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. 2026 Feb 25;16(2):e106954. doi: 10.1136/bmjopen-2025-106954

Associations of oxidative balance score with mortality and cardiovascular events: cohort study from NHANES and UK Biobank

Haotian Zhang 1, Shi Chen 1, Xueke Bai 1, Xingtong Zhou 1, Fengqing Zhang 1, Xiaohu Wang 1, Liang Chen 1,*, Xianqiang Wang 1,✉
PMCID: PMC12958911  PMID: 41748168

Abstract

Abstract

Objective

To investigate the associations of oxidative balance score (OBS) with all-cause mortality, cardiovascular mortality and cardiovascular disease (CVD) incidence in two large, population-based cohorts.

Design

Cohort study and cross-sectional study were used.

Setting

The US National Health and Nutrition Examination Survey (NHANES) and the UK Biobank.

Participants

A total of 33 566 adults from NHANES (1998–2018) and 55 760 adults from the UK Biobank were included.

Main outcome measures

All-cause mortality, cardiovascular mortality and CVD. Mortality outcomes were ascertained through national death registries. Prevalent CVD was identified in NHANES through questionnaire, and incident CVD events were identified in the UK Biobank using linked hospital admission and death registry data.

Results

Higher OBS was consistently associated with lower all-cause and cardiovascular mortality in both cohorts. In NHANES, participants in the highest OBS quartile (Q4) had a 39% lower risk of all-cause mortality (adjusted HR: 0.61, 95% CI 0.52 to 0.72) and a 45% lower risk of cardiovascular mortality (adjusted HR: 0.55, 95% CI 0.41 to 0.74) compared with those in Q1. Similarly, in the UK Biobank, Q4 was associated with an 18% lower risk of all-cause mortality (adjusted HR: 0.82, 95% CI 0.74 to 0.91) and a 41% lower risk of cardiovascular mortality (adjusted HR: 0.59, 95% CI 0.4 to 0.87). In NHANES, Q4 was associated with lower odds of prevalent CVD (adjusted OR: 0.56, 95% CI 0.46 to 0.67), whereas in the UK Biobank, Q4 was associated with a 19% lower risk of incident CVD during follow-up (adjusted HR: 0.81, 95% CI 0.74 to 0.9). Subgroup analyses in NHANES indicated heterogeneity by ethnicity and socioeconomic status, whereas associations in the UK Biobank followed an L-shaped pattern with a flattening of estimated risk at moderate OBS levels.

Conclusion

Higher OBS was associated with more favourable mortality and cardiovascular outcomes. These findings indicate that OBS is a composite indicator associated with cardiovascular health at the population level.

Keywords: oxidative balance score, mortality, cardiovascular disease, cohort study

STRENGTHS AND LIMITATIONS OF THIS STUDY.

  • The use of two representative, high-quality databases enhanced the robustness and reproducibility of the observed associations.

  • The oxidative balance score (OBS) is derived from routinely collected dietary and lifestyle variables, supporting its feasibility for use in population and primary care settings.

  • The observational design limits causal inference despite adjustment for key demographic and socioeconomic factors.

  • Dietary intake and lifestyle factors were assessed at baseline, and changes over time could not be captured.

  • Differences in variable measurement methods between two cohorts may introduce measurement heterogeneity.

Introduction

Oxidative stress (OS) results from an imbalance between pro-oxidative and antioxidative components, leading to cellular damage. Under normal conditions, cellular responses to oxidative damage include upregulation of antioxidative defence mechanisms.1 However, when reactive oxygen species exceed the neutralising capacity of antioxidants, OS occurs,2 which can cause damage to DNA, proteins and lipids, resulting in cell injury and death.3 Both endogenous processes and exogenous factors, including diet, smoking and medication use, influence oxidative balance.4

Although experimental and animal studies have consistently linked OS to inflammation and chronic disease, epidemiological evidence remains inconsistent when individual pro-oxidative or antioxidative factors are examined in isolation.5,8 This inconsistency likely reflects the complex interplay between endogenous oxidative pathways and multiple lifestyle-related exposures, making it challenging to capture overall oxidative status using single biomarkers or exposures.

