Participant characteristics

A total of 2211 participants (1094 males and 1117 females) were recruited for the current investigation. The fundamental attributes of the individuals experiencing acute headache compared to those who were not, are presented in Table 1. Roughly 26.6% (588) of the individuals within our research cohort reported severe headache. More specifically, among those with severe headache, a higher percentage of females and Non-Hispanic Black, individuals exhibited a reduced family poverty income ratio (PIR), an elevated body mass index (BMI), decreased levels of alkaline phosphatase, hemoglobin, and glucose. Furthermore, individuals experiencing frequent or severe headaches demonstrated a higher IBI Q4, increased total cholesterol and LDL levels, and decreased albumin concentrations. The baseline characteristics of all participants and those with or without headache categorized by the IBI are depicted in Additional file 1: Tables S1.

Table 1 Baseline characteristics of participants with or without severe headacheUnivariate analysis: demographic and inflammatory predictors of severe headache

In this study, we analyzed the association between various demographic, clinical, and inflammatory factors with headache risk in youth, stratified by gender. The hazard ratio for age indicated no significant difference in headache risk between participants under and over 18 years of age (OR: 1.00, 95% CI: 0.80–1.25, P = 0.9896). However, gender-specific analysis revealed that females had a significantly higher risk of headaches compared to males (OR: 1.45, 95% CI: 1.20–1.75, P = 0.0001, see Table 2).

Race also emerged as a significant factor, with Other Hispanic and Non-Hispanic Black youth showing an increased headache risk compared to Mexican Americans (OR: 1.72, 95% CI: 1.11–2.68, P = 0.0161 and HR: 1.35, 95% CI: 1.07–1.71, P = 0.013, respectively, see Table S2). Body mass index (BMI) was positively correlated with headache risk (OR: 1.03, 95% CI: 1.01–1.05, P = 0.0002), while the poverty income ratio (PIR) was inversely associated with the risk (OR: 0.91, 95% CI: 0.86–0.97, P = 0.0059). Inflammatory markers such as C-reactive protein (CRP), neutrophils, lymphocytes, and white blood cells (WBC) showed no significant association with headache risk.

Finally, the Inflammatory Burden Index (IBI) demonstrated a dose-response relationship, with youth in the highest quartile (Q4) having a significantly higher risk of headaches compared to those in the lowest quartile (Q1) (OR: 1.46, 95% CI: 1.12–1.91, P = 0.0051). Other biochemical parameters such as lactate dehydrogenase (LDH), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) did not show significant associations with headache risk.

Table 2 Univariate analysis of severe headacheMultivariable regression analysis of inflammatory burden and headache risk

In multivariate regression analyses, when IBI was divided into quartiles, the risk of headache in the highest quartile group (Q4) was significantly higher than in the lowest quartile group (Q1) in all models. The model 1 showed a 46% increased risk of headache in the Q4 group (OR: 1.46, 95% CI: 1.12–1.91, P = 0.0051). In the model2, the Q4 group had a 43% increased risk of headache (OR: 1.43, 95% CI: 1.09–1.88, P = 0.0106), and in the model3, the risk increased to 38% (OR: 1.38, 95% CI: 1.16–2.07, P = 0.0196).

In analyses with quartiles as continuous variables, for each quartile increase in IBI, the risk of model2 (OR: 1.10, 95% CI: 1.01–1.20, P = 0.0325), and significantly more in the model3 (OR: 1.03, 95% CI: 1.01–1.14, P = 0.0582). These results suggest that a higher inflammatory burden index is associated with an increased risk of headache in youth, particularly significant in the interquartile analyses (see Table 3).

Table 3 ORs (95% CIs) for frequent/significant headache according to the IBIStratified analysis

In the stratified analysis, we evaluated the association between various demographic, clinical, and inflammatory variables with headache risk in female patients, while categorizing the data into relevant subgroups.

Age stratification revealed that youth under 18 years of age had a moderately increased risk of headaches (OR: 1.36, 95% CI: 1.00–1.85, P = 0.0486), while those aged 18 and above had an even higher risk (OR: 1.97, 95% CI: 1.02–3.81, P = 0.0433). Gender analysis showed a significant association between female gender and headache risk (OR: 1.48, 95% CI: 1.03–2.11, P = 0.0324), whereas the association was not significant in males (OR: 1.33, 95% CI: 0.88–2.00, P = 0.1734). (See Table S2).

We further did stratified analysis on female group falling within IBI Q4, since IBI.Q4 was found to be the most significant across all the models mentioned above (see Table 4 and Table S3). We found several parameters are of great significance, for Age: Significant association with pain in females under 18 (OR 1.55, 95% CI: 1.02–2.37, P = 0.0414), but not in those 18 and older (OR 1.15, 95% CI: 0.31–4.34, P = 0.8349).For Glucose Levels: Higher pain risk in the 86–329 mg/dl group (OR 2.32, 95% CI: 1.25–4.33, P = 0.0079).For HDL Levels: Increased pain risk in the highest HDL group (1.45–2.97 mmol/L) (OR 1.99, 95% CI: 1.05–3.79, P = 0.0359). For WBC Count: Significant association with pain in the 6.2–7.9 × 10^9/L group (OR 3.45, 95% CI: 1.74–6.82, P = 0.0004).

PIR: Higher income-to-poverty ratio associated with increased pain risk (OR 2.11, 95% CI: 1.13–3.95, P = 0.0198).For Race: Significant association with pain in Non-Hispanic White females (OR 2.01, 95% CI: 1.04–3.86, P = 0.0374).

Table 4 Stratified analysis for female falling within IBI.Q4Threshold effect analysis in females

In the analysis of the threshold effect of the Inflammatory Burden Index (IBI) on headache risk in females, we examined the data across different age groups and identified a potential threshold (K) at which the association between IBI and headache risk might change.

In Model I, no significant interaction was observed between age and IBI (P-interaction: 0.880), and the overall effect of IBI across all ages was not significant (OR: 1.00, 95% CI: 0.99–1.01, P = 0.8032).

Model II introduced a threshold effect analysis with a breakpoint (K) identified at an IBI value of 3.78. For females under 18 years of age, IBI values below the threshold were associated with a significantly increased risk of headaches (OR: 1.12, 95% CI: 1.01–1.25, P = 0.0385). However, this association was not significant for IBI values above the threshold (OR: 1.00, 95% CI: 0.98–1.01, P = 0.4875). The difference in effects between the two segments was statistically significant (OR: 0.89, 95% CI: 0.79–0.99, P = 0.0386).

For females aged 18 years and older, the threshold effect was less clear, with no significant associations observed in either segment of the threshold (OR: 1.99, 95% CI: 0.39–10.23, P = 0.4096 for IBI < K and OR: 1.00, 95% CI: 0.98–1.01, P = 0.6730 for IBI > K, see Table 5).

The overall difference in effects across all ages was significant, suggesting that the risk of headaches associated with IBI may be more pronounced at lower IBI values, particularly in younger females. The log-likelihood ratio test further confirmed the significance of this threshold effect (P = 0.042).

The analysis supports the idea that there may be a specific IBI range in which the risk of headaches is heightened, especially in younger females, indicating the importance of early detection and intervention in this group.

Table 5 Threshold effect analysis in femalesSensitivity analyses results

After excluding extreme IBI values, consistent results is observed with our primary analyses, suggesting that our findings are robust to potential outliers. The association between IBI and headache risk remained significant in females (adjusted OR: 1.48, 95% CI: 1.03–2.11, p = 0.0324), while no significant association was observed in males.