Association between systemic immune inflammation index and osteoarthritis in US adults: a cross-sectional study

doi:10.21203/rs.3.rs-3863944/v1

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Association between systemic immune inflammation index and osteoarthritis in US adults: a cross-sectional study

https://doi.org/10.21203/rs.3.rs-3863944/v1

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Background

The relationship between systemic immune inflammation index (SII) and the osteoarthritis (OA) has not been well established. This study aimed to investigate the associations between SII and OA risk using data from the National Health and Nutrition Examination Survey (NHANES) 2005–2016.

Methods

A cross-sectional study was conducted using data from participants in NHANES 2005–2016. SII is calculated as platelet count × neutrophil count/lymphocyte count. Multivariable logistic regression models were used to explore the link between SII and osteoporosis, adjusting for potential confounders.

Results

A total of 18,459 participants were included, of which 1130 reported having OA. After adjusting for potential confounders, an inverse association was observed between SII and OA (OR = 1.27; 95% CI = 1.07–1.51, p = 0.006). Moreover, we also identify that SII of 515.56 is the optimal cut-off value, indicating that when the SII value exceeds the cut-off value, the risk increases rapidly.

Conclusions

In this large, nationally representative sample of U.S. adults, higher SII was negatively associated with the risk of OA. Further prospective studies are needed to confirm these findings and elucidate potential underlying mechanisms.

systemic immune-inflammation index

NHANES

cross-sectional study

Osteoarthritis (OA), the most prevalent form of arthritis, manifests as a multifactorial joint disorder characterized by the progressive degradation of articular cartilage, osteophyte formation, and subchondral bone sclerosis[1, 2]. These pathological changes result in joint pain, stiffness, and functional impairment, substantially impacting the quality of life. The etiology of OA is multifaceted, intertwining mechanical, genetic, metabolic, and inflammatory factors, leading to its heterogeneous nature[3–5].

The Systemic Immune-Inflammation Index (SII), which combines neutrophil, lymphocyte, and platelet counts, has emerged as a comprehensive marker reflecting the balance between host inflammatory and immune status[6–8]. Accumulating studies have indicated that SII emerged as a strong prognostic value for tumors and chronic diseases induced by immune dysfunction or chronic inflammation [9–11]. While SII has been extensively studied in the context of various malignancies and cardiovascular diseases, its association with degenerative joint diseases, particularly OA, remains under-explored.

Given the close association between inflammatory responses and the pathogenesis of OA, exploring this relationship is of significant interest. And the relationship between the SII index and OA is currently unknown. Therefore, the purpose of our study was to clarify the relationship between SII and OA among the participants of the National Health and Nutrition Examination Survey (NHANES). We hypothesized that an elevated SII would be associated with a higher risk of OA.

Study Design and participants

This study was based on NHANES 2005–2016. NHANES is a nationally representative, cross-sectional survey administered by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). The survey aims to assess the health and nutritional status of the U.S. civilian, non-institutionalized population by combining interviews and physical examinations. The Institutional Review Board (IRB) at the National Center for Health Statistics granted approval for all protocols, and informed consent was required from participants. We processed and interpreted the downloaded data using R software (version 3.4.3).

The exclusion criteria included: 1) individuals aged < 20 years; 2) individuals with missing data on arthritis; 3) individuals with rheumatoid arthritis, psoriasis arthritis or other type of arthritis; 4) a pregnancy at baseline; 5) having cancer at baseline; 6) individuals with missing data on platelets, neutrophils, and lymphocytes; and 7) for whom information on other covariates was incomplete. Finally, 18,459 participants from NHANES 2005–2016 were included.

Definition of Systemic Immune-Inflammation Index

Complete blood count (CBC) parameters were derived using the Beckman Coulter methodology, which combines counting and sizing techniques with an automated diluting and mixing device for sample processing and employs a single-beam photometer for hemoglobinometry. The white blood cell (WBC) differential was assessed using VCS technology. The NHANES mobile examination center (MEC) utilized the Beckman Coulter DxH 800 instrument to produce a CBC from blood specimens, providing a cellular distribution for all participants. SII is defined as the platelet count multiplied by the neutrophil count, divided by the lymphocyte count, as previously described[12, 13].

