Gender differences in the relationship between the systemic immune-inflammation index and all-cause and cardiovascular mortality among adults with hypertension: evidence from NHANES 1999-2018

Background There are gender differences in hypertension and the effect of gender on the relationship between systemic immune-inflammation index (SII) and mortality in hypertensive patients is unclear. Methods Hypertensive patients (n=7444) from ten cycles of the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018 were enrolled in this study. The maximally selected rank statistics method was employed to identify the optimal cut-off value for the SII. Survey-weighted Cox regression analysis was utilized to explore the links between SII and all-cause and cardiovascular mortality. Kaplan-Meier method and time-dependent receiver operating characteristic curve analysis was conducted to assess the predictive accuracy of SII for mortality. Results Whether SII was considered as a numerical variable or as a binary variable (higher- and lower-SII groups), higher SII levels were associated with a higher risk of all-cause and cardiovascular mortality in female hypertensive patients (all P < 0.001), but no such association was observed in the males. The area under the curve of the SII was 0.602, 0.595, and 0.569 for 3-, 5-, and 10-year all-cause mortality, respectively, in females, but was 0.572, 0.548, and 0.554 in males. High SII levels interacted with the poverty income ratio and physical activity to affect mortality in the male population (P for interaction < 0.05), and there was an interaction between race and SII in the female cardiovascular mortality rate (P for interaction < 0.05). Conclusion Higher levels of SII may be closely related to the high risk of all-cause and cardiovascular mortality in hypertensive patients, and the results showed that this relationship is more significant and stable in the female group. High SII interacts with PIR, physical activity, and race to affect the mortality rate in different gender populations.