the primary neurotransmitter associated with learning and memory functions and is essential for neuronal activity, plasticity, and network connectivity. Oxidative stress can lead to decreased acetylcholine levels by impairing choline acetyltransferase activity ¹⁸. Furthermore, oxidative stress can impair neuronal signaling by damaging acetylcholine receptors, leading to decreased learning and memory abilities ¹⁹. Oxygen free radicals in the brain can interfere with the metabolism of amyloid precursor proteins, leading to the production of β-amyloid, an abnormal metabolite that tends to aggregate into insoluble plaques around neurons, interfering with normal neuronal signaling and causing neuronal dysfunction, which ultimately triggers cognitive decline ²⁰.

Previous studies have demonstrated a correlation between dietary composition and cognitive function. A meta-analysis showed that B vitamins, vitamin C, and vitamin E can help protect the brain from oxidative stress, and that using these vitamins as dietary supplements may help improve cognitive function in aging individuals ²¹. A study by Wang et al. ²² showed that dementia patients had significantly lower blood carotenoid levels than controls, suggesting that lower blood carotenoid levels could be a contributing factor to cognitive decline. Meng et al. ²³ demonstrated that dietary zinc intake exhibited an L-shaped negative correlation with cognitive decline in older adults, suggesting that maintaining appropriate dietary zinc levels could help prevent cognitive decline. A cross-sectional study indicated that higher dietary intakes of iron and copper were associated with poorer cognitive function ²⁴. Xu et al. ²⁵ supported the idea that higher copper exposure may be associated with cognitive impairment. However, another prospective cohort study showed that dietary copper intake was nonlinearly and negatively associated with cognitive decline in older adults ²⁶.suggesting that this discrepancy may be related to the proportion of copper forms present in the body. Copper can act as both an antioxidant and a pro-oxidant in the body. Chan et al. ²⁷ proposed that copper is a cofactor for CuZn-superoxide dismutase, which specifically scavenges superoxide radicals, while Valko et al. ²⁸ found that copper ions catalyze the generation of hydroxyl radicals from hydrogen peroxide, which are highly oxidative and lead to oxidative damage to cellular lipids, proteins, and DNA. The correlation between dietary magnesium and cognitive impairment is inconsistent. A cohort study from China showed that high dietary magnesium intake was associated with an increased risk of dementia, while another cohort study from Japan suggested that higher dietary intake of magnesium reduced the risk of all-cause dementia in the general Japanese population ^29,30. Chen et al. ³¹ suggested that the calcium-to-magnesium intake ratio may be responsible for the discrepancy in the results, indicating that when diets are low in calcium and high in magnesium, magnesium may be a risk factor for dementia, whereas it may be protective in diets high in calcium and low in magnesium. Fat is a significant pro-oxidant in OBS, and results from animal experiments have shown that sustained intake of a high-fat diet leads to hyperphosphorylation of Tau proteins in the hippocampus, triggering microglial activation and the expression of inflammatory factors, which ultimately results in cognitive decline ³².

Several studies have confirmed that physical activity is a protective factor for cognitive function, and encouraging older adults to remain physically active can help prevent cognitive decline and dementia ³³. Smoking exacerbates the burden of vascular diseases such as cerebral infarction, impairs the blood supply to the brain, and exacerbates damage to brain cells. In addition, smoking may promote white matter degeneration by inhibiting myelin synthesis, thereby increasing the risk of AD ³⁴. Similarly, alcohol consumption is positively associated with cognitive decline in older adults, with even more than one standard unit of alcohol intake negatively affecting cognitive performance ³⁵. There is conflicting evidence on the relationship between BMI and cognitive function, with a study by Naomi et al. ³⁶ suggesting that obesity induces oxidative stress and inflammation, which in turn increases the risk of cognitive impairment and dementia. Conversely, Sun et al. ³⁷ found that obese individuals in later life exhibited improved cognitive function and a reduced risk of dementia. This may suggest an "obesity paradox," where weight loss is directly linked to health deterioration and increased mortality in older adults, while obese individuals possess a higher level of physical reserve and are less likely to suffer from other serious health complications ³⁸.

Our study showed that the positive correlation between OBS and DSST was more pronounced in the liver disease group compared to the normal group. The DSST is a highly sensitive test that detects milder cognitive impairments. In liver disease, impaired liver function leads to an increase in free radicals and a decrease in antioxidant capacity. This elevated level of oxidative stress may exacerbate cognitive impairments. The correlation between OBS and cognitive impairment was more pronounced in patients with liver disease ³⁹. Similarly, the positive correlations between OBS and AFT, DSST, and Global.Cognition were more significant in the stroke group compared to the normal group. There may be a synergistic effect of oxidative stress and stroke on the impairment of cognitive function. Specifically, stroke leads to decreased blood supply to the brain, directly affecting brain function and the integrity of the blood-brain barrier. Peripheral inflammatory mediators are more likely to invade brain tissue, aggravating damage, while ischemic damage triggers oxidative stress, further harming neurons ^40,41. Stroke-induced cerebral ischemia weakens the brain's ability to resist oxidative stress, making even mild oxidative stress more damaging.

This study has several strengths. We integrated data from all available consecutive NHANES cycles, including a large sample of elderly participants across the United States, which enhances the stability of the statistical analysis and generalizability of the results. Our study design accounted for several potential confounders, including gender, race, income, and comorbidities, and adjustments were made using multivariate analysis methods, ensuring the accuracy and reliability of the results. The OBS integrates multiple metrics related to oxidative stress, reflecting the overall oxidative status of the body. Compared to a single biomarker, the OBS is more holistic and representative. We found, for the first time, a significant association between OBS and cognitive function. This finding provides a new perspective for understanding the potential role of oxidative stress in cognitive disorders and enables better identification of those at risk, allowing for the development of personalized interventions.

There are some limitations to this study. First, this was a cross-sectional study, so we were unable to determine a causal relationship between OBS and cognitive impairment, nor could we observe dynamic changes in OBS and cognitive function over time. Second, assessing cognitive function is a complex process, and the cognitive tests in the NHANES database may not comprehensively cover all cognitive domains. Although we adjusted for multiple confounders in this study, it remains difficult to completely exclude all external variables that may affect the results, and unconsidered confounders could impact the study's accuracy. Future prospective longitudinal studies are needed to further validate the relationship between OBS and cognitive impairment and to strengthen causal inferences.

Our findings indicate that higher oxidative balance scores (OBS) in the older American population are typically associated with better cognitive performance. This association was particularly pronounced among older adults with liver disease and stroke. Antioxidant dietary and lifestyle modifications may help enhance cognitive function in older adults. However, the mechanisms by which OBS affects cognitive function require further investigation.

Ethics approval and consent to participate

The NCHS Research Ethics Review Board (ERB) reviewed and approved NHANES study protocols, and all participants provided their written informed consent to participate in this study.

Competing interests

The authors declare no competing interests.

Author Contribution

Shouxin Wei, Sijia Yu contributed to conceptualization and design, investigation, data analysis, visualization,and writing editing and review. Yunsheng Lan and Yingdong Jia participated in methodology, software, image processing, and writing review. Shouxin Wei and Yunsheng Lan contributed to project management, funding acquisition,and supervision. All authors contributed to this paper and approved its publication.

Acknowledgement

Our team sincerely appreciates all the staff and participants whose invaluable contributions have greatly enhanced the NHANES data collection.

Data Availability

The datasets generated and/or analyzed during the current study are available in the NHANES repository, [https://www.cdc.gov/nchs/nhanes/].

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Association between the oxidative balance score and cognitive function: evidence from NHANES 2011-2014

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