Assessment of OA

The diagnosis of OA was established based on self-reported personal interview data obtained through health condition questionnaires. Initially, participants were queried with the question, "Has a doctor or other health professional ever informed you that you have arthritis?" The response options included "Yes" or "No". If the response was "Yes", participants were further asked to specify the type of arthritis they had. Those participants whose response indicated OA were identified as having OA.

Covariates

Demographic data included age, sex (male, female), race (non-Hispanic White, non-Hispanic Black, Mexican American, and other races), education level (under high school, high school, or equivalent, above high school) and poverty-to-income ratio (PIR < 1, 1–2 or > 3). Drinking status was classified as never (had < 12 drinks in a lifetime), former (had ≥ 12 drinks in 1 year and did not drink last year, or did not drink last year but drank ≥ 12 drinks in a lifetime), current light/moderate drinker (≤ 1 drink per day for women or ≤ 2 drinks per day for men on average over the past year), or current heavier drinker (> 1 drink per day for women or > 2 drinks per day for men on average over the past year). Smoking status was categorized as never smokers (smoked < 100 cigarettes during lifetime and does not smoke now), former smokers (smoked > 100 cigarettes during lifetime and does not smoke now), and current smokers (smoked at least 100 cigarettes in life and smoke now) according to self-reported smoking status. Body mass index (BMI) was categorized as < 25, 25–29.9 and ≥ 30 kg/m², which corresponded to normal weight, overweight, and obese population for participants.

The diagnosis of diabetes was based on any of the following criteria were met: (1) A self-reported doctor’s diagnosis of diabetes. (2) Use of anti-diabetic drugs. (3) A Hemoglobin A1c (HbA1c) level ≥ 6.5% [25]. The diagnosis of hypertension was based on any of the following criteria were met: (1) A self-reported diagnosis of hypertension. (2) Use of anti-hypertensive drugs. (3) Systolic blood pressure greater than 140mmHg or diastolic blood pressure higher than 90mmHg.

Statistical Analysis

All statistical analyses were conducted using R software (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria). In accordance with the intricate NHANES survey design, we adhered to the NHANES recommendations and appropriately implemented a six-year cycle of weights, stratification, and clustering for each analytical procedure in our study. Categorical variables are represented as numerical values and weighted proportions, while continuous variables are reported as weighted means (Standard Deviation).

We observed that the distribution of the SII data is not uniform, and it exhibits a noticeable rightward skew. Consequently, it is necessary to apply a log2 transform to its values before we proceed with any statistical analysis. SII were categorized into quartiles, with quartile 1 (Q1) representing the lowest values and quartile 4 (Q4) representing the highest values. Weighted two-tailed t-tests were employed for continuous variables, and weighted Rao-Scott chi-square tests were utilized for categorical variables. Multivariate logistic regression analysis was used to evaluate the correlation between SII and the risk of OA in different models. Crude Model: confounding variables were not adjusted. Model 1: age, sex and race were adjusted. Model 2: age, sex, race, education levels, PIR and BMI were adjusted. Model 3: age, sex, race, education levels, PIR, BMI, hypertension, diabetes, drinking status, smoking status, white blood cell count, and red blood cell count were adjusted. Furthermore, logistic regression based on restricted cubic splines with four knots was conducted to examine the nonlinear association between SII and OA.

Tests for linear trend were calculated by assigning the median value to each quartile of intake. Subgroup analyses were also conducted, stratified by age, sex, race, BMI, smoking status, drinking status, diabetes, and hypertension. Likelihood ratio tests were employed to test for interactions. All P values were two-sided, and P values less than 0.05 were considered to indicate statistical significance.

Basic characteristics of the study participants

After screening the six cycles of NHANES, 18,459 individuals met our inclusion criteria and were enrolled in our final analysis. The detailed selection flow was presented in Fig. 1. The demographic data and laboratory indexes of the finally enrolled 18,459 participants were presented in Table 1. The study population was divided into 4 groups based on the quartile of SII. Of all the included individuals, 52.73% were males, and 47.27% were females. The number of patients diagnosed with OA was 1130 (6.1%). A progressive and significant increase in the risk of OA with SII levels was observed in Table 1 (p < 0.0001). Compared with the Q1 group, individuals in the Q4 group were more likely to be less male, non-Hispanic black, never smokers and heavier drinkers. Female, white ethnicity, highly educated level and higher BMI were associated with higher SII levels. Moreover, the frequency of hypertension and diabetes increased gradually with increasing levels of SII (Table 1).

