Abstract
Epilepsy, a prevalent chronic neurological disorder, has significant neurobiological, cognitive, psychological, and social implications. The American Heart Association (AHA) introduced Life’s Essential 8 as a key metric for assessing cardiovascular health. This study aims to investigate the association between Life’s Essential 8 and epilepsy prevalence, offering population-level evidence on the potential clinical and public health relevance of cardiovascular health in individuals with epilepsy. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2013 to 2018. A cross-sectional design was used, and logistic regression models, subgroup analyses were utilized to assess the association between LE8 and the prevalence of epilepsy. Restricted cubic splines were utilized to examine the nonlinear correlations. A total of 9408 participants were included in the study. After adjusting for potential confounding factors, LE8 showed a significant inverse association with the odds of epilepsy (odds ratio = 0.98, 95% confidence interval [CI]: 0.96–0.99). Restricted cubic spline analysis revealed a linear relationship between LE8 and the odds of epilepsy (P for nonlinearity = .658). Further analysis indicated that the diet score was significantly inversely associated with the odds of epilepsy (odds ratio = 0.99, 95% CI: 0.98–0.99). Subgroup analysis showed no significant interaction between confounding factors and LE8 on the odds of epilepsy (all interaction P values > .05). Higher LE8 scores were independently associated with lower odds of epilepsy. Despite the modest effect size, these findings suggest potential clinical and public health implications, highlighting the importance of promoting cardiovascular health behaviors, particularly dietary improvements, in relation to epilepsy prevalence.
Keywords: cross‑sectional study, epilepsy, health behavior, life’s essential 8, National Health andNutrition Examination Survey (NHANES)
1. Introduction
Epilepsy is one of the most common chronic nervous system diseases. More than 80 new seizures occur every year per 100,000 people, most commonly occurring in childhood and old age.[1] In addition to causing more than 125,000 deaths annually, epilepsy is also associated with substantial disability.[2] According to the 2015 World Health Organization Epilepsy Burden Report, epilepsy accounts for 0.5% of the total global disease burden.[3] Current treatments mainly involve pharmacological treatment, but most antiepileptic drugs are deficient in epilepsy prevention and neuroprotection,[4] emphasizing the urgent need for more effective prevention and treatment methods.
Given these limitations in pharmacological approaches, growing attention has been directed toward identifying modifiable risk factors that may influence epilepsy occurrence and progression. Among these, cardiovascular health has been increasingly recognized as a potential factor influencing the occurrence and progression of epilepsy, with mechanisms such as systemic inflammation, oxidative stress, and vascular dysfunction playing critical roles.[5–10] Notably, cardiovascular health encompasses not only traditional clinical biomarkers but also lifestyle behaviors, with dietary patterns being particularly relevant to both cardiovascular outcomes and neurological conditions. Evidence suggests that a balanced diet can reduce seizure frequency and severity, with the high-fat, low-carbohydrate ketogenic diet demonstrating significant efficacy in treating epilepsy spectrum disorders in clinical practice.[11,12] However, current research in this field remains fragmented, often focusing on isolated aspects such as cardiovascular risk factors or dietary interventions, rather than adopting a holistic approach. This lack of a comprehensive assessment tool limits our ability to evaluate the multifactorial interactions between cardiovascular health, dietary behaviors, and epilepsy.
To address this gap, there is a need for an integrated metric that can simultaneously capture multiple dimensions of cardiovascular health and related lifestyle factors. Life’s Essential 8 (LE8), a recently proposed metric by the AHA, provides a comprehensive framework for assessing cardiovascular health.[13] It integrates 8 key components, including diet, physical activity, nicotine exposure, sleep health, body mass index (BMI), blood lipids, blood glucose, and blood pressure, offering a unified and standardized approach to evaluate overall cardiovascular health. The use of LE8 in epilepsy research holds significant advantages,[14,15] as it allows simultaneous assessment of multiple interrelated factors, providing a more comprehensive understanding of their combined association with the odds of epilepsy.
Based on these considerations, this study aimed to examine the association between LE8 and epilepsy using data from the NHANES. We hypothesized that higher LE8 scores, reflecting better cardiovascular health, would be associated with lower odds of epilepsy.
2. Materials and methods
2.1. Study populations
NHANES is a large-scale, continuous, and nationally representative health assessment program administered by the Centers for Disease Control and Prevention. 16] We conducted our study using data from the 2013 to 2018 cycles of NHANES, including participants aged 20 years or older. Through a rigorous screening process, we excluded individuals with missing LE8 assessment data or incomplete key covariate information. Participants with missing data were excluded using a complete-case analysis approach. Ultimately, a total of 9408 eligible participants were included in the final analysis (Fig. 1).
