Abstract
Limited evidence has shown the relationship between systemic inflammation and high myopia. Thus, we conducted this study to explore this issue. A total of 2891 participants (2891 eyes) aged ≤40 years were included in this cross-sectional study. Four systemic inflammation markers were calculated through blood cell counts: systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio. Univariate and multivariate logistic regression analyses, as well as restricted cubic spline analyses, were used to assess the relationship between systemic inflammation markers and high myopia. The incidence of mild and moderate myopia was 67.24% (1944 eyes), and the incidence of high myopia was 4.6% (133 eyes) in this US population. After adjusting for covariates, multivariate logistic regression analysis revealed that high myopia was associated with white blood cell counts (odds ratio [OR] = 0.242, P = .027), neutrophils (OR = 4.052, P = .033), lymphocytes (OR = 4.989, P = .021), neutrophil-to-lymphocyte ratio (OR = 0.621, P = .025), and SII (OR = 1.002, P = .011). We also found that lymphocytes and the SII were nonlinearly associated with high myopia (all P < .05). Higher levels of lymphocytes and SII related to high myopia. Thus, the measurement of inflammatory markers should be taken into consideration when assessing high myopia.
Keywords: high myopia, inflammation, lymphocytes, risk factors, SII
1. Introduction
Myopia is a common cause of vision loss. A total of 938 million people will have high myopia by 2050.[1] An increased risk of cataracts, glaucoma, retinal detachment, and myopic macular degeneration brings many clinical challenges for high myopia patients.[2] Recently, several studies have revealed that intraocular inflammation plays a role in myopia. IL-6 and matrix metalloproteinase-2 were significantly higher in the aqueous humor of myopia patients and were positively associated with axial length.[3] Elevation of inflammatory cytokines decreases collagen 1A1 content and weakens the sclera, resulting in the progression of myopia.[4]
Not only did intraocular inflammation contribute to myopia, but systemic inflammation was also associated with myopia. A population-based cohort study in Taiwan found a higher prevalence of myopia in patients with autoimmune diseases, such as type 1 diabetes mellitus, systemic lupus erythematosus, and uveitis.[5] A previous study revealed that 43% of patients with juvenile idiopathic arthritis encountered elevated myopia.[6] According to a study conducted using Taiwan’s National Health Insurance Research Database, Kawasaki disease, which is associated with immune dysregulation, also poses a risk factor for myopia.[7] However, few studies have evaluated the relationship between high myopia and systemic inflammation markers.
Several systemic inflammation markers, such as the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR), were found to be related to eye diseases. NLR and PLR were identified to be associated with diabetic retinopathy, age-related macular degeneration, and primary angle closure glaucoma.[8–11] The SII, NLR, and PLR were significantly higher in patients with dry eye disease, and the SII may be an inexpensive and reliable indicator of inflammatory status in dry eye disease patients.[12] An increase in LMR was a biomarker indicating impaired blood-aqueous barrier function in Fuchs uveitis syndrome.[13] Based on the above studies, we hypothesize that there may exist a potential correlation between these systemic inflammation markers and high myopia. Thus, we conducted this cross-sectional study to verify our conjecture.
2. Methods
2.1. Study population
We used data from NHANES, which is a multistage study that can represent the US population. The NHANES Institutional Review Board/NCHS Research Ethics Review Board approved the conduct of the NHANES serial cross-sectional survey, and all the participants signed informed consent. Distance visual acuity and objective refraction were performed from 2001 to 2008. A total of 41,658 participants were enrolled in NHANES. After excluding participants without ophthalmic examination, having cataract surgery history, without visual acuity, without eyeglass prescription, age >40 years, with hypermetropia, without poverty data, without white blood cells (WBC), without C-reactive protein (CRP), and taking anti-inflammatories, 2891 participants were included in the final analysis. Figure 1 shows detailed information on the enrollment procedure of the participants.
Figure 1.
Flowchart of the inclusion of participants.
2.2. Ophthalmic parameters
All eligible participants finished the noncycloplegic vision examination, including objective refraction and visual acuity incorporating objective refraction. Autorefractor/keratometry (Nidek ARK-760 A, Nidek Co. Ltd., Tokyo, Japan) was conducted to measure objective refraction and corneal curvature data.[14] The mean of 3 repeated measurements was included in the study. Myopia was defined as spherical equivalent (SE) < ‐0.5 diopters (D). Participants with SE < ‐6.0 D were diagnosed with high myopia. Thus, according to SE, participants were divided into 3 groups: the emmetropia group, the mild and moderate myopia group, and the high myopia group.