Multivariate logistic regression analysis of OA

According to multivariate logistic regression analysis (Table 2), older age, females, non-Hispanic black, higher BMI (> 25), smokers (current or past smokers), non-drinkers, diabetes (yes), and hypertension (yes) were related to a higher risk of OA (OR > 1, p < 0.05). However, participants who PIR (1–3 and > 3) presented a reduced risk of OA (OR < 1, p < 0.05).

Relationship between OA and SII

After performing a weighted multivariate logistic regression analysis (Table 3), our results indicate that a higher SII score is associated with an increased risk of developing OA. This association was significant in our crude model (OR = 1.43; 95% CI = 1.22–1.69, p < 0.001), model 1 (OR = 1.38; 95% CI = 1.12–1.53, p < 0.001), and model 2 (OR = 1.31; 95% CI = 1.12–1.53, p < 0.001). In the fully adjusted model (model 3), the positive association between SII and OA remained stable (OR = 1.27; 95% CI = 1.07–1.51, p = 0.006), indicating that for every unit increase in In-SII score, the risk of developing OA increased by 27%.

We further transformed the SII from a continuous variable into a categorical variable (quartiles) for sensitivity analysis (Table 3). Compared with the lowest quartile, the risk of OA in the highest quartile increased by 47% (OR = 1.47; 95% CI = 1.20–1.80, p < 0.001) in the crude model, 47% (OR = 1.47; 95% CI = 1.18–1.84, p < 0.001) in the model 1, 37% (OR = 1.37; 95% CI = 1.10–1.71, p = 0.006) in model 2 and 32% (OR = 1.32; 95% CI = 1.03–1.68, p = 0.029) in model 3.

The non‑linear relationship between OA and SII

Using restricted cubic splines, a non-linear relationship between log2-SII and OA risk was found after adjustment for multiple covariates (Fig. 3) (p < 0.001). Moreover, as a threshold effect can be observed, we identified log2-SII value of 9.01 (SII = 515.56) as an inflection point. When the SII value is less than the cut-off value, the risk of OA is almost unchanged or even decreased, and when the SII value exceeds the cut-off value, the risk increases rapidly.

Subgroup analysis

Subgroup analysis results are shown in Fig. 4. In patients with OA, there were no differences in SII level in most subgroups, with the exception of sex. High SII levels were independently related to OA in male patients (OR = 1.42, 95% CI: 1.08–1.87, p = 0.014), but not in female patients. The interaction test revealed no significant differences among age, race, BMI, smoking status, drinking status, diabetes, and hypertension in the relationship between SII and OA, demonstrating that these factors had no significant influence on this positive relationship (p for interaction > 0.05). Contrary, sex may influence the positive association between SII and OA (p for interaction < 0.05).

This is the first study to investigate the association between SII level and the risk of OA in US adults by using NHANES data. Our cross-sectional study, including a substantial cohort of 18,459 participants, demonstrated that participants with OA had significantly higher SII levels. And we also observed a non-linear relationship between SII and the risk of OA. Furthermore, we found that when SII is higher than 515.56, the risk of OA will increase significantly.

SII cut-off values have been explored to determine disease prevalence or predict health outcomes. However, there are few studies investigating the relationship between the SII cut-off values and OA. Satis et al. [14]observed that SII cut-off point of 574.20 is the best cut-off point for active RA. Zhang et al. [15] concluded the SII of 530.09 is an optimal cut-off value for indicating the occurrence of osteoporosis. Our study demonstrated that an SII of 515.56 is the optimal cut-off point for our population of interest. This lower threshold suggests that subjects with OA may have different clinical characteristics or baseline inflammation levels compared to those in previous studies. Our results emphasize the need for specific approaches in the application of SII cut-off values for disease diagnosis and prognosis, reflecting the variability among populations and the dynamic nature of disease pathophysiology.

