Physical activity levels may impact on the risk of premature mortality in people with epilepsy

Abstract

Epilepsy affects over 70 million individuals worldwide, with optimal physical activity (PA) levels remaining challenging to determine due to potential negative outcomes from both insufficient and excessive activity. To quantify the associations between objective PA and mortality in people with epilepsy, we analyzed accelerometer data from 98,561 UK Biobank participants, including 1167 with epilepsy, to quantify associations between objectively measured PA and mortality. During a median follow-up of 7.1 years, people with epilepsy had significantly higher mortality rate (Standardized mortality ratio: 2.39, 1.97-2.86). Higher sedentary behavior duration was associated with lower all-cause mortality (hazard ratio: 0.87, 0.78-0.97). Dose-response analyses identified sedentary durations of 7-13 h/day (p nonlinear=0.025) and moderate-to-vigorous PA of 0.1-0.2 h/day (p nonlinear=0.005) were associated with lower mortality. An explainable machine-learning model that combined multi-dimensional PA with demographic and health information effectively stratified individual risk (Area Under the Receiver Operating Characteristic curve: 0.87 ± 0.08) and could support personalized activity guidance through a wearable system.

Fig. 1. Study framework for physical activity patterns and mortality risk analysis in people with epilepsy.

a Study population including 1167 people with epilepsy and 97,394 controls with 7-day accelerometer data. b Mortality ascertainment for all-cause and cause-specific deaths including cardiovascular, cancer, and epilepsy-related mortality. c Comprehensive demographic and clinical characteristics collection including age, education, smoking status, alcohol use, BMI, overall health, disability status, and Charlson Comorbidity Index. d Physical activity exposure measurements including daily sedentary duration, light PA duration, and MVPA duration (min/day). e Primary analysis incorporating temporal distribution analysis and standardized mortality ratio analysis across groups. f In-depth statistical analysis including correlation analysis of PA patterns with mortality outcomes, proportional hazards regression for all-cause and cause-specific mortality, dose-response analysis, and optimal PA threshold determination across demographic subgroups. g Machine learning framework for mortality prediction using GridSearchCV for kernel SVM with feature extraction, model development and interpretable analysis incorporating PA pattern features (sedentary, light PA, and MVPA duration) and signal features (statistical, time domain, and frequency domain features). h EpiActivity Manager design for PA management and health monitoring in people with epilepsy using smartwatch technology.

Fig. 2. Physical activity (PA) patterns and standardized mortality ratios across activity tertiles in people with and without epilepsy.

a Hour-level PA patterns showing mean acceleration (milligravity) over 24 h for survivors (blue, n = 1051) and deceased participants (orange, n = 116). The center line denotes the mean and shaded bands indicate 95% confidence intervals (CIs). Hourly values were computed as participant-level means. b Standardized mortality ratios (SMRs) comparing people with epilepsy (orange) to people without epilepsy (blue; reference) across sedentary tertiles. Bars show SMR point estimates with 95% CIs (Byar’s approximation). Across tertiles 1–3, the sample sizes were n = 352/387/428 for people with epilepsy and n = 33,464/33,277/30,653 for people without epilepsy. Statistical significance was assessed using two-sided exact Poisson tests. c SMRs across light PA tertiles, with people without epilepsy as the reference. The sample sizes by tertile were n = 491/358/318 (people with epilepsy) and n = 32,879/32,178/32,337 (people without epilepsy). Statistical comparisons were performed using two-sided exact Poisson tests. d SMRs across moderate-to-vigorous PA tertiles, again using people without epilepsy as the reference. The corresponding sample sizes were n = 590/305/272 and n = 41,504/26,991/28,899, with statistical significance evaluated by two-sided exact Poisson tests. e Internal SMRs (ISMRs) by sedentary tertiles within each group, using the lowest tertile as the internal reference. The sample sizes were n = 352/387/428 (people with epilepsy) and n = 33,464/33,277/30,653 (people without epilepsy). Comparisons between tertiles were analyzed using two-sided exact Poisson tests. f Internal SMRs by light PA tertiles (reference=lowest tertile). Sample sizes were n = 491/358/318 and n = 32,879/32,178/32,337. Statistical significance was determined using two-sided exact Poisson tests. g Internal SMRs by moderate-to-vigorous PA tertiles (reference=lowest tertile). Sample sizes were n = 590/305/272 and n = 41,504/26,991/28,899. Two-sided exact Poisson tests were used for statistical comparisons. Red dashed lines indicate the reference. No adjustments for multiple comparisons were applied. n denotes independent participants.