The oxidative balance score (OBS) was developed as a composite index integrating both pro-oxidative and antioxidative dietary and lifestyle factors.9 By summarising the overall oxidative balance rather than individual components, OBS offers a pragmatic approach for population-based research. Previous studies have reported inverse associations between higher OBS and all-cause or cardiovascular mortality in selected high-risk populations, such as individuals with diabetes or pre-diabetes,10 as well as associations with cardiometabolic and other chronic conditions, including dyslipidaemia, hypertension, metabolic syndrome, kidney disease, depression and cancer.11,16

However, evidence regarding the association between OBS and mortality or cardiovascular disease (CVD) in the general population remains limited, and findings across cohorts have been inconsistent. Large-scale studies examining OBS in diverse populations and across different study designs are scarce. To address these gaps, we investigated the association between OBS and mortality and cardiovascular outcomes using data from two large population-based cohorts: the US National Health and Nutrition Examination Survey (NHANES) and the UK Biobank (UKB).

Subjects and methods

Study population

The US NHANES uses a multistage sampling design to achieve national representativeness. All participants provided written informed consent, and the survey protocol was approved by the Institutional Review Board of the National Center for Health Statistics.17 This study included data from 10 NHANES cycles conducted between 1998 and 2018, comprising 101 316 participants at baseline. Exclusions were made for individuals: (1) under 18 years (n=42 112), (2) lacking dietary or lifestyle data required to calculate the OBS (n=25 587) and (3) with insufficient mortality data (n=51). The final analytic sample included 33 566 participants (figure 1).

Figure 1. Flowchart of inclusion and exclusion standard of participants. CVD, cardiovascular disease; NHANES, National Health and Nutrition Examination Survey; UKB, UK Biobank.

Figure 1

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The UK Biobank recruited over 500 000 participants aged 37–73 years from 22 assessment centres in England, Scotland and Wales between 2007 and 2010.18 This study used data from the UK Biobank Resource under approved application number 87 841. Of the 502 492 participants, exclusions were made for individuals: (1) missing dietary or lifestyle data for OBS calculation (n=4 43 493), (2) lost to follow-up (n=164) and (3) with prevalent CVD at baseline (n=3075). The final sample included 55 760 participants (figure 1).

Assessment of oxidative balance score

The OBS is a composite index reflecting overall antioxidant and pro-oxidant exposure and consists of dietary and lifestyle components.

The dietary component includes 14 nutrients classified as antioxidant or pro-oxidant factors, including fibre, carotenoids (retinol equivalent), vitamins (B6, B12, C and E), folic acid, calcium, magnesium, zinc, copper, selenium, saturated fatty acid and iron.9 19 Dietary intake in NHANES was assessed using two 24-hour dietary recalls, with mean values calculated across both days; when second day data were unavailable, first day data were used. In the UK Biobank, dietary intake was assessed using a single 24-hour dietary questionnaire.

The lifestyle component includes physical activity, body mass index (BMI), smoking status and alcohol consumption. BMI was classified as normal weight, overweight or obesity, with values assigned as 2, 1 and 0, respectively. Alcohol consumption was categorised as heavy drinking (≥15 g/day for women, ≥30 g/day for men), non-drinking (0 g/day), and moderate drinking, with values assigned as 0, 2 and 1, respectively. Physical activity was stratified into tertiles based on metabolic equivalent scores,20 with values assigned as 0, 1 and 2. NHANES data from 2006 onward used a consistent questionnaire design, while earlier cycles were analysed separately. Smoking intensity was assessed using plasma cotinine concentration in NHANES, whereas in UK Biobank, smoking status was categorised as never, occasional, or current/former frequent smoking. All components were trichotomised in a sex-specific manner.