Previous studies have demonstrated that inflammation plays a crucial role in OA pathophysiology[16, 17]. Elevated levels of pro-inflammatory cytokines, such as interleukin-1 beta (IL-1β), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6), have been detected in the synovial fluid and serum of OA patients[18]. It is reported that IL-1β contribute to cartilage degradation and joint inflammation by promoting the expression of matrix-degrading enzymes and inducing chondrocyte dysfunction[19–21].

Additionally, IL-1β activates extracellular signal-regulated kinases (ERK), which in turn downregulates type II collagen and aggrecan gene expression, resulting in reduced synthesis of the cartilage extracellular matrix (ECM)[22]. Furthermore, IL-1β has been identified as a potent stimulator of reactive oxygen species (ROS) production[23–25]. These ROS, including peroxides and hydroxyl radicals, are implicated in directly inflicting damage upon articular cartilage. TNF-α, another cytokine with potent proinflammatory properties, significantly contributes to the regulation and amplification of inflammatory responses in OA. Westacott et al. reported that the activity of tumor necrosis factor receptor 1(TNRF-1) exerts a more pronounced effect on the localized loss of cartilaginous tissue[26]. TNF-α has been shown to induce the production of key enzymes such as iNOS, cyclooxygenase-2 (COX-2), and prostaglandin E synthase 2 (PGE-2 synthase). This induction, in turn, further upregulates the synthesis of IL-1 β and TNF-α, creating a feedback loop that amplifies the inflammatory response[27–29]. Interleukin-6 (IL-6) principally exacerbates synovitis by facilitating angiogenesis, recruiting inflammatory cells, and promoting synovial cell proliferation. Pearle et al. suggested that systemic levels of high-sensitivity C-reactive protein may serve as indicators of synovial inflammation in patients with OA, potentially through the mediation of IL-6 synthesis[30]. Enhanced concentrations of IL-6 have been detected concurrently in the synovial fluid and serum, demonstrating a positive correlation with the lesion severity as delineated by radiographic imaging in X-rays[31–33].

SII, a novel biomarker, represents a comprehensive measure of systemic inflammation by incorporating peripheral blood cell counts, including neutrophils, lymphocytes, and platelets. Recent studies have investigated the association between the SII and bone diseases, such as rheumatoid arthritis (RA)[34], osteoporosis[15], ankylosing spondylitis[35] and psoriatic arthritis[36]. Liu et al. [34] demonstrated that SII could be used as a valuable and convenient biomarker to predict the risk of RA. Zhang et al. [15] suggested that that an elevated SII is positively associated with the prevalence of osteoporosis in middle-aged and older individuals. In that study, SII of 530.09 is an optimal cut-off value for indicating the occurrence of osteoporosis. The study by Wu et al. indicated that patients diagnosed with ankylosing spondylitis exhibited significantly elevated levels of SII in comparison to healthy control subjects[35]. Another study reported statistically significant correlations of disease activity with SII in psoriatic arthritis[36]. SII serves as a valuable tool for quantifying the systemic immune response and may offer insights into the inflammatory component of OA.

Our study has some limitations. Initially, the cross-sectional design of our study inherently limits the capacity to deduce a direct causative linkage between the SII and OA. The need for future multicenter, prospective studies is imperative to substantiate the hypothesized causal correlations and to delineate definitive inflection points in OA. Sequentially, evaluations of neutrophil, lymphocyte, and platelet counts—crucial constituents of the SII—were performed at a singular temporal juncture. This isolated measure may not accurately mirror the persistent inflammatory milieu characteristic of entrenched OA, particularly considering the disease’s variable clinical trajectory. Moreover, our research did not integrate markers indicative of immediate inflammation, for example, C-reactive protein levels or erythrocyte sedimentation rates, which could potentially augment the understanding of the inflammatory condition of the participants. Lastly, although we have adjusted for several confounding factors, the existence of other, non-quantified confounding factors within the analysis and subgroup analysis cannot be entirely precluded.

In summary, we observed a positive correlation between SII and OA. Further large-scale prospective studies are necessary to confirm our findings.

Institutional Review Board Statement

The study was carried out in compliance with the Declaration of Helsinki. Ethical review and approval were not required for this study, as it involved the use of publicly available data and did not qualify as human subject research in the United States.

Informed Consent Statement

NHANES has obtained informed consent from all participants.

Data Availability Statement

Those datasets generated and analyzed in the current study can be found at NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm).