Figure 1.
The flowchart of participant selection. NHANES = National Health and Nutrition Examination Survey, LE8 = Life’s Essential 8.
2.2. Assessment of LE8
LE8 is a comprehensive and validated framework designed to assess cardiovascular health through 8 modifiable components: blood pressure, non-hdl cholesterol, blood glucose, smoking status, physical activity, diet quality, BMI and sleep duration. Each component was operationalized based on the detailed definitions and scoring criteria provided in the AHA guidelines, as outlined in Table S1, Supplemental Digital Content 1. The overall score, ranging from 0 to 100, was calculated as the unweighted average of the 8 component metric scores. Based on this scoring system, overall LE8 was categorized into 3 levels: high LE8 (80 –100 points), moderate LE8 (50–79 points), and low LE8 (0–49 points).
2.3. Evaluation of epilepsy
Data on epilepsy were obtained from the Prescription Drugs section of NHANES. Participants were asked whether they had taken any prescription medications in the past 30 days for the treatment of “epilepsy and recurrent seizures.” The corresponding International Classification of Diseases, Tenth Revision, Clinical code (G40) provided in NHANES was used to categorize the reported indication for medication use. Participants who reported using medications for epilepsy or recurrent seizures during the past 30 days were classified as having epilepsy in the present analysis.[17]
2.4. Covariates
We collected data on the following covariates: age, gender, race, marital status, education level, family income-to-poverty ratio, and drinking status. Participants’ race was categorized into 4 groups: White, Black, Mexican American, and Other races. Marital status was classified as married or other. Family income-to-poverty ratio was divided into 3 groups: below $13,000, between $13,000 and $34,900, and above $35,000. Drinking status was categorized as never, former, or current. Additionally, diabetes and hypertension were determined based on participants’ self-reported diagnoses or current use of medications for these conditions.
2.5. Sensitivity analyses
To assess the robustness of our findings, we conducted a sensitivity analysis by applying NHANES examination sampling weights. The results from the weighted analyses were compared with those from the primary unweighted models to evaluate the potential impact of the sampling design on our estimates.
2.6. Statistical analysis
Continuous variables are presented as means with standard deviations, while categorical variables are described as frequencies and percentages. For statistical analysis, the chi-square test was employed to evaluate categorical variables, and 1-way analysis of variance was utilized to assess normally distributed continuous variables.The association between LE8 and the odds of epilepsy was analyzed using logistic regression models. Three models were constructed: the Crude model was unadjusted; Model 1a was adjusted for age, gender, race, marital status, education level, and family poverty income ratio (PIR); and Model 2b was further adjusted for alcohol consumption, hypertension, and diabetes history. Subgroup analyses were also performed while accounting for confounding variables. Restricted cubic splines were used to explore potential nonlinear relationships. All analyses were conducted using R software (version 4.4.0), and a 2-sided P value < .05 was considered statistically significant. The primary analyses were performed without NHANES sampling weights, whereas weighted analyses were additionally conducted as sensitivity analyses.
3. Result
Of the initial 17,057 participants aged ≥20 years, 5683 (33.3%) were excluded due to missing LE8 data, and an additional 1966 (11.5%) were excluded due to missing covariate data. Compared with included participants, those excluded were more likely to be older, have lower educational levels, and have a higher prevalence of hypertension and diabetes (all P < .05). Table 1 shows the baseline characteristics of the participants, categorized into low (n = 1147, 12.19%), moderate (n = 6280, 66.75%), and high (n = 1981, 21.06%) LE8 groups. The overall prevalence of epilepsy in the study population was 0.88%, with the highest prevalence observed in the low LE8 group (2.01%), compared with 0.83% in the moderate LE8 group and 0.40% in the high LE8 group, corresponding to an absolute difference of 1.61 percentage points between the low and high LE8 groups.
Table 1.
Baseline characteristics of the study population.