2.3. Systemic inflammation markers
Automated hematology analyzing devices (Coulter DxH 800 analyzer) were used to obtain the distribution of blood cells of all the participants. Blood cell counts are presented as ×103 cells/µL. Four systemic inflammation markers associated with chronic inflammation were calculated using lymphocytes, monocytes, neutrophils, and platelets. The formulas were as follows: SII = (neutrophils × platelets)/lymphocytes, NLR = neutrophils/lymphocytes, PLR = platelets/lymphocytes, and LMR = lymphocytes/monocytes. In addition, we extracted data on other systemic inflammation indexes that were mentioned by previous studies, including WBCs and CRP.
2.4. Other covariate information
To explore the association between systemic inflammation and myopia, we also collected some covariate information. Including demographic factors: age, gender, ethnicity, education, and the ratio of family income to poverty (PIR); general medical history and body measure index: diabetes, hypertension, asthma, and body mass index (BMI).
Diabetes was diagnosed by one of the following criteria: self-reported diabetes history, glycosylated hemoglobin HbA1c (%) > 6.5, fasting glucose (mmol/L) ≥ 7.0, random blood glucose (mmol/L) ≥ 11.1, 2-hour OGTT blood glucose (mmol/L) ≥ 11.1, and use of diabetes medication or insulin.[15] When patients with a history of hypertension or have non-same-day randomized records of 3 systolic blood pressure ≥130 mm Hg or diastolic blood pressure ≥80 mm Hg or use any antihypertensive drug, they will be recognized as having hypertension.[16] Asthma was determined by the question “Has a doctor or other health professional ever told you that have asthma?” or by receiving treatment with antiasthmatic drugs.[17]
2.5. Statistical analysis
Statistical analysis was performed using StataSE15 (version 15.0, Stata Corp LP, TX) and R version 4.2.2 (www.R-project.org). All data were weighted using 2 years sample weight. All continuous variables were expressed as the means ± standard deviations. Categorical variables were counted as values and percentages. The Shapiro–Francia W test was used to confirm the normal distribution. Nonparametric tests (Pearson chi-square test for categorizing data; Kruskal–Wallis test for continuous data) were used to assess the differences among the emmetropia group, the mild and moderate myopia group, and the high myopia group. Survey-weight adjusted univariate and multivariate logistic regression analyses were used to assess the relationship between systemic inflammation markers and covariates with high myopia. We further used restricted cubic spline logistic regression analyses with 5 knots to explore the nonlinear associations between high myopia and systemic inflammation parameters, and the same covariates were adjusted in this analysis. A 2-sided P value < .05 was considered statistically significant.
3. Results
As Table 1 shows, a total of 2891 participants were included in the final analysis. The average age of the patients was 24.53 ± 0.20 years, and 1385 participants (47.91%) were male. The average BMI was 26.59 ± 0.17 kg/m2. Best-corrected visual acuity declined significantly in the high myopia group (P = .032). More participants with a higher BMI and having an education level “college education or above” were in the high myopia group, although there was no significant difference. There was no difference among the 3 groups in gender, diabetes, hypertension, asthma, anterior flat and steep keratometry, ethnicity, or PIR.
Table 1.
Characteristics of enrolled participants.
