Association between platelet-to-lymphocyte ratio and chronic obstructive pulmonary disease：findings based on NHANES 1999–2018

Association between platelet-to-lymphocyte ratio and chronic obstructive pulmonary disease：findings based on NHANES 1999–2018 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association between platelet-to-lymphocyte ratio and chronic obstructive pulmonary disease：findings based on NHANES 1999–2018 Yuan Luo, Haibo Gong, Xiao Chen, Li Chen, Dingfan Zhou, Liyue Zhang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6906240/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective: The platelet-lymphocyte ratio (PLR) is one of the recognized indicators of systemic inflammation. Currently, there are no studies on the relationship between this individual indicator of PLR and chronic obstructive pulmonary disease. This study aims to clarify the relationship between the inflammatory response indicator platelet-lymphocyte ratio (PLR) and chronic obstructive pulmonary disease in the adult population. Method: Adults with chronic obstructive pulmonary disease who were included in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 are the subjects of the current cross-sectional survey. The relationship between PLR and the prevalence of COPD was analyzed using the generalized linear model. Then visualize the relationship between them using restricted cubic splines (RCS). Subgroup analysis was conducted to evaluate the robustness of the relationship between the PLR index and the prevalence of COPD. Result: This study included a total of 22,679 subjects, of whom 973 were diagnosed as having COPD. The restricted cubic spline (RCS) curve demonstrated a linear relationship between the PLR index and COPD prevalence. A positive association was observed between the PLR index and COPD (β = 1.002, 95% CI: 1.001–1.003, P < 0.001). Subgroup analyses and interaction tests confirmed the robustness of this relationship, which remained consistent across most subgroups. Conclusion: This study found that there is a linear relationship between the PLR index and the prevalence of COPD, which has an impact on public health. The control of PLR inflammatory indicators plays a key role in reducing the occurrence of COPD and improving long-term health outcomes. platelet-lymphocyte ratio chronic obstructive pulmonary disease NHANES cross-sectional study population-based study Figures Figure 1 Figure 2 1. Introduction Chronic obstructive pulmonary disease (COPD) remains a leading cause of global morbidity and mortality, affecting over 300 million people worldwide and contributing significantly to healthcare burdens[1,2].As a complex inflammatory airway disorder, COPD is characterized by persistent respiratory symptoms and progressive airflow limitation, predominantly driven by chronic inflammation and oxidative stress[3-5]. Despite established clinical biomarkers such as C-reactive protein (CRP) and white blood cell count (WBC), there is growing interest in identifying readily accessible, cost-effective inflammatory indicators to enhance risk stratification and pathophysiological understanding[6-8]. The platelet-to-lymphocyte ratio (PLR), an integrative hematological index derived from routine complete blood counts, has emerged as a novel biomarker reflecting systemic inflammation and immune activation[9-11]. Elevated PLR has been independently associated with adverse outcomes in cardiovascular diseases, malignancies, and other chronic inflammatory conditions, owing to its dual representation of thrombotic activity (via platelets) and immune regulation (via lymphocytes)[12-15]. However, evidence regarding its relationship with COPD prevalence and severity remains limited and inconsistent, with most prior studies constrained by single-center designs, small sample sizes, or restricted demographic coverage. Leveraging the National Health and Nutrition Examination Survey (NHANES) 1999–2018—a nationally representative database with standardized protocols—this study aims to comprehensively investigate the association between PLR and COPD in a large, multi-ethnic adult population. We hypothesize that elevated PLR is independently associated with increased COPD prevalence and may serve as an accessible indicator of chronic inflammatory burden in these patients. Our analysis further explores potential nonlinear relationships and subgroup variations, addressing critical gaps in existing literature while providing epidemiological insights derived from high-quality, population-level data. 2. Methods 2.1 Study design and population This study is a cross-sectional study, and the database is from NHANES. NHANES is a comprehensive survey aimed at collecting data on the health status of the US population. NHANES adopted a stratified multi-stage random sampling method, ensuring the representativeness of the national sample[16]. NHANES was approved by the Ethics Review Committee of the National Center for Health Statistics, and each participant provided informed consent by signing an agreement[17]. These datasets contain complete files and protocols, which are publicly available on the NHANES website and are consistent with the laboratory technicians and anthropometric procedures in our previous research[18]. We screened and analyzed the data from 1999 to 2018. To ensure the integrity and reliability of the results, specific exclusion criteria were applied, including (1) individuals under 20 years old (n=46235); (2) There is no PLR index (n=5459); (3) Individuals lacking COPD (n=3); (4) The data of Cancer, LDL, TC and TG are incomplete. A total of 22,679 subjects were enrolled in our study (Figure 1). 