| Variables | Total (n = 9048) |
Low LE8 (n = 1147) |
Moderate LE8 (n = 6280) |
High LE8 (n = 1981) | P |
|---|---|---|---|---|---|
| Age, yr | 49.56 ± 17.35 | 56.49 ± 14.42 | 50.91 ± 17.27 | 41.29 ± 16.18 | <.001 |
| Sex | <.001 | ||||
| Female | 4550 (48.36) | 552 (48.13) | 3196 (50.89) | 802 (40.48) | |
| Male | 4858 (51.64) | 595 (51.87) | 3084 (49.11) | 1179 (59.52) | |
| Race | <.001 | ||||
| Non-hispanic White | 3927 (41.74) | 479 (41.76) | 2592 (41.27) | 856 (43.21) | |
| Non-hispanic Black | 1905 (20.25) | 314 (27.38) | 1355 (21.58) | 236 (11.91) | |
| Mexican-American | 1303 (13.85) | 169 (14.73) | 897 (14.28) | 237 (11.96) | |
| Other | 2273 (24.16) | 185 (16.13) | 1436 (22.87) | 652 (32.91) | |
| Marital status | <.001 | ||||
| Married | 4902 (52.10) | 545 (47.52) | 3278 (52.20) | 1079 (54.47) | |
| Other | 4506 (47.90) | 602 (52.48) | 3002 (47.80) | 902 (45.53) | |
| Education level | <.001 | ||||
| High school below | 1646 (17.50) | 324 (28.25) | 1144 (18.22) | 178 (8.99) | |
| High school | 2139 (22.74) | 323 (28.16) | 1539 (24.51) | 277 (13.98) | |
| High school above | 5623 (59.77) | 500 (43.59) | 3597 (57.28) | 1526 (77.03) | |
| PIR, million (%) | <.001 | ||||
| <1.3 | 2759 (29.33) | 479 (41.76) | 1881 (29.95) | 399 (20.14) | |
| 1.3–3.49 | 3618 (38.46) | 493 (42.98) | 2446 (38.95) | 679 (34.28) | |
| ≥3.5 | 3031 (32.22) | 175 (15.26) | 1953 (31.10) | 903 (45.58) | |
| Drinking status | <.001 | ||||
| Never | 1279 (13.59) | 125 (10.90) | 830 (13.22) | 324 (16.36) | |
| Former | 1158 (12.31) | 242 (21.10) | 795 (12.66) | 121 (6.11) | |
| Current | 6971 (74.10) | 780 (68.00) | 4655 (74.12) | 1536 (77.54) | |
| Hypertension | <.001 | ||||
| No | 5335 (56.71) | 284 (24.76) | 3329 (53.01) | 1722 (86.93) | |
| Yes | 4073 (43.29) | 863 (75.24) | 2951 (46.99) | 259 (13.07) | |
| Diabetes | <.001 | ||||
| No | 7773 (82.62) | 627 (54.66) | 5209 (82.95) | 1937 (97.78) | |
| Yes | 1635 (17.38) | 520 (45.34) | 1071 (17.05) | 44 (2.22) | |
| Epilepsy | <.001 | ||||
| No | 9325 (99.12) | 1124 (97.99) | 6228 (99.17) | 1973 (99.60) | |
| Yes | 83 (0.88) | 23 (2.01) | 52 (0.83) | 8 (0.40) | |
| LE8 scores | 67.07 ± 14.64 | 41.98 ± 6.32 | 65.42 ± 8.06 | 86.82 ± 5.09 | <.001 |
| Diet score | 39.77 ± 31.36 | 21.32 ± 23.56 | 36.84 ± 29.95 | 59.73 ± 29.71 | <.001 |
| Physical activity score | 70.91 ± 42.37 | 29.35 ± 42.62 | 70.96 ± 42.05 | 94.83 ± 17.34 | <.001 |
| Nicotine exposure score | 72.03 ± 38.62 | 43.86 ± 42.52 | 70.71 ± 38.88 | 92.53 ± 19.03 | <.001 |
| Sleep health score | 82.35 ± 24.84 | 66.09 ± 30.97 | 82.30 ± 24.33 | 91.90 ± 15.97 | <.001 |
| Body mass index score | 57.90 ± 34.28 | 31.23 ± 28.89 | 54.39 ± 32.96 | 84.44 ± 22.34 | <.001 |
| Blood lipids score | 66.93 ± 29.81 | 47.41 ± 29.57 | 64.61 ± 28.88 | 85.57 ± 22.05 | <.001 |
| Blood glucose score | 81.00 ± 27.10 | 55.31 ± 30.30 | 80.79 ± 26.29 | 96.57 ± 11.91 | <.001 |
| Blood pressure score | 65.66 ± 32.12 | 41.29 ± 29.83 | 62.74 ± 31.12 | 89.01 ± 20.01 | <.001 |
LE8 = Life’s Essential 8, PIR = family income to poverty ratio.