| Characteristic | Total | Emmetropia | Mild and moderate myopia | High myopia | P-trend |
|---|---|---|---|---|---|
| Patients, n (%) | 2891 (100) | 814 (28.16) | 1944 (67.24) | 133 (4.60) | – |
| Age (yr), mean (SD) | 24.53 (0.20) | 24.45 (0.48) | 24.45 (0.24) | 26.10 (0.89) | .826 |
| Gender, n (%) | .822 | ||||
| Male | 1385 (47.91) | 380 (46.68) | 945 (48.61) | 60 (45.11) | |
| Female | 1506 (52.09) | 434 (53.32) | 999 (51.39) | 73 (54.89) | |
| Diabetes, n (%) | .132 | ||||
| Yes | 131 (4.53) | 32 (3.93) | 91 (4.68) | 8 (6.02) | |
| No | 2760 (95.41) | 782 (96.07) | 1853 (95.32) | 125 (93.98) | |
| Hypertension, n (%) | .493 | ||||
| Yes | 464 (16.05) | 139 (17.08) | 302 (15.53) | 23 (17.29) | |
| No | 2427 (83.95) | 675 (82.92) | 1642 (84.47) | 110 (82.71) | |
| Asthma, n (%) | .165 | ||||
| Yes | 488 (16.88) | 127 (15.60) | 337 (17.34) | 24 (18.05) | |
| No | 2403 (83.12) | 687 (84.40) | 1607 (82.66) | 109 (81.95) | |
| BMI (kg/m2), mean (SD) | 26.59 (0.17) | 26.65 (0.37) | 26.45 (0.18) | 28.03 (0.93) | .840 |
| SE (D), mean (SD) | -1.62 (0.05) | -0.20 (0.01) | -1.71 (0.03) | -8.44 (0.30) | <.001 |
| BCVA (log MAR), mean (SD) | 0.14 (0.00) | 0.16 (0.01) | 0.13 (0.00) | 0.20 (0.02) | .032 |
| Anterior Kf (D), mean (SD) | 43.25 (0.04) | 43.27 (0.08) | 43.22 (0.05) | 43.58 (0.27) | .780 |
| Anterior Ks (D), mean (SD) | 44.44 (0.04) | 44.33 (0.06) | 44.42 (0.05) | 45.28 (0.31) | .069 |
| Ethnicity, n (%) | .929 | ||||
| White | 759 (26.25) | 230 (28.26) | 493 (25.36) | 36 (25.90) | |
| Black | 863 (29.85) | 226 (27.76) | 588 (30.25) | 49 (33.73) | |
| Mexican American | 958 (33.14) | 265 (32.65) | 658 (33.85) | 35 (28.31) | |
| Other | 311 (10.76) | 93 (11.43) | 205 (10.55) | 13 (9.77) | |
| Education, n (%) | .270 | ||||
| <9th grade | 1006 (34.80) | 288 (35.38) | 683 (35.13) | 35 (26.32) | |
| 9–11th grade | 880 (30.44) | 250 (30.71) | 595 (30.61) | 35 (26.32) | |
| High school grade | 434 (15.01) | 131 (16.09) | 288 (14.81) | 15 (11.28) | |
| College or above | 571 (19.75) | 145 (17.81) | 378 (19.44) | 48 (36.09) | |
| PIR | .748 | ||||
| PIR < 1.3, n (%) | 1185 (40.99) | 345 (42.38) | 794 (40.84) | 46 (34.59) | |
| PIR ≥ 1.3, n (%) | 1706 (59.01) | 469 (57.62) | 1150 (59.16) | 87 (65.41) |
BCVA = best-corrected visual acuity, BMI = body mass index, kg/m2, D = diopter, Kf = flat keratometry, Ks = steep keratometry, PIR = poverty-to-income ratio, SD = standard deviation, SE = spherical equivalent.
Table 2 presents a comparison of inflammatory parameters among different groups, including the emmetropia group, the mild and moderate myopia group, and the high myopia group. The results indicate that there was no statistical difference between of inflammatory parameters such as WBC, neutrophils, lymphocytes, monocytes, platelets, CRP, NLR, LMR, PLR, and SII among the 3 groups.
Table 2.
Characteristics of the systemic inflammatory parameters in emmetropic, mild and moderate myopic, and high myopic participants.
| Characteristic | Total | Emmetropia | Mild and moderate myopia | High myopia | P-trend |
|---|---|---|---|---|---|
| WBC (103/µL), mean (SD) | 7.45 (0.07) | 7.52 (0.10) | 7.41 (0.08) | 7.59 (0.23) | .397 |
| Neu (103/µL), mean (SD) | 4.38 (0.06) | 4.42 (0.08) | 4.35 (0.06) | 4.48 (0.21) | .471 |
| Lym (103/µL), mean (SD) | 2.26 (0.02) | 2.29 (0.03) | 2.24 (0.02) | 2.33 (0.07) | .209 |
| Mono (103/µL), mean (SD) | 0.56 (0.01) | 0.55 (0.01) | 0.57 (0.01) | 0.57 (0.02) | .123 |
| Plt (103/µL), mean (SD) | 282.04 (2.30) | 282.10 (3.02) | 282.20 (2.68) | 289.12 (13.98) | .865 |
| CRP (mg/dL), mean (SD) | 0.33 (0.03) | 0.30 (0.03) | 0.33 (0.03) | 0.50 (0.10) | .368 |
| NLR, mean (SD) | 2.08 (0.03) | 2.06 (0.05) | 2.09 (0.03) | 2.04 (0.11) | .665 |
| LMR, mean (SD) | 4.31 (0.04) | 4.42 (0.07) | 4.26 (0.05) | 4.38 (0.17) | .087 |
| PLR, mean (SD) | 133.73 (1.36) | 131.66 (2.47) | 134.73 (1.46) | 132.65 (7.30) | .289 |
| SII (103/µL), mean (SD) | 590.58 (8.63) | 587.77 (15.02) | 588.67 (9.58) | 630.09 (73.86) | .827 |
CRP = C-reactive protein, LMR = lymphocyte-to-monocyte ratio, Lym = lymphocytes, Mono = monocytes, Neu = neutrophils, NLR = neutrophil-to-lymphocyte ratio, PLR = platelet-to-lymphocyte ratio, Plt = platelets, SD = standard deviation, SII = systemic immune-inflammation index, WBC = white blood cells counts.