The overall OBS was calculated as the sum of all component scores, ranging from 2 to 38 in NHANES and 3 to 38 in UK Biobank, with higher scores indicating a more favourable oxidative balance (online supplemental tables 2 and 3).

Ascertainment of outcomes

Study outcomes included all-cause mortality, cardiovascular mortality and CVD events.

In NHANES, mortality data were obtained from the National Death Index up to 31 December 2019. Cardiovascular mortality was defined using ICD-10 (international classification of diseases, 10th revisions) codes (I00–I09, I11, I13 and I20–I51). CVD events were self-reported based on a validated questionnaire, which inquired about diagnoses of congestive heart failure, stroke, angina, myocardial infarction or coronary heart disease.

In UK Biobank, mortality data were obtained from death certificates through 30 April 2020. Incident CVD events, including myocardial infarction and stroke, were identified using linked hospital admission records and death registry data. Myocardial infarction was defined using ICD-9 (international classification of diseases, 9th revisions) codes 410–412 and 429.79, and ICD-10 codes I21–I23, I24.1 and I25.2, while stroke was defined using ICD-9 codes 430, 431, 434 and 436 and ICD-10 codes I60, I61, I63 and I64. Follow-up for incident CVD events was available through 19 December 2022.

Covariates

Covariates included age, sex, race/ethnicity (White vs other), educational attainment (less than high school, high school or equivalent, and more than high school), and socioeconomic indicators. In NHANES, socioeconomic status was assessed using the poverty-to-income ratio (≤1.3, 1.3–3.5, and >3.5),21 while in the UK Biobank, total household income before tax was categorised as <£30 999, £31 000–51 999, or >£52 000.

Histories of hypertension, diabetes and dyslipidaemia were defined using standard clinical, laboratory and self-reported criteria (online supplemental methods) and were considered as potential effect modifiers rather than covariates in the primary adjusted models.

Statistical analysis

All analyses in NHANES accounted for the complex sampling design using weighted analyses. Baseline characteristics were summarised across quartiles of OBS for NHANES and sex-specific quartiles for the UK Biobank. Categorical variables were presented as counts and percentages, and continuous variables as medians with IQRs. Differences were tested using the Rao-Scott χ2 test for categorical variables and the Kruskal-Wallis test for continuous variables.

The associations between OBS and mortality outcomes were assessed using multivariable Cox proportional hazards models with two levels of adjustment: (1) unadjusted, (2) adjusted for age, gender and race/ethnicity, education level, poverty-to-income ratio/family total income. For CVD events, logistic regression was used in NHANES due to its cross-sectional design, while Cox regression was applied to the UK Biobank cohort.

Restricted cubic splines and forest plots based on fully adjusted models were used to visualise the relationship between OBS and outcomes. Subgroup analyses and interaction tests were conducted by sex, age (<65 vs ≥65 years), race, education, income level and history of hypertension, diabetes and dyslipidaemia.

All statistical analyses were performed using R software (V.4.4.1; R Foundation for Statistical Computing, Vienna, Austria), with significance set at p<0.05.

Results

Characteristics of the study population

The study included 33 566 participants from NHANES (median age 46 years, 51% male) and 55 760 from the UK Biobank (median age 58 years, 45% male). Baseline characteristics stratified by OBS quartiles are summarised in online supplemental table 1.

Participants with higher OBS were more likely to be White and to have higher education attainment in both cohorts (all p<0.001). Higher OBS quartiles were also associated with a lower prevalence of hypertension, diabetes and dyslipidaemia (all p<0.001).

Associations of the OBS with mortality and cardiovascular events

During a median follow-up of 113 months (IQR: 63–167), 3157 deaths were recorded in NHANES, including 754 deaths due to CVD. In the UK Biobank, 3053 deaths were documented over a median follow-up of 157.2 months (IQR: 153.1–160.9), of which 219 were attributed to CVD.