The average age of all participants was 49.56 years, and the majority were female (51.64%) and Non-hispanic White (41.74%). Participants with high LE8 were significantly younger (41.29 years), more likely to have higher educational levels (77.03% above high school), and had higher PIR values (PIR ≥ 3.5: 45.58%). Conversely, the low LE8 group exhibited older age, lower education levels, lower income, and higher prevalence of hypertension (75.24%) and diabetes (45.34%). All comparisons across demographic, socioeconomic, and clinical characteristics were statistically significant (all P < .001). Regarding the 8 components of the LE8, participants in the high LE8 group consistently achieved significantly higher scores compared to those in the low and moderate groups. The largest gap was observed in the diet score, with the high LE8 group scoring 59.73 ± 29.71, compared to 21.32 ± 23.56 in the low LE8 group (difference: 38.41 points). Other notable gaps were identified in physical activity (difference: 65.48 points), nicotine exposure (difference: 48.67 points), and BMI (difference: 53.21 points).
3.1. The association between LE8 and epilepsy
Table 2 presents the logistic regression analysis examining the association between LE8 and the odds of epilepsy. In the crude model, a higher continuous LE8 score was significantly associated with a reduced odds of epilepsy (odds ratio [OR] 0.97 [95% CI 0.96–0.98], P < .001). When analyzed by LE8 categories, participants with moderate LE8 exhibited 59% lower odds of epilepsy (OR 0.41 [95% CI 0.25–0.67], P < .001), and those with high LE8 showed 80% lower odds of epilepsy (OR 0.20 [95% CI 0.09–0.44], P < .001), compared to the low LE8 group. The trend across categories was statistically significant (P for trend < .001). In Model 1, after adjusting for age, sex, race, marital status, education, and PIR, the continuous LE8 score was inversely associated with the odds of epilepsy (OR 0.98 [95% CI 0.96–0.99], P = .003). Compared to the low LE8 group, participants in the moderate and high LE8 groups had 52% (OR 0.48 [95% CI 0.29–0.79], P = .004) and 72% (OR 0.28 [95% CI 0.12–0.67], P = .004) lower odds of epilepsy, respectively, with a significant trend (P for trend = .001). In Model 2, which further adjusted for drinking status, hypertension, and diabetes, the protective association of LE8 remained significant. The continuous LE8 score was still significantly associated with lower odds of epilepsy (OR 0.98 [95% CI 0.96–0.99], P = .01). Participants with moderate and high LE8 had 53% (OR 0.47 [95% CI 0.27–0.80], P = .01) and 72% (OR 0.28 [95% CI 0.11–0.69], P = .01) lower odds of epilepsy compared to the low LE8 group, with a consistently significant trend (P for trend = .002). Although the per-point effect size of continuous LE8 was modest, the categorical analyses and absolute prevalence differences suggest a meaningful population-level gradient across LE8 categories.
Table 2.
Logistic regression analysis on the association between LE8 and the odds of epilepsy.
| Crude model | Model 1* | Model 2† | ||||
|---|---|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | |
| LE8 (continuous) | 0.97 (0.96,0.98) | <.001 | 0.98 (0.96,0.99) | .003 | 0.98 (0.96,0.99) | .01 |
| LE8 (categories) | ||||||
| Low | Ref. | Ref. | Ref. | |||
| Moderate | 0.41 (0.25,0.67) | <.001 | 0.48 (0.29,0.79) | .004 | 0.47 (0.27,0.80) | .01 |
| High | 0.20 (0.09,0.44) | <.001 | 0.28 (0.12,0.67) | .004 | 0.28 (0.11,0.69) | .01 |
| P for trend | <.001 | .001 | .002 |
CI = confidence interval, LE8 = Life’s Essential 8, OR = odds ratio, PIR = family income-to-poverty ratio.
Model 1: adjusted for age, sex, race, marital status, education, and PIR.
Model 2: model 1 + drinking status, hypertension, and diabetes.
3.2. Sensitivity analysis
To address potential concerns regarding the non-application of NHANES sampling weights, we conducted a sensitivity analysis applying the recommended examination weights (MEC weights). Table 3 presents the weighted logistic regression results examining the association between LE8 and epilepsy. In the crude model, each 1-point increase in LE8 score was associated with lower odds of epilepsy (OR 0.97, 95% CI 0.96–0.98; P < .001), corresponding to a 3% decrease in the odds of epilepsy. After adjusting for demographic and socioeconomic factors (Model 1), the association remained significant (OR 0.98 [95% CI 0.96–0.99], P = .002), and persisted in the fully adjusted model (OR 0.98 [95% CI 0.96–0.99], P = .01).
Table 3.