Fig. 3. Associations between physical activity and covariates in people with epilepsy.

a Spearman correlation heatmap showing associations between sedentary duration, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) and covariates. Colors encode Spearman correlation coefficients. b–d Scatter plots showing relationships between BMI and (b) sedentary duration, c LPA, and (d) MVPA. Each point is one independent participant. The solid line is the regression fit; the shaded band denotes the 95% confidence interval. Statistics are Spearman’s rank correlation, two-sided; r and P are shown in-panel. Center and error: regression line and 95% CI. e–g Scatter plots showing relationships between Charlson comorbidity score and (e) sedentary duration, f LPA, and (g) MVPA. Each point is one independent participant. The solid line denotes the regression fit with 95% confidence band. Statistics are Spearman’s rank correlation, two-sided; r and P are shown in-panel. Center and error: regression line and 95% CI. h–j Box plots comparing (h) sedentary duration, i LPA, and (j) MVPA between males and females. Sample sizes per box: Male (n = 559), Female (n = 608). k–m Box plots comparing (k) sedentary duration, l LPA, and (m) MVPA between participants with and without long-term disability. Sample sizes per box: Yes (n = 734), No (n = 433). n–p Box plots comparing (n) sedentary duration, o LPA, and (p) MVPA across education levels. Sample sizes per box: Below college degree (n = 681), Above college degree (n = 486). q–s Box plots comparing (q) sedentary duration, r LPA, and (s) MVPA across self-rated overall health categories. Sample sizes per box: Excellent (n = 161), Good (n = 608), Fair (n = 306), Poor (n = 92). Box-plot definitions (applies to h–s): center line = median; box bounds = 25th and 75th percentiles (IQR); whiskers extend to 1.5 × IQR; points beyond whiskers are outliers. For two-group comparisons (gender, long-term disability, education level), group differences were evaluated using two-sided independent-samples t tests (Welch’s correction). n denotes the number of independent participants; For scatter plots, center and error refer to the fitted line and its 95% CI. All statistical tests were two-sided, and P values < 0.001 are reported in scientific notation in panels.

Fig. 4. Dose-response relationships between physical activity patterns and cause-specific mortality risk in people with epilepsy.

a All-cause mortality hazard ratios by sedentary duration. b All-cause mortality hazard ratios by light physical activity duration. c All-cause mortality hazard ratios by moderate-to-vigorous physical activity duration. d Cardiovascular death hazard ratios by sedentary duration. e Cardiovascular death hazard ratios by light physical activity duration. f Cardiovascular death hazard ratios by moderate-to-vigorous physical activity duration. g Cerebrovascular death hazard ratios by sedentary duration. h Cerebrovascular death hazard ratios by light physical activity duration. i Cerebrovascular death hazard ratios by moderate-to-vigorous physical activity duration. j Epilepsy death hazard ratios by sedentary duration. k Epilepsy death hazard ratios by light physical activity duration. l Epilepsy death hazard ratios by moderate-to-vigorous physical activity duration. m Cancer death hazard ratios by sedentary duration. n Cancer death hazard ratios by light physical activity duration. o Cancer death hazard ratios by moderate-to-vigorous physical activity duration. The red solid curve is the point estimate of the hazard ratio (center) from the restricted cubic spline (RCS) Cox model; the pink shaded band denotes the model-based 95% confidence interval (error band) around the estimated HR. Overall and non-linear association P values are from Wald tests of the spline terms (anova on the RCS model), two-sided. The number of knots was selected by minimum AIC. The reference exposure is the prob-quantile (prob=0.10), at which HR = 1.

Fig. 5. Model performance and feature importance for mortality prediction in people with epilepsy.

Integrating demographic, health-related, and advanced accelerometer-derived physical activity features with machine learning substantially improves individualized mortality risk prediction in people with epilepsy. a Receiver operating characteristic (ROC) curves for the baseline model (demographics and health-related features; AUROC = 77.6%) and the comprehensive model (demographics, health-related, and RFE-selected time- and frequency-domain PA features; AUROC = 86.7%), both using optimally tuned random forest classifiers. The comprehensive model shows markedly improved discrimination. b Precision–recall curves for the same two models as in (a), with the area under the precision–recall curve (AUPRC) increasing from 74.7% (baseline) to 82.2% (comprehensive model). All results are based on models with optimal hyperparameters. c Confusion matrix for the baseline model, showing predicted versus true labels (Survived, Deceased). The baseline model demonstrates moderate classification performance. d Confusion matrix for the comprehensive model, indicating improved sensitivity and specificity for mortality prediction upon inclusion of physical activity features. e Kaplan–Meier survival curves stratified by quartiles of predicted mortality risk from the comprehensive model. Survival probabilities decrease significantly across risk quartiles (log-rank p = 1.70e-05), indicating effective risk stratification. f Scatter plot of predicted mortality risk versus time to death or last follow-up, colored by true outcome (alive or deceased). A significant negative correlation (Two side spearman r = –0.40, p = 0.0051) demonstrates that higher predicted risk is associated with shorter survival time. g SHAP (SHapley Additive exPlanations) summary plot showing the top feature contributions in the comprehensive model. Blue bars represent PA features (time and frequency domain), and orange bars represent demographic and health-related features. The most important features include age at onset of epilepsy, mean change in moderate activity, and several high-frequency PA intensity measures.