Funding

This research received no funding.

Consent for publication

Not applicable

Acknowledgments

The authors thank all the NHANES study participants for their assistance.

Authors’ Contributions

Conception and design: Zaijun Lin, Duojun Wang and Cai Liu;

Collection and assembly of data: Jianguo Fang and Hui Zhang;

Data analysis and interpretation: Jianguo Fang;

Manuscript writing: All authors;

Final approval of manuscript: All authors.

Conﬂicts of Interest

The authors declare no conﬂict of interest.

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Table 1 Weighted characteristics of study participants

Characteristics	Quintile categories of SII
Characteristics	Q1	Q2	Q3	Q4	P values
	4615	4616	4613	4615
Age (years, mean ± SD)	42.08 ±15.49	42.22 ±15.26	43.01 ± 15.00	43.82 ±15.49	0.006
Gender, n (%)
Male	2714 (58.8)	2545 (55.14)	2408 (52.19)	2069 (44.83)	<0.001
Female	1901 (41.2)	2071 (44.86)	2205 (47.81)	2546 (55.17)
Race/ethnicity, n (%)
Non-Hispanic white	2615 (56.67)	3040 (65.85)	3141 (68.08)	3283 (71.13)	<0.001
Non-Hispanic black	935 (20.27)	475 (10.30)	388 (8.41)	354 (7.68)
Mexican American	439 (9.51)	443 (9.60)	466 (10.11)	436 (9.44)
Others	626 (13.55)	658 (14.26)	618 (13.40)	542 (11.74)
Education level, n (%)
Below high school	748 (16.21)	702 (15.21)	717 (15.55)	735 (15.93)	0.005
High school or equivalent	977 (21.17)	943 (20.42)	1060 (22.98)	1120 (24.26)
Above high school	2890 (62.62)	2971 (64.37)	2836 (61.47)	2760 (59.81)
PIR, n (%)
≤ 1	732 (15.87)	646 (14)	645 (13.99)	709 (15.37)	0.053
1＜ to ≤ 3	1675 (36.29)	1649 (35.72)	1586 (34.37)	1651 (35.77)
＞3	2208 (47.84)	2321 (50.29)	2382 (51.64)	2255 (48.86)
Diabetes, n (%)
Yes	467 (10.11)	437 (9.46)	518 (11.23)	599 (12.98)	<0.001
No	4148 (89.89)	4179 (90.54)	4095 (88.77)	4016 (87.02)
Hypertension, n (%)
Yes	1432 (31.04)	1414 (30.64)	1549 (33.57)	1717 (37.2)	<0.001
No	3183 (68.96)	3202 (69.36)	3064 (66.43)	2898 (62.80)
BMI, n (%)
Normal	1672 (36.23)	1592 (34.49)	1364 (29.57)	1408 (30.5)	<0.001
Overweight	1664 (36.05)	1586 (34.35)	1579 (34.23)	1457 (31.57)
Obese	1279 (27.71)	1438 (31.16)	1669 (36.19)	1750 (37.93)
Smoking status, n (%)
Never smoker	2738 (59.33)	2718 (58.87)	2680 (58.11)	2455 (53.19)	<0.001
Current smoker	971 (21.05)	987 (21.39)	935 (20.27)	1031 (22.34)
Past smoker	905 (19.62)	911 (19.74)	998 (21.63)	1129 (24.47)
Drinking status, n (%)
Former	533 (11.54)	508 (11.01)	502 (10.88)	477 (10.33)	<0.001
Never	587 (12.73)	532 (11.53)	615 (13.33)	664 (14.39)
Moderate	1674 (36.28)	1649 (35.73)	1534 (33.26)	1448 (31.38)
Heavy	1821 (39.45)	1927 (41.73)	1962 (42.54)	2026 (43.89)
White blood cell	6.06 ± 1.94	6.75 ± 1.63	7.37 ± 1.79	8.54 ± 2.44	<0.001
Red blood cell	4.71 ± 0.49	4.74 ± 0.47	4.75 ± 0.47	4.72 ± 0.48	0.033
Lymphocyte	2.41 ± 1.23	2.23 ±0.65	2.11 ±0.62	1.90 ±0.61	<0.001
Neutrophils	2.90 ± 0.93	3.74 ± 0.97	4.44 ±1.15	5.79 ± 1.94	<0.001
Platelet	207.73 ± 48.28	236.48 ± 49.34	259.08 ± 51.06	294.35 ± 70.90	<0.001
SII	251.49 ±57.35	394.06 ± 37.01	542.98 ± 52.40	922.80 ± 403.78

Data are expressed as weighted proportions (± Standard Error (SE)) for categorical variables and as weighted means ± SE for continuous variables. Weighted two-tailed t tests and weighted Rao-Scott chi-square test were used to compare difference between groups.