The association of high myopia and systemic inflammatory parameters was assessed via univariate and multivariate logistic regression analyses (Table 3). In univariate analysis, only CRP was a risk factor for high myopia (odds ratio [OR] = 1.315, 95% confidence interval [CI] 1.069–1.618; P = .010). The multivariate logistic regression analyses demonstrated that white blood counts (WBC, OR = 0.200, 95% CI 0.063–0.628; P = .007), neutrophils (OR = 5.000, 95% CI 1.534–16.297; P = .008), lymphocytes (OR = 6.269, 95% CI 1.857–21.161; P = .004), CRP (OR = 1.320, 95% CI 1.020–1.709; P = .036), NLR (OR = 0.644, 95% CI 0.424–0.977; P = .039), and SII (OR = 1.002, 95% CI 1.000–1.003; P = .013) were associated with high myopia incidence without adjustment. In model 2, we adjusted for age, gender, BMI, PIR, education, diabetes, hypertension, and asthma. We found that WBC (OR = 0.242, 95% CI 0.070–0.843; P = .027), neutrophils (OR = 4.052, 95% CI 1.127–14.559; P = .033), lymphocytes (OR = 4.989, 95% CI 1.287–19.337; P = .021), NLR (OR = 0.621, 95% CI 0.411–0.938; P = .025), and SII (OR = 1.002, 95% CI 1.000–1.003; P = .011) were still associated factors of high myopia. In addition, we found that female (OR = 1.712, 95% CI 1.197,2.448; P = .004) and participants with a “college or above” (OR = 2.806, 95% CI 1.400–5.627; P = .005) education level were more likely to have high myopia.
Table 3.
Associations of high myopia and the systemic inflammatory parameters.
| Factors | Univariate analysis | Model 1 | Model 2 | |||
|---|---|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | |
| Usual systemic inflammatory parameters | ||||||
| WBC (103/uL) | 1.030 (0.941, 1.127) | .517 | 0.200 (0.063, 0.628) | .007 | 0.242 (0.070, 0.843) | .027 |
| Neu (103/uL) | 1.031 (0.929, 1.144) | .555 | 5.000 (1.534, 16.297) | .008 | 4.052 (1.127,14.559) | .033 |
| Lym (103/uL) | 1.160 (0.823, 1.634) | .674 | 6.269 (1.857, 21.161) | .004 | 4.989 (1.287, 19.337) | .021 |
| Mono (103/uL) | 1.104 (0.285, 4.275) | .884 | 4.653 (0.858, 25.249) | .074 | 6.204 (0.918, 41.930) | .061 |
| Plt (103/uL) | 1.001 (0.997, 1.006) | .569 | 1.001 (0.995, 1.006) | .761 | 1.001 (0.996, 1.006) | .723 |
| CRP (mg/dl) | 1.315 (1.069, 1.618) | .010 | 1.320 (1.020, 1.709) | .036 | 1.202 (0.880, 1.643) | .241 |
| Four systemic inflammatory markers | ||||||
| NLR | 0.969 (0.803, 1.170) | .739 | 0.644 (0.424, 0.977) | .039 | 0.621 (0.411, 0.938) | .025 |
| LMR | 1.031 (0.891, 1.194) | .674 | 0.964 (0.792, 1.175) | .715 | 0.949 (0.657, 1.371) | .775 |
| PLR | 0.999 (0.803, 1.170) | .739 | 0.994 (0.987, 1.002) | .149 | 0.903 (0.717, 1.136) | .376 |
| SII | 1.001 (1.000, 1.001) | .492 | 1.002 (1.000, 1.003) | .013 | 1.002 (1.000, 1.003) | .011 |
| Significant covariate | ||||||
| Gender (female) | 1.778 (1.209, 2.617) | .004 | – | – | 1.712 (1.197,2.448) | .004 |
| Education | ||||||
| <9th grade | Ref | – | – | Ref | – | |
| 9–11th grade | 0.959 (0.506, 1.816) | .896 | – | – | 0.971 (0.502, 1.878) | .928 |
| High school Grade | 0.844 (0.345, 2.063) | .706 | – | – | 0874 (0.367, 2.081) | .756 |
| College or above | 2.826 (1.721, 4.639) | .004 | – | – | 2.806 (1.400, 5.627) | .005 |
Bold values represent significant differences.
