A total sample of 22,573 was included, comprising 48.69% males and 51.31% females. The mean age was 48.01 years, and the mean BMI was 28.88 kg/m². In this study, the prevalence of high blood pressure among males was 33.75% (n = 3,710), and the prevalence of sleep disturbance was 22.06% (n = 2,425). Among females, the prevalence of high blood pressure was 35.09% (n = 4,064), and the prevalence of sleep disturbance was 29.17% (n = 3,378).
Subjects were divided into four groups: Without high blood pressure and sleep disturbance, high blood pressure without sleep disturbance, sleep disturbance without high blood pressure, and sleep disturbance with high blood pressure(Table 1). The percentage of all subjects experiencing sleep problems was 25.71% (n = 5,803). Among them, 38.86% slept less than 7 hours, making up 58.21% of respondents who slept within the recommended range of 7–9 hours, with the remaining 2.93% exceeding 9 hours of sleep. Respondents experiencing sleep disturbances took approximately eleven minutes longer to fall asleep compared to those without this disturbance, which was somewhat shorter than anticipated. Regarding the use of sleeping pills, the majority of subjects overall did not use such medications (88.52%). However, when considering the presence of both high blood pressure and sleep disturbance, subjects tended to use sleeping pills more frequently. Among respondents experiencing both sleep disturbance and high blood pressure, 14.25% required sleeping pills more than half of the time each month. This percentage decreased to 10.87% for those with sleep disturbance without high blood pressure.
Among subjects without high blood pressure and sleep disturbance, 32.96% were smokers. In contrast, among those experiencing both sleep disturbance and high blood pressure, this proportion increased to 55.35%. This trend is reversed among non-smokers.
The comorbid trend with alcohol consumption shows a similar pattern: among subjects without high blood pressure and sleep disturbance, 33.96% were drinkers. For those with high blood pressure without sleep disturbance, this proportion increased to 36.53%. Among subjects experiencing sleep disturbance without high blood pressure, 24.78% were drinkers, whereas for those with both sleep disturbance and high blood pressure, this figure rose to 25.69%.
Among different racial groups, the comorbidity rate of sleep disturbance and high blood pressure is lowest among Mexican Americans at 7.83% (n = 271). In contrast, non-Hispanic whites have a comorbidity rate of 14.8% (n = 1465), and Other Hispanics have a rate of 15.1% (n = 702).
In terms of educational attainment, 51.63% of subjects had diplomas higher than college. However, among subjects with high blood pressure, this percentage decreased to 46.49% (n = 3602). Conversely, among subjects with sleep disturbance, 52.87% had diplomas higher than college (n = 3068).
The proportion of partnered subjects (57.26%) consistently exceeded that of non-partnered subjects across all groups.
Significant correlations (all P values < 0.001) were observed between sleep disturbance and high blood pressure (Table 2), sleep disturbance and the inflammation index (Table 3), as well as between the inflammation index and high blood pressure (Table 4), as confirmed by subsequent logistic and linear regression analyses.
Furthermore, mediation analysis revealed that inflammatory indicators mediated the relationship between sleep disturbance and the development of high blood pressure by 0.23% (Table 5). Gender-specific subgroup analyses were conducted throughout the study. Model 1 represented an unadjusted model, while Model 2 controlled for age, ethnicity, smoking status, alcohol status, BMI, marital status, and education level.
Table 1
Characteristics of study participants
Characteristics | Total participants | Without high blood pressure and sleep disturbance | high blood pressure without sleep disturbance | sleep disturbance without high blood pressure | sleep disturbance with high blood pressure | p |