In addition, 2571 NHANES participants had prevalent CVD, whereas among participants without baseline CVD in the UK Biobank, 3807 incident CVD events occurred during a median follow-up of 92.2 months (IQR: 49.1–125.5). Kaplan-Meier survival analysis revealed significant differences in all-cause and cardiovascular mortality rates across OBS quartiles in both cohorts (log-rank p<0.001; figure 2).

Figure 2. Kaplan-Meier analyses for mortality among the four groups. Q1–Q4 quartiles based on OBS. NHANES, National Health and Nutrition Examination Survey; OBS, oxidative balance score; UKB, UK Biobank.

Figure 2

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Table 1 summarises the Cox and logistic regression models evaluating the association between OBS and all-cause mortality, cardiovascular mortality and CVD events. In both cohorts and for all three outcomes, higher OBS was consistently associated with a reduced risk of mortality and cardiovascular events.

Table 1. Associations of OBS with mortality and incident cardiovascular disease.

Model 1 Model 2
Group Characteristic HR 95% CI P value HR 95% CI P value
All-cause death US NHANES
OBS 0.97 0.96 to 0.98 <0.001 0.98 0.97 to 0.98 <0.001
OBS (quartile)
Q1 — — — —
Q2 0.89 0.79 to 1.01 0.070 0.92 0.79 to 1.06 0.2
Q3 0.68 0.60 to 0.77 <0.001 0.73 0.64 to 0.84 <0.001
Q4 0.52 0.45 to 0.59 <0.001 0.61 0.52 to 0.72 <0.001
UK Biobank
OBS 0.99 0.98 to 0.99 <0.001 0.99 0.98 to 0.99 <0.001
OBS (quartile)
Q1 — — — —
Q2 0.88 0.80 to 0.97 0.013 0.85 0.77 to 0.95 0.003
Q3 0.83 0.76 to 0.92 <0.001 0.83 0.74 to 0.92 <0.001
Q4 0.86 0.78 to 0.95 0.004 0.82 0.74 to 0.91 <0.001
Cardiovascular death US NHANES
OBS 0.96 0.96 to 0.97 <0.001 0.97 0.96 to 0.98 <0.001
OBS (quartile)
Q1 — — — —
Q2 1.04 0.83 to 1.29 0.7 1.09 0.86 to 1.38 0.5
Q3 0.71 0.53 to 0.95 0.023 0.81 0.59 to 1.11 0.2
Q4 0.44 0.33 to 0.57 <0.001 0.55 0.41 to 0.74 <0.001
UK Biobank
OBS 0.97 0.95 to 0.99 0.003 0.97 0.95 to 0.99 0.002
OBS (quartile)
Q1 — — — —
Q2 0.66 0.46 to 0.94 0.023 0.63 0.43 to 0.92 0.016
Q3 0.67 0.47 to 0.96 0.031 0.66 0.45 to 0.96 0.032
Q4 0.70 0.49 to 1.01 0.055 0.59 0.40 to 0.87 0.008
Cardiovascular events US NHANES
OBS 0.97 0.96 to 0.97 <0.001 0.97 0.96 to 0.98 <0.001
OBS (quartile)
Q1 — — — —
Q2 0.78 0.68 to 0.90 <0.001 0.79 0.68 to 0.92 0.003
Q3 0.66 0.57 to 0.77 <0.001 0.72 0.61 to 0.84 <0.001
Q4 0.48 0.41 to 0.57 <0.001 0.56 0.46 to 0.67 <0.001
UK Biobank
OBS 0.99 0.98 to 0.99 <0.001 0.99 0.98 to 0.99 <0.001
OBS (quartile)
Q1 — — — —
Q2 0.90 0.82 to 0.98 0.014 0.88 0.80 to 0.96 0.005
Q3 0.84 0.77 to 0.92 <0.001 0.87 0.79 to 0.95 0.003
Q4 0.84 0.76 to 0.91 <0.001 0.81 0.74 to 0.90 <0.001
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Model 1 was unadjusted for covariates. Model 2 was adjusted for sex, age, race/ethnicity, education level, and poverty-to-income ratio/family total income.