Sensitivity analysis on the association between LE8 and the odds of epilepsy.
| Crude model | Model 1* | Model 2† | ||||
|---|---|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | |
| LE8 (continuous) | 0.97 (0.96,0.98) | <.001 | 0.98 (0.96,0.99) | .002 | 0.98 (0.96,0.99) | .01 |
| LE8 (categories) | ||||||
| Low | Ref. | Ref. | Ref. | |||
| Moderate | 0.45 (0.29,0.70) | <.001 | 0.51 (0.32,0.82) | .010 | 0.49 (0.29,0.82) | .01 |
| High | 0.25 (0.23,0.50) | <.001 | 0.36 (0.16,0.79) | .010 | 0.35 (0.15,0.82) | .02 |
| P for trend | <.001 | .01 | .02 |
CI = confidence interval, LE8 = Life’s Essential 8, OR = odds ratio, PIR = family income-to-poverty ratio.
Model 1: adjusted for age, sex, race, marital status, education, and PIR.
Model 2: model 1 + drinking status, hypertension, and diabetes.
When analyzed by LE8 categories, participants with moderate LE8 exhibited 51% lower odds of epilepsy (OR 0.51 [95% CI 0.32–0.82], P = .01) in Model 1 and 51% lower odds [OR 0.49 (95% CI 0.29–0.82), P = .01] in Model 2, compared to the low LE8 group. Those with high LE8 showed 64% lower odds (OR 0.36 [95% CI 0.16–0.79], P = .01) in Model 1 and 65% lower odds (OR 0.35 [95% CI 0.15–0.82], P = .02) in Model 2. The trend across categories remained statistically significant in all models (P for trend = .01 in Model 1 and P for trend = .02 in Model 2). These findings were highly consistent with the primary unweighted analysis, indicating that the non-application of sampling weights did not materially bias the parameter estimates.
3.3. The association between the components of LE8 and epilepsy
Table 4 presents the results of logistic regression analyses examining the association between the components of the LE8 and the odds of epilepsy. In the crude model, a higher diet score was significantly associated with lower odds of epilepsy (OR, 0.98; 95% CI, 0.98–0.99; P < .001). This association remained significant in Model 1 (adjusted for age, sex, race, marital status, education, and family income-to-poverty ratio), with an OR of 0.99 (95% CI: 0.98–0.99, P < .001) and continued to be significant in Model 2 (further adjusted for drinking status, hypertension, and diabetes) with an OR of 0.99 (95% CI: 0.98–0.99, P < .001).
Table 4.
Logistic regression analysis on the association between LE8 components and the odds of epilepsy.
| Crude model | Model 1* | Model 2† | ||||
|---|---|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | |
| Diet score | 0.98 (0.98,0.99) | <.001 | 0.99 (0.98,0.99) | <.001 | 0.9 (0.98,0.99) | <.001 |
| Physical activity score | 0.99 (0.99,1.00) | .01 | 1.00 (0.99,1.00) | .05 | 1.0 (0.99,1.00) | .07 |
| Nicotine exposure score | 0.99 (0.99,1.00) | .02 | 1.00 (0.99,1.00) | .30 | 1.00 (0.99,1.00) | .19 |
| Sleep health score | 0.99 (0.98,1.00) | .02 | 0.99 (0.99,1.00) | .13 | 0.99 (0.99,1.00) | .15 |
| Body mass index score | 0.99 (0.99,1.00) | .06 | 0.99 (0.99,1.00) | .08 | 1.00 (0.99,1.00) | .14 |
| Blood lipids score | 1.00 (0.99,1.01) | .78 | 1.00 (0.99,1.01) | .92 | 1.00 (0.99,1.01) | .97 |
| Blood glucose score | 1.00 (0.99,1.01) | .73 | 1.00 (0.99,1.01) | .73 | 1.00 (0.99,1.02) | .43 |
| Blood pressure score | 1.00 (0.99,1.00) | .27 | 1.00 (0.99,1.01) | 0.98 | 1.00 (1.00,1.01) | .37 |
CI = confidence interval, LE8 = Life’s Essential 8, OR = odds ratio, PIR = family income-to-poverty ratio.
Model 1: adjusted for age, sex, race, marital status, education, and PIR.
Model 2: model 1 + drinking status, hypertension, and diabetes.