NHANES, National Health and Nutrition Examination Survey; OA, rheumatoid arthritis; BMI, body mass index; PIR, the ratio of family income to poverty; SD, standard deviation; n, numbers of subjects; %, weighted percentage; SII, systemic immune inflammation index.

Table 2 Weighted univariate logistic analysis of OA

Variables	OR 95% CI	P value
SII	1.27 (1.07, 1.51)	0.006
Age	1.05 (1.04, 1.06)	<0.001
Female (versus male)	1.44 (1.17, 1.78)	0.001
Race (versus Non-Hispanic white)
Non-Hispanic black	1.34 (1.1, 1.64)	0.005
Mexican American	0.83 (0.65, 1.06)	0.129
Others	0.83 (0.67, 1.04)	0.099
Education level (versus below high school)
High school or equivalent	0.89 (0.69, 1.15)	0.359
Above high school	0.86 (0.69, 1.08)	0.2
PIR (versus PIR≤ 1)
1＜ to ≤ 3	0.69 (0.55, 0.88)	0.003
＞3	0.52 (0.39, 0.70)	<0.001
Diabetes (no versus yes)	1.26 (1.03, 1.56)	0.029
Hypertension (no versus yes)	1.55 (1.25, 1.91)	<0.001
Red blood cell	0.68 (0.57, 0.81)	<0.001
White blood cell	0.99 (0.95, 1.03)	0.572
Smoking status (versus never)
Current smoker	1.35 (1.07, 1.7)	0.011
Past smoker	2.00 (1.57, 2.55)	<0.001
Body mass index (versus normal)
Overweight	1.02 (0.81, 1.29)	0.851
Obese	1.9 (1.52, 2.36)	<0.001
Drinking status (versus former)
Never	1.48 (1.1, 2)	0.011
Moderate	0.96 (0.71, 1.28)	0.767
Heavy	0.89 (0.67, 1.2)	0.441

Table 3 OR (95% conﬁdence intervals) of OA across quartiles of magnesium, copper and potassium intakes, NHANES 2005–2016.

	Crude model		Model 1		Model 2		Model 3
	OR 95% CI	P‑value	OR 95% CI	P‑value	OR 95% CI	P‑value	OR 95% CI	P‑value
SII	1.43 (1.22, 1.69)	<0.001	1.38 (1.18, 1.60)	<0.001	1.31 (1.12, 1.53)	<0.001	1.27 (1.07, 1.51)	0.006
Stratified by SII quartiles
Q1	ref		ref		ref		ref
Q2	1.01 (0.79, 1.30)	0.940	1.09 (0.83, 1.42)	0.545	1.67 (0.82, 1.39)	0.623	1.09 (0.84, 1.42)	0.523
Q3	0.98 (0.79, 1.22)	0.884	1.04 (0.82, 1.32)	0.760	0.99 (0.78, 1.26)	0.926	0.97 (0.77, 1.23)	0.806
Q4	1.47 (1.20, 1.80)	<0.001	1.47 (1.18, 1.84)	<0.001	1.37 (1.10, 1.71)	0.006	1.32 (1.03, 1.68)	0.029
P for trend	<0.001		<0.001		0.007		0.046

No competing interests reported.

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Association between systemic immune inflammation index and osteoarthritis in US adults: a cross-sectional study

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Abstract

Background

Methods

Results

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Introduction

Method

Study Design and participants

Definition of Systemic Immune-Inflammation Index

Assessment of OA

Covariates

Statistical Analysis

Results

Basic characteristics of the study participants

Multivariate logistic regression analysis of OA

Relationship between OA and SII

The non‑linear relationship between OA and SII

Subgroup analysis

Discussion

Conclusion

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References

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