Model 1: multivariate logistic analysis without adjustments.
Model 2: multivariate logistic analysis adjusted for age, gender, body mass index, poverty-to-income ratio, education level, diabetes, hypertension, and asthma.
CI = confidence interval, CRP = C-reactive protein, LMR = lymphocyte-to-monocyte ratio, Lym = lymphocytes, Mono = monocytes, Neu = neutrophils, NLR = neutrophil-to-lymphocyte, PLR = platelet-to-lymphocyte ratio, Plt = platelets, SII = systemic immune-inflammation index, WBC = white blood cells counts.
We further explored the nonlinear association of WBC, neutrophils, lymphocytes, NLR, SII, and high myopia. Nonlinear and ‘S-shaped’ associations were found between lymphocytes and high myopia (P for nonlinear = .019). The risk of high myopia was increased with lymphocytes when lymphocytes were smaller than 2.02 × 103 cells/µL, while the slope decreased when lymphocytes were over 2.87 × 103 cells/µl (Fig. 2C). There was also a “w-shaped” nonlinear relationship between the SII and high myopia; 3 knots were 362.48 × 103 cells/µL, 531.96 × 103 cells/µL, and 895.14 × 103 cells/µL (P for nonlinear = .005), as shown in Figure 2E. WBC, neutrophils, and NLR were not significantly associated with high myopia by restricted cubic splines analysis.
Figure 2.
Association between high myopia and white blood cells (A), neutrophils (B), lymphocytes (C), NLR (D), and SII (E) using restricted cubic spline analysis. NLR = neutrophil-to-lymphocyte ratio, SII = systemic immune-inflammation index.
4. Discussion
In recent years, growing evidence has suggested a link between chronic inflammation and high myopia. However, the association between systemic inflammation and high myopia remains poorly understood. To address this research gap, we conducted a cross-sectional study to investigate this issue. Our study revealed that WBC, neutrophils, lymphocytes, CRP, NLR, and SII were all associated with high myopia. However, after adjusting for various confounding factors, such as age, gender, BMI, PIR, education level, diabetes, hypertension, and asthma, the association between CRP and high myopia was no longer significant. Furthermore, our analysis using restricted cubic splines indicated that lymphocytes and the SII exhibited a nonlinear correlation with high myopia. Additionally, consistent with previous studies, we found that female and a “college and above” educational level were identified as risk factors.
The correlations between WBC and myopia have been mentioned in a previous study. Han SB et al reported a positive correlation between WBC and myopia in a population-based study in Korea.[18] However, in this study, we obtained different results. We found that WBC was not a significant risk factor for high myopia. We thought the reason for these differences may be the different populations of the 2 studies. The majority of ethnicity in high myopia patients was black in our study, which was not a significant risk ethnicity for myopia.[19] In addition, there was a piece of evidence that proved the WBC was lowest in black participants when compared with white and Mexican American participants.[20] From subgroup analysis, we found that the WBC counts in the emmetropia group and the high myopia group were very close. This indicates that in the US population, WBC was not a recommended index when assessing the risk of high myopia.
Nevertheless, we found that neutrophils were risk factors for high myopia, which was consistent with existing work in the literature. Wang X et al compared neutrophils between participants with and without high myopia and found an elevation of neutrophils in the high myopia group, although there was no significant difference.[21] Furthermore, we found that the association between lymphocytes and high myopia was stronger than that between neutrophils and high myopia in our study. This result provides a potential validation of a hypothesis that chronic inflammation related to myopia. Wei C et al reported that long-term allergic conjunctivitis promoted the development of myopia via a clinical and animal study.[22] Zarzuela JC et al verified that Th2 and NKT lymphocytes increased in patients with perennial allergic conjunctivitis, and seasonal allergic conjunctivitis was distinguished by an increase in Th17 and Th22 cell proportions.[23] Ocular surface lymphocytes may promote retinal inflammation and induce the progression of myopia. Thus, we thought that elevated systemic lymphocytes helped assess the risk of high myopia.