The physical activity score showed a marginally significant association in the crude model (OR 0.99, P = .01), but this was not significant after adjustments in Models 1 and 2 (OR 1.00, P = .05 and OR 1.00, P = .07, respectively). Likewise, the nicotine exposure score was associated with lower odds of epilepsy in the crude model (OR 0.99, P = .02); however, this association was no longer statistically significant after adjustment (OR 1.00, P = .30 in Model 1 and OR 1.00, P = .19 in Model 2).The sleep health score also demonstrated a significant association in the crude model (OR 0.99, P = .02), but was not significant in the adjusted models (OR 0.99, P = .13 in Model 1 and OR 0.99, P = .15 in Model 2). The body mass index score showed a trend towards significance in the crude and adjusted models, with ORs of 0.99 (P = .06) and 0.99 (P = .08), but did not reach significance in Model 2 (OR 1.00, P = .14). The blood lipids, blood glucose, and blood pressure scores were not significantly associated with the odds of epilepsy in any model, with ORs near 1.00 and P values above .05. In summary, the diet score consistently showed a protective effect against epilepsy across all models, while other components exhibited variable associations that were often attenuated after adjustment for confounding factors. These findings suggest that the observed association between overall LE8 and epilepsy may be primarily driven by dietary quality rather than uniform effects across all components.
3.4. Subgroup analyses for the association between LE8 and the odds of epilepsy
Table 5 shows the results of the subgroup analysis, revealing a consistent association between the LE8 score and the odds of epilepsy across various demographic and health-related subgroups. Notably, no significant interactions were found for sex, race, marital status, education level, PIR, drinking status, hypertension, or diabetes, indicating that the association was independent of these factors (all P values for interaction > .05).
Table 5.
Subgroup analyses for the association between LE8 and the odds of epilepsy.
| Variables | OR (95% CI) |
P
|
P for interaction |
|---|---|---|---|
| Sex | .42 | ||
| Male | 0.97 (0.94,0.99) | .01 | |
| Female | 0.99 (0.96,1.01) | .24 | |
| Race | 1.00 | ||
| Non-hispanic White | 0.98 (0.95,1.00) | .07 | |
| Non-Hispanic Black | 0.98 (0.95,1.02) | .43 | |
| Mexican-American | 0.96 (0.90,1.01) | .13 | |
| Other | 0.97 (0.94,1.01) | .19 | |
| Marital status | .32 | ||
| Married | 0.95 (0.92,1.00) | .10 | |
| Other | 0.99 (0.97,1.01) | .42 | |
| Education level | .22 | ||
| High school below | 0.96 (0.92,1.00) | .07 | |
| High school | 1.01 (0.98,1.05) | .45 | |
| High school above | 0.97 (0.94,1.01) | .12 | |
| PIR | .12 | ||
| <1.3 | 0.99 (0.96,1.01) | .31 | |
| 1.3-3.49 | 0.95 (0.92,0.98) | <.001 | |
| ≥3.5 | 1.01 (0.96, 1.06) | .79 | |
| Drinking status | .33 | ||
| Never | 0.96 (0.92, 0.99) | .24 | |
| Former | 0.96 (0.92, 0.99) | .01 | |
| Current | 0.97 (0.95,0.99) | .01 | |
| Hypertension | .75 | ||
| No | 0.97 (0.95,1.00) | .05 | |
| Yes | 0.98 (0.96,1.00) | .08 | |
| Diabetes | .18 | ||
| No | 0.97 (0.95,0.99) | <.001 | |
| Yes | 1.01 (0.97, 1.05) | .67 |
CI = confidence interval, OR = odds ratio, PIR = family income-to-poverty ratio. Adjusted for age, sex, race, marital status, education, PIR, drinking status, hypertension, and diabetes.
Figure 2 shows the restricted cubic spline of OR and 95% CI for the association between LE8 and the odds of epilepsy. We discovered a linear relationship between LE8 and the odds of epilepsy (P for nonlinearity = .658).
Figure 2.
Restricted cubic spline analysis showing the association between Life’s Essential 8 and the odds of epilepsy. CI = confidence interval, LE8 = Life’s Essential 8.
4. Discussion
Based on the NHANES database, this study systematically explored the relationship between LE8 and the odds of epilepsy for the first time. The results demonstrated that a higher LE8 score was significantly associated with lower odds of epilepsy, revealing a linear relationship between LE8 and the odds of epilepsy. Among the 8 components of LE8, dietary factors showed the strongest association with the odds of epilepsy. These findings provide new epidemiological evidence on the relationship between cardiovascular health and epilepsy and highlight the potential relevance of lifestyle-related factors in epilepsy research.