| 22573 | 11845 | 4925 | 2954 | 2849 | |
Age (year), Mean(± SD) | 48.01 ± 18.51 | 40.87 ± 17.02 | 60.15 ± 15.68 | 45.89 ± 16.75 | 58.88 ± 14.32 | < 0.001 |
Sex, n (%) | | | | | | < 0.001 |
Male | 10991 (48.69) | 6062 (51.18) | 2504 (50.84) | 1219 (41.27) | 1206 (42.33) | |
Female | 11582 (51.31) | 5783 (48.82) | 2421 (49.16) | 1735 (58.73) | 1643 (57.67) | |
BMI Mean(± SD) | 28.88 ± 6.93 | 27.53 ± 6.21 | 30.32 ± 6.77 | 28.51 ± 7.03 | 32.42 ± 8.10 | < 0.001 |
Marital status, n (%) | | | | | | < 0.001 |
Married/living with a partner | 9648 (42.74) | 5049 (42.63) | 1979 (40.18) | 1293 (43.77) | 1327 (46.58) | |
Divorced/separated/widowed/Never married | 12925 (57.26) | 6796 (57.37) | 2946 (59.82) | 1661 (56.23) | 1522 (53.42) | |
Education level, n (%) | | | | | | < 0.001 |
<High school | 5808 (25.73) | 2945 (24.86) | 1499 (30.44) | 581 (19.67) | 783 (27.48) | |
High school | 5110 (22.64) | 2572 (21.71) | 1167 (23.70) | 648 (21.94) | 723 (25.38) | |
College | 11655 (51.63) | 6328 (53.42) | 2259 (45.87) | 1725 (58.40) | 1343 (47.14) | |
Smoking status, n (%) | | | | | | < 0.001 |
Yes | 9973 (44.18) | 4554 (38.45) | 2318 (47.07) | 1524 (51.59) | 1577 (55.35) | |
No | 12600 (55.82) | 7291 (61.55) | 2607 (52.93) | 1430 (48.41) | 1272 (44.65) | |
Alcohol status, n (%) | | | | | | < 0.001 |
Yes | 7286 (32.28) | 4023 (33.96) | 1799 (36.53) | 732 (24.78) | 732 (25.69) | |
No | 15287 (67.72) | 7822 (66.04) | 3126 (63.47) | 2222 (75.22) | 2117 (74.31) | |
Race, n (%) | | | | | | < 0.001 |
Mexican American | 3459 (15.32) | 2231 (18.83) | 626 (12.71) | 331 (11.21) | 271 (9.51) | |
Non-Hispanic Black | 2307 (10.22) | 1345 (11.36) | 455 (9.24) | 258 (8.73) | 249 (8.74) | |
Non-Hispanic White | 9895 (43.84) | 4625 (39.05) | 2135 (3.35) | 1670 (56.53) | 1465 (51.42) | |
Other Hispanic | 4646 (20.58) | 2190 (18.49) | 1308 (26.56) | 446 (15.10) | 702 (24.64) | |
Other race | 2266 (10.04) | 1454 (12.28) | 401 (8.14) | 249 (8.43) | 162 (5.69) | |
time to fall asleep(min),Mean(± SD) | 23.23 ± 20.32 | 20.29 ± 18.29 | 20.40 ± 18.82 | 31.42 ± 22.82 | 31.81 ± 23.18 | < 0.001 |
length of sleep,n, (%) | | | | | | < 0.001 |
< 7h | 8772 (38.86) | 3990 (33.69) | 1690 (34.31) | 1494 (50.58) | 1598 (56.09) | |
7-9h | 13139 (58.21) | 7541 (63.66) | 3040 (61.73) | 1397 (47.29) | 1161 (40.75) | |
> 9h | 662 (2.93) | 314 (2.65) | 195 (3.96) | 63 (2.13) | 90 (3.16) | |
dosing *frequency of sleeping pills,n (%) | | | | | | < 0.001 |
Never | 19982 (88.52) | 11192 (94.49) | 4601 (93.42) | 2174 (73.60) | 2015 (70.73) | |
Rarely | 563 (2.49) | 233 (1.97) | 103 (2.09) | 125 (4.23) | 102 (3.58) | |
Sometimes | 728 (3.23) | 244 (2.06) | 101 (2.05) | 199 (6.74) | 184 (6.46) | |
Often | 400 (1.77) | 79 (0.67) | 44 (0.89) | 135 (4.57) | 142 (4.98) | |
Almost always | 900 (3.99) | 97 (0.82) | 76 (1.54) | 321 (10.87) | 406 (14.25) | |
*SII,median (IQR) | 461.842 (329.667–653.600) | 445.474 (321.667-629.739) | 478.154 (331.259-677.444) | 473.79 (341.824-668.023) | 491.429 (344.211-699) | < 0.001 |
*dosing frequency of sleeping pills |
Rarely (1 time a month) |
Sometimes (2–4 times a month) |
Often (5–15 times a month) |
Almost always (16–30 times a month) |
*SII: Systemic Immune-Inflammation Index(Platelets*neutrophils/ Lymphocytes) |
Table 2
Associations of sleep disturbance and high blood pressure
| | Number of participants | OR(95% CI) | P |
Model 1 | Total | 22573 | 2.32(2.18,2.47) | < 0.001 |
| Male | 10991 | 2.40(2.19,2.63) | < 0.001 |
| Female | 11582 | 2.26(2.08,2.46) | < 0.001 |
Model 2 | Total | 22573 | 1.81(1.69,1.95) | < 0.001 |
| Male | 10991 | 1.83(1.65,2.04) | < 0.001 |
| Female | 11582 | 1.78(1.61,1.97) | < 0.001 |
Model 1:Unadjusted |
Model 2:Adjusted for age, ethnicity, smoking status, alcohol status, BMI, marital status, and education level |
The results(Table 2) showed a positive correlation between sleep disorders and hypertension, both in the overall population and by gender, and this correlation remained significant after model two calibration. This result is clearly in line with common sense[11][12].