Statistical significance was defined as a P value < \0.05. Values in bold indicate statistically significant differences.

NHANES, National Health and Nutrition Examination Survey; OBS, oxidative balance score.

In NHANES, the highest OBS quartile (Q4) was associated with a 39% lower risk of all-cause mortality (adjusted HR: 0.61, 95% CI 0.52 to 0.72) and a 45% lower risk of cardiovascular mortality (adjusted HR: 0.55, 95% CI 0.41 to 0.74) compared with Q1. Similarly, in the UK Biobank, Q4 was associated with an 18% lower risk of all-cause mortality (adjusted HR: 0.82, 95% CI 0.74 to 0.91) and a 41% lower risk of cardiovascular mortality (adjusted HR: 0.59, 95% CI 0.4 to 0.87).

Moreover, higher OBS was consistently associated with lower CVD incidence. In NHANES, participants in Q4 had lower odds of prevalent CVD compared with Q1 (adjusted OR: 0.56, 95% CI 0.46 to 0.67). In contrast, in the UK Biobank cohort, Q4 was associated with a 19% lower risk of incident CVD during follow-up (adjusted HR: 0.81, 95% CI 0.74 to 0.9). Restricted cubic spline analyses revealed a non-linear association between OBS and outcomes (figure 3). In the UK Biobank, the relationship between OBS and outcomes followed an L-shaped pattern (p for non-linearity: <0.001 for all-cause mortality; p for non-linearity: 0.003 for CVD events), with a flattening of the estimated risk at moderate OBS levels.

Figure 3. The association of OBS with mortality and prevalent/incident cardiovascular disease visualised by restricted cubic spline. OBS, oxidative balance score; NHANES, National Health and Nutrition Examination Survey; UKB, UK Biobank.

Figure 3

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Subgroup analyses

Subgroup analyses confirmed the robustness of these associations across age, sex, race, socioeconomic strata and medical history (online supplemental figures 1.1 to 1.6). Overall, higher OBS was consistently associated with lower all-cause mortality and CVD incidence across most predefined subgroups. Notably, statistically significant interactions were observed by race/ethnicity (p for interaction=0.008), education level (p for interaction <0.001) and income level (p for interaction=0.026) between OBS and all-cause mortality in NHANES. The inverse association between them appeared stronger among White participants, individuals with higher educational attainment and those with higher income levels. However, no significant interaction effects were observed in the UK Biobank cohort.

Discussion

This study examined the association between the OBS and mortality and cardiovascular outcomes in two large population-based cohorts, NHANES and the UK Biobank. Across both cohorts, higher OBS was consistently associated with more favourable mortality and cardiovascular profiles.

Subgroup analyses revealed heterogeneity in the NHANES cohort, with a stronger inverse association between OBS and all-cause mortality among White participants and individuals with higher education and income levels. These findings suggest that the OBS–mortality association may be influenced by socioeconomic context. Differences in access to nutrient-dense foods, preventive healthcare and health-related resources may partly explain the stronger associations observed in socioeconomically advantaged groups, whereas structural constraints may attenuate observable associations in disadvantaged populations.22

In contrast, the OBS–outcome association in the UK Biobank followed an L-shaped pattern, with a flattening of estimated risk at moderate OBS levels. This difference may reflect variations in baseline risk profiles, age distribution and socioeconomic characteristics between the two cohorts, underscoring the importance of interpreting OBS within population-specific contexts.