While the relationship between LE8 and conditions such as stroke, dementia, and late-life depression has been studied,[14,18,19] its connection to epilepsy remains underexplored. However, individual components of Life’s Essential 8 have frequently been examined in the context of epilepsy, offering indirect insights into this potential association. At the same time, there is a complex interaction between cardiovascular disease (CVD) and epilepsy, which may affect the risk of seizures through multiple mechanisms. Cardiovascular diseases such as arrhythmia, heart failure, and hypotension can lead to insufficient blood supply to the brain and cause ischemia and hypoxia in brain tissue. Ischemia and hypoxia can damage the metabolic function of brain cells, and cerebral ischemia can destroy neuron function and lower the seizure threshold, thereby inducing seizures.[20,21] Seizures may originate or spread to cardiovascular regulatory areas of the forebrain (such as the insular cortex) and may affect the synchronization of the sympathetic and vagus nerves of the heart, thereby affecting heart stability.[21,22] Because LE8 serves as a dynamic reflection of cardiovascular health trajectories in individuals or populations,[13] it is plausible that LE8 and its components are associated with epilepsy prevalence through shared biological and behavioral pathways, rather than direct causal mechanisms.
Our study analyzed the association between 8 components of LE8 and epilepsy and found several positive results. For example, healthy eating was associated with lower odds of epilepsy, whereas physical activity, nicotine exposure, and sleep health, although not significantly associated with the odds of epilepsy after adjustment, showed favorable effects in the unadjusted crude model. These findings are consistent with previous studies. A longitudinal study showed that transdermal nicotine was effective in controlling seizures in patients with epilepsy, and that overnight exposure to nicotine was better than nicotine intake alone during the day.[23] 1 review included 17 observational studies showing a significant association between current smoking and epilepsy, and smoking cessation may have a protective effect, but the quality of evidence is low and more large cohort studies are needed to confirm causality and dose-response relationships.[24] Exercise can reduce the frequency of seizures and improve cardiovascular health and mental state.[25] In addition, an epidemiological study used data from the 2017 National Health Interview Survey to analyze the participation of epilepsy patients in physical activities and compared it with the general population. In this study, people with epilepsy participated in physical activity at a lower rate than the general population, and people with epilepsy participated in moderate and intense physical activity at a lower rate than the general population.[26] Rachel E. Stirling et al studied 4956 seizure records in the experimental group and 30,485 recorded sleep nights in the control group. They used wearable devices to record sleep data and analyzed the relationship between changes in sleep time, bedtime, and awakening time and the odds of seizure. Lack of sleep was associated with a slight 2% increase in the odds of seizure within the following 48 hours (P < .01).[27] These health behaviors should be considered in future intervention studies, as they may serve as effective strategies for preventing epilepsy.
Our findings suggest that dietary quality, as captured by LE8, may be particularly relevant in understanding the association between cardiovascular health and epilepsy prevalence, although causal inferences cannot be drawn from this cross-sectional analysis. The current main eating patterns for adjusting cardiovascular structure are the Dietary Approaches to Stop Hypertension (diet that stops hypertension) and the Mediterranean diet[28] and less restrictive dietary patterns such as the improved Atkins diet are gradually applied to epilepsy treatment,[29,30] which significantly reduce the risk of CVD attacks through multiple mechanisms. These eating patterns are not only beneficial for people with epilepsy but also have a positive impact on overall health. The Mediterranean diet is primarily plant-based, emphasizing the consumption of olive oil, fish, fruits, vegetables, and whole grains. It is rich in antioxidants and antiinflammatory components. Cinzia Ferraris et al after reviewing articles and research in the field of “Ketogenic Diet in Nervous System Diseases and the Mediterranean Diet,” proposed the Mediterranean Ketogenic Diet. This diet provides abundant antioxidants and antiinflammatory ingredients, such as monounsaturated and polyunsaturated fatty acids, and has been shown to improve cognitive function and biomarkers associated with Alzheimer’s disease.[31] Dietary Approaches to Stop Hypertension diet can effectively prevent the occurrence of hypertension by increasing the intake of minerals such as potassium, magnesium, and calcium,[32] and can also reduce overall blood pressure levels, thereby reducing the incidence of CVD.[33] This diet is rich in antioxidants found in plant foods and is low in saturated fatty acids and cholesterol.[32] The Atkins diet is a high-fat, high-protein, low-carbohydrate diet that does not limit total calorie or protein intake. By limiting the intake of carbohydrates, it can induce ketosis, reduce appetite, and mobilize fat reserves. Compared with ketogenic diet, the Atkins diet is easier to implement and may have a similar effect on epilepsy control with fewer side effects.[34] Kverneland M et al conducted a randomized clinical trial examining the efficacy of the modified Atkins diet in adults with drug-resistant focal epilepsy, in which seizure frequency was significantly reduced in the diet group compared with the control group.[30] This study also provides a new perspective on the intersection of nutrition and the prevention and treatment of epilepsy, emphasizing the importance of dietary methods in adjusting epileptic states. Future research should delve deeper into the relationship between overall dietary patterns, cardiovascular health, and epilepsy prevalence to provide more rigorous evidence supporting our findings.