We further investigated the role of other systemic inflammation markers in high myopia. The NLR was a negatively associated factor of high myopia, which can be understood because lymphocytes were a stronger factor than neutrophils. In a Turkish and a Chinese study, the NLR was elevated in people with high myopia.[21,24] However, in our study, the NLR showed no significant tendency to increase with the severity of myopia. We thought the reason was that the age of the participants in this study was younger than that in the above 2 studies. The NLR increases with age.[25] In addition, the sample size of our study was larger than that of the above 2 studies, so our study may provide more information. In this study, we found that the SII was a risk factor for high myopia, which was not mentioned in previous research. SII, a novel inflammatory biomarker, has been proposed as a predictor of coronary artery disease, cancer, and autoimmune diseases.[26–29] It can act as a reliable indicator of inflammatory status in dry eye disease and primary open-angle glaucoma.[12,30] The SII may be a promising biomarker of high myopia due to its sensitivity to inflammatory changes. In the subgroup analysis, high myopia participants had the highest level of SII (Table 2).
In the present study, we also demonstrated that female participants and participants with “college or above” were more likely to have high myopia. Chinese data from 11,011 students from primary schools, junior high schools, and high schools revealed that female sex was a risk factor for myopia.[31] The probable reason was that females may prefer to perform some indoor activities; as a result, the outdoor time was less than that of males. In addition, the correlation between higher education level and myopia was also confirmed by previous studies. The study of Mountjoy et al showed that every additional year of education was associated with a more myopic refractive error of −0.18 to −0.27 D/yr.[32] Data analysis based on NHANES also proved that myopia was associated with higher education.[33] In addition, the spherical equivalent gap between subjects who graduated from college and those <9th grade school was −1.47 D33. These results indicated that gender and education factors were stable factors in different populations and ethnicities.
This study has some limitations. First, this study was a cross-sectional study, and some results may need a longitudinal study for confirmation. Second, axial length could not be obtained in our study, and several studies indicated that inflammation levels may increase with axial length; therefore, a study containing axial length will better explain the relationship between inflammation and myopia. Finally, the majority of ethnicity in this study was not susceptible to high myopia. Thus, a longitudinal and East Asian population-based study to validate these results will be promising.
5. Conclusions
In conclusion, we found that the prevalence of high myopia was 4.3% in the US population. WBC, neutrophils, lymphocytes, NLR, and SII were associated with high myopia after adjusting for age, gender, BMI, PIR, education level, diabetes, hypertension, and asthma. Neutrophils, lymphocytes, and the SII were risk factors for myopia. We found that lymphocytes and the SII were associated with high myopia in a nonlinear way. Overall, our findings provide a better understanding of the relationship between systemic inflammation and high myopia. However, further research is needed to elucidate the underlying mechanisms and establish causal relationships.
Author contributions
Conceptualization: Xiaoxun Gu.
Data curation: Xiaoxun Gu.
Formal analysis: Xiaoxun Gu.
Funding acquisition: Xiaoxun Gu.
Investigation: Xiaoxun Gu.
Methodology: Xiaoxun Gu.
Project administration: Xiaoxun Gu.
Resources: Xiaoxun Gu.
Software: Xiaoxun Gu.
Supervision: Xiaoxun Gu.
Validation: Xiaoxun Gu.
Visualization: Xiaoxun Gu.
Writing – original draft: Xiaoxun Gu.
Writing – review & editing: Xiaoxun Gu.
Abbreviations:
- BMI
- body mass index
- CI
- confidence interval
- CRP
- C-reactive protein
- LMR
- lymphocyte-to-monocyte ratio
- NLR
- neutrophil-to-lymphocyte ratio
- OR
- odds ratio
- PIR
- poverty-to-income ratio
- PLR
- platelet-to-lymphocyte ratio
- SE
- spherical equivalent
- SII
- systemic immune-inflammation index
- WBC
- white blood cells
This study was supported by the Postdoctoral projects of Xi’an People’s Hospital (2022LBSH11) and Shaanxi Natural Science Basic Research Project (2025JC-YBQN-1258).
The NHANES Institutional Review Board/NCHS Research Ethics Review Board approved the conduct of the NHANES serial cross-sectional survey, and all the participants signed informed consent.
The author has no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are publicly available.
How to cite this article: Gu X. Systemic inflammation associated with high myopia: Evidence from NHANES 2001–2008. Medicine 2025;104:44(e45592).
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