Unlike prior studies conducted in single cohorts or selected high-risk populations (eg, diabetes or pre-diabetes),10 23 our analysis leveraged two large, independent population-based cohorts, supporting the generalisability of the association between OBS and cardiovascular outcomes across different settings. Our findings are consistent with previous cross-sectional analyses in NHANES, in which Chen et al and Chen et al reported inverse associations between higher OBS and cardiovascular risk.24 25

Extending these observations, we analysed a broader range of NHANES cycles (1998–2018) and examined the OBS–CVD association in the UK Biobank using a longitudinal cohort design. In addition, prior cohort studies have reported similar associations between higher OBS and lower risks of cardiovascular and all-cause mortality in specific populations, including individuals with non-alcoholic fatty liver disease and participants in the Seguimiento Universidad de Navarra (SUN) Study.26 27 Collectively, these findings suggest that OBS is a reproducible composite indicator associated with cardiometabolic health across diverse populations.12 28 29

Although OBS integrates multiple dietary and lifestyle components, its constituent variables are routinely assessed in clinical and epidemiological settings. As such, OBS may serve as a pragmatic summary measure of oxidative balance at the population level. Rather than functioning as a standalone clinical tool, OBS could help identify individuals or groups with less favourable lifestyle profiles who may benefit from targeted preventive strategies, such as dietary modification or smoking cessation, in future intervention studies.

Strengths and limitations

This study has notable methodological strengths. The use of two large, population-based datasets enhances the robustness and reproducibility of the observed associations. In addition, the OBS is derived from routinely collected dietary and lifestyle variables, supporting its feasibility for use in population and primary care settings. Nevertheless, our study has several limitations. First, the observational design limits causal inference despite adjustment for key demographic and socioeconomic factors. Second, dietary intake and lifestyle factors were assessed at baseline, and changes over time could not be captured. Third, differences in variable measurement methods between two cohorts may introduce measurement heterogeneity.

Conclusion

In two large population-based cohorts, higher OBS was associated with more favourable mortality and cardiovascular outcomes. These findings indicate that OBS is a composite indicator associated with cardiovascular health at the population level.

Supplementary material

online supplemental file 1
bmjopen-16-2-s001.docx (1.8MB, docx)
DOI: 10.1136/bmjopen-2025-106954
online supplemental file 2
bmjopen-16-2-s002.docx (18.2KB, docx)
DOI: 10.1136/bmjopen-2025-106954

Acknowledgements

All authors have read and approved the final manuscript and affirm its honesty. We appreciate the staff and the participants of the National Health and Nutrition Examination Survey and UK Biobank study for their valuable contribution. Artificial intelligence was only employed to refine the manuscript’s language.

Footnotes

Funding: Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2024–12M-ZD-002); Beijing Higher Education Institutions (2024-BZZQ01); Key Technologies Research and Development Program (2023YFC2414401).

Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2025-106954).

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Ethics approval: The National Health and Nutrition Examination Survey (NHANES) study was conducted with ethical approval from the National Centre for Health Statistics’ Research Ethics Review Board. All participants in the NHANES study provided written informed consent prior to participation. Moreover, the UK Biobank received ethical approval from the North West Multi-centre Research Ethics Committee. This study used data from the UK Biobank Resource under approved application number 87 841.

Data availability statement

NHANES data are available in a public, with URL https://www.cdc.gov/nchs/nhanes/. UKB data may be obtained from a third party and are not publicly available. Applications to access UKB data can be made via https://www.ukbiobank.ac.uk.

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    online supplemental file 1
    bmjopen-16-2-s001.docx (1.8MB, docx)
    DOI: 10.1136/bmjopen-2025-106954
    online supplemental file 2
    bmjopen-16-2-s002.docx (18.2KB, docx)
    DOI: 10.1136/bmjopen-2025-106954

    Data Availability Statement

    NHANES data are available in a public, with URL https://www.cdc.gov/nchs/nhanes/. UKB data may be obtained from a third party and are not publicly available. Applications to access UKB data can be made via https://www.ukbiobank.ac.uk.

    Articles from BMJ Open are provided here courtesy of BMJ Publishing Group

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