Our findings indicate that higher LE8 scores were associated with a consistent and monotonic decrease in the prevalence of epilepsy, with no evidence of nonlinearity or threshold effects. Although this association does not imply causality, it suggests the potential public health relevance of overall cardiovascular health, as reflected by LE8, in relation to epilepsy prevalence. In light of these results, it is important to note that, in our study, we did not observe any statistical interactions between LE8 and the covariates. However, considering the intricate interplay between social determinants of health and brain health, future research should incorporate these additional variables for a more comprehensive analysis. By doing so, we can better understand the complex relationships at play and identify high-risk populations. Such investigations are crucial, as they may inform targeted intervention strategies that focus on the key components of LE8, ultimately enhancing our efforts to prevent epilepsy and improve overall health outcomes.
The robustness of our study is supported by its reliance on NHANES data, which utilizes a hierarchical multistage probability sampling method to ensure high reliability and representativeness. Furthermore, by incorporating a comprehensive set of covariates, including age, gender, race, marital status, education level, annual household income, poverty status, and alcohol consumption, into our regression analyses, we were able to significantly reduce the influence of potential confounders.
In addition, sensitivity analyses applying sampling weights yielded results highly consistent with the primary analysis, suggesting that the non-application of sampling weights did not materially affect our parameter estimates or conclusions. However, our investigation is subject to certain limitations. First, the cross-sectional design inherently restricts the ability to establish causal relationships between LE8 and epilepsy, as it does not allow for the assessment of temporal relationships. Second, epilepsy status was defined based on self-reported medication use within the past 30 days rather than physician-confirmed diagnoses, which may have led to misclassification. This approach may not have captured all individuals with epilepsy and could have influenced the observed associations. Additionally, some Life’s Essentials 8 components rely on self-reported data, introducing potential bias. Additionally, the exclusion of individuals with incomplete dietary data may have altered the characteristics of the study population, potentially affecting the accuracy of our results. While we adjusted for a wide range of covariates, the possibility of unmeasured confounders influencing our findings cannot be entirely ruled out. It is also important to note that the demographic composition of our sample, primarily comprising individuals from the United States, may limit the generalizability of our findings to broader populations. Future research, including longitudinal studies and clinical validation of epilepsy cases, is needed to further explore these relationships and validate our findings.
In summary, this large cross-sectional analysis demonstrated that higher LE8 scores were associated with lower odds of epilepsy. Among the LE8 components, dietary quality showed the most consistent association with epilepsy prevalence. Rather than implying causality or prevention, these findings highlight an epidemiological association between overall cardiovascular health, particularly dietary factors, and epilepsy prevalence, and support the use of LE8 as a composite indicator for studying population-level health patterns related to epilepsy.
Acknowledgments
The author expresses gratitude to the NHANES study participants and staff for their invaluable contributions.
Author contributions
Data curation: Kang Pan, Hao Dai.
Formal analysis: Kang Pan, Hao Dai, Wanying Chen.
Methodology: Kang Pan, Hao Dai, Wanying Chen, Zhewei Dong.
Visualization: Wanying Chen.
Validation: Zhewei Dong.
Writing – review & editing: Siqi Ding.
Writing – original draft: Jinhui Song.
Abbreviations:
- AHA
- American Heart Association
- BMI
- body mass index
- CI
- confidence interval
- CVD
- cardiovascular disease
- KD
- ketogenic diet
- LE8
- Life’s Essential 8
- NHANES
- National Health and Nutrition Examination Survey
- OR
- odds ratio
- PIR
- poverty income ratio
- RCS
- restricted cubic splines
The authors have no funding and conflicts of interest to declare.
This study used publicly available, de-identified data from NHANES. NHANES protocols were approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board, and all participants provided written informed consent. As this secondary analysis used publicly available anonymized data, additional ethical approval was not required.
The datasets generated during and/or analyzed during the current study are publicly available.
Supplemental Digital Content is available in the online version of this article (http://dx.doi.org/10.1097/MD.0000000000050800).
How to cite this article: Song J, Pan K, Dai H, Chen W, Dong Z, Ding S. Association between life’s essential 8 and epilepsy: A cross-sectional study (NHANES 2013–2018). Medicine 2026;105:39(e50800).
JS and KP contributed to this article equally.
Contributor Information
Jinhui Song, Email: 240383387@qq.com.
Kang Pan, Email: 13906546610@163.com.
Hao Dai, Email: daihao8@wmu.edu.cn.
Wanying Chen, Email: 1277126506@qq.com.
Zhewei Dong, Email: dongzhewei2022@163.com.
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