Table 3
Associations of Sleep disturbance and SII
| | Number of participants | β(95% CI) | P |
| sleep disturbance and SII | | | |
Model 1 | Total | 22573 | 38.52(27.03,50.01) | < 0.001 |
| Male | 10991 | 54.61(35.43,73.79) | < 0.001 |
| Female | 11582 | 20.45(6.78,34.12) | 0.003 |
Model 2 | Total | 22573 | 16.34(4.62,28.06) | 0.006 |
| Male | 10991 | 28.62(9.04,48.21) | 0.004 |
| Female | 11582 | 5.74(-8.23,19.71) | 0.42 |
Model 1:Unadjusted |
Model 2:Adjusted for age, ethnicity, smoking status, alcohol status, BMI, marital status, and education level |
There was a significant association between sleep disturbance and SII, but different results emerged in the corrected model for females, and a covariate-by-covariate validation found that race and BMI had the greatest effect on the significance of the results, with a p-value back to 0.037 after validation exclusion, the mechanisms of which need to be further validated in follow-upSimilar results were found in Jiahui Yin's study[13], and the age cycle of the women, the changes in hormone levels, and the pattern of blood pressure response will be discussed later.
Table 4
Associations of SII and high blood pressure
| | Number of participants | OR(95% CI) | P |
| SII and high blood pressure | | | |
Model 1 | Total | 22573 | 1.0004(1.0003,1.0004) | < 0.001 |
| Male | 10991 | 1.0005(1.0004,1.0006) | < 0.001 |
| Female | 11582 | 1.0002(1.0001,1.0003) | < 0.001 |
Model 2 | Total | 22573 | 1.0002(1.0001,1.0003) | < 0.001 |
| Male | 10991 | 1.0003(1.0001,1.0004) | < 0.001 |
| Female | 11582 | 1.0002(1.0001,1.0004) | < 0.001 |
Model 1:Unadjusted |
Model 2:Adjusted for age, ethnicity, smoking status, alcohol status, BMI, marital status, and education level |
SII showed a significant association with high blood pressure, with an odds ratio (OR) of 1.0004 in the total population, and 1.0005 and 1.0002 in males and females, respectively. It's notable that the interquartile range of SII was 461.842 (329.667–653.6), indicating substantial variability in the computed values despite the modest OR range of 1.0002–1.0005.
To further elucidate the relationship between SII and high blood pressure, curve fitting analysis was conducted for both models (Fig. 2).
In Model 1, the odds ratio (OR) for SII was < 1 between 191.45 and 461.84 in the total population, indicating that within this range, SII serves as a protective factor against high blood pressure. Below the lower or above the upper limit of this range, the risk of high blood pressure increases. In men, this protective range was observed between 185.51 and 440.87, showing a similar trend. In contrast, in women, the range extended from 200.00 to 482.35, indicating a broader protective range compared to men.
Upon adding covariates, the fitted curve showed a unidirectional trend. In men, the risk of high blood pressure began to increase at SII > 440.87, while in women, this inflection point was observed at SII > 482.35.
Table 5
| ACME | | | |
| Estimate | CI_Lower95 | CI_Upper95 | P |
Unadjusted | | | | |
Total | 0.0023 | 0.0013 | 0.0037 | < 0.001 |
Male | 0.0039 | 0.0020 | 0.0073 | < 0.001 |
Female | 0.0009 | 0.0001 | 0.0018 | 0.018 |
Adjusted | | | | |
Total | 0.0005 | 0.0001 | 0.0010 | 0.006 |
Male | 0.0010 | 0.0003 | 0.0022 | 0.002 |
Female | 0.0002 | -0.0004 | 0.0008 | 0.434 |
| ADE | | | |
Unadjusted | | | | |
Total | 0.1950 | 0.1804 | 0.2102 | < 0.001 |
Male | 0.2011 | 0.1785 | 0.2230 | < 0.001 |
Female | 0.1904 | 0.1714 | 0.2115 | < 0.001 |
Adjusted | | | | |
Total | 0.1047 | 0.0914 | 0.1188 | < 0.001 |
Male | 0.1129 | 0.0920 | 0.1339 | < 0.001 |
Female | 0.0957 | 0.0774 | 0.1137 | < 0.001 |
| TotalEffect | | | |
Unadjusted | | | | |
Total | 0.1973 | 0.1825 | 0.2124 | < 0.001 |
Male | 0.2050 | 0.1826 | 0.2271 | < 0.001 |
Female | 0.1913 | 0.1721 | 0.2123 | < 0.001 |
Adjusted | | | | |
Total | 0.1052 | 0.0917 | 0.1192 | < 0.001 |
Male | 0.1139 | 0.0928 | 0.1355 | < 0.001 |
Female | 0.0959 | 0.0777 | 0.1137 | < 0.001 |
| PropMediated | | | |
Unadjusted | | | | |
Total | 0.0116 | 0.0067 | 0.0187 | < 0.001 |
Male | 0.0189 | 0.0098 | 0.0361 | < 0.001 |
Female | 0.0045 | 0.0006 | 0.0097 | 0.018 |
Adjusted | | | | |
Total | 0.0046 | 0.0012 | 0.0092 | 0.006 |
Male | 0.0086 | 0.0026 | 0.0194 | 0.002 |
Female | 0.0019 | -0.0037 | 0.0081 | 0.434 |
ACME: average causal mediation effect, ADE: average direct effect.
A generalized additive model was used to the smooth mediator effect on outcome.
Adjusted analyses adjusted for age, ethnicity, smoking status, alcohol status, BMI, marital status, and education level