2.2 Chronic obstructive pulmonary disease(COPD) definition In this study, COPD diagnosis was primarily ascertained based on self-reported medical history. Utilizing questionnaire data from the NHANES database, participants were classified as having COPD if they responded "YES" to either of the following items: "Has a doctor or other health professional ever told you that you have emphysema?" or "Has a doctor or other health professional ever told you that you have chronic bronchitis?" [19]. 2.3 Platelet-to-lymphocyte ratio(PLR) assessment PLR (platelet-to-lymphocyte ratio) was calculated from complete blood count (CBC) data obtained during NHANES physical examinations. Blood specimens were processed, stored, and shipped to designated laboratories at the National Center for Environmental Health and Centers for Disease Control and Prevention (CDC) for analysis. Certified CDC laboratory technicians performed all procedures following standardized protocols. PLR was derived by dividing absolute platelet count by absolute lymphocyte count. The accuracy and reliability of these measurements were ensured through rigorous NHANES quality control procedures [20]. 2.4 Covariate variables The covariates assessed in this study comprised: gender (male, female), age (years), race/ethnicity (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Other Race), education level ( high school), marital status (married/cohabiting, widowed/divorced/separated, never married), family poverty income ratio (PIR), body mass index (BMI; kg/m²), smoking status (never smoker: 12 drinks/year; never drinker; unknown), hypertension (defined as average systolic blood pressure ≥140 mmHg, and/or diastolic blood pressure ≥90 mmHg, self-reported diagnosis, or use of antihypertensive medication [21]), diabetes mellitus (defined as fasting blood glucose ≥7.0 mmol/L [≥126 mg/dL], glycated hemoglobin (HbA1c) >6.5%, self-reported diagnosis, or use of hypoglycemic agents/insulin), cancer (self-reported physician-diagnosed cancer; MCQ220), stroke (self-reported physician-diagnosed stroke; MCQ160f), and heart disease (self-reported physician-diagnosed heart failure [MCQ160b], coronary heart disease [MCQ160c], angina [MCQ160d], or myocardial infarction [MCQ160e]). Laboratory variables included aspartate aminotransferase (AST; U/L), alanine aminotransferase (ALT; U/L), triglycerides (TG; mg/dL), total cholesterol (TC; mg/dL), and low-density lipoprotein cholesterol (LDL-C; mg/dL). 2.5 Statistical analysis Statistical analyses accounted for NHANES's complex survey design using CDC-recommended sampling weights per National Center for Health Statistics (NCHS) guidelines. Weighted chi-square tests analyzed categorical variables, while continuous variables were assessed via weighted one-way ANOVA. The PLR-COPD relationship was evaluated through multivariable linear regression across three hierarchical models: Model 1 (unadjusted); Model 2 (adjusted for sex, age, and race); Model 3 (additionally adjusted for marital status, education level, BMI, poverty-income ratio, smoking status, alcohol consumption, hypertension, diabetes, heart disease, stroke, cancer, ALT, AST, total cholesterol, triglycerides, and LDL). Stratified analyses examined subgroups by sex (male/female), race/ethnicity (White/Black/Mexican American/other), alcohol intake (≥12/<12 drinks/year, unknown), smoking status (never/former/current), hypertension, diabetes, cancer, stroke, and heart disease. Nonlinear relationships were investigated using smooth curve fitting, with threshold effects analyzed via two-piecewise linear regression. All analyses were performed using R v4.1.3 with EmpowerStats, with statistical significance defined as two-tailed P < 0.05. 3. Results 3.1 Baseline characteristics This study included 22,679 participants (mean age 49.88 ± 18.16 years; 47.87% male) stratified by platelet-to-lymphocyte ratio (PLR) quartiles (Q1-Q4). As detailed in Table 1, the highest PLR quartile (Q4) demonstrated significantly higher proportions of females (P < 0.05), Non-Hispanic White individuals (P < 0.05), and participants with advanced education (P < 0.05). Conversely, the lowest quartile (Q1) was associated with lower poverty-income ratios and higher body mass index values. Participants with diabetes, hypertension, heart disease, and COPD were predominantly distributed in lower PLR quartiles, with COPD patients exhibiting significantly reduced PLR values compared to non-COPD counterparts (P < 0.001). 3.2 Relationship between PLR and CODP In this multiple linear regression analysis examining the association between platelet-to-lymphocyte ratio (PLR) and chronic obstructive pulmonary disease (COPD), continuous PLR per standard deviation increase showed a significant positive association across all models. Specifically, in the unadjusted Model 1, the β coefficient was 1.003 (95% CI: 1.002–1.004, p<0.00001), which attenuated but remained significant in Model 2 after adjusting for gender, age, and race (β=1.001, 95% CI: 1.000–1.002, p=0.026), and in the fully adjusted Model 3 (β=1.002, 95% CI: 1.001–1.003, p<0.0001). For categorical PLR quartiles, with Q1 as the reference, Q4 demonstrated significantly elevated risk in Model 1 (β=1.216, 95% CI: 1.022–1.446, p=0.027) and Model 3 (β=1.249, 95% CI: 1.036–1.506, p=0.020), but not in Model 2 (β=1.018, 95% CI: 0.850–1.218, p=0.850). Q2 and Q3 showed no significant associations. Strong linear trends were observed for all models (p<0.00001 for Model 1, p=0.026 for Model 2, and p<0.0001 for Model 3)(Table 2). 3.3 Restricted cubic spline curves Figure 2 presents restricted cubic spline (RCS) analysis evaluating the dose-response relationship between PLR and COPD. The overall association was highly statistically significant (P-overall < 0.001). The P-value for non-linearity was 0.204, indicating no statistically significant deviation from a linear relationship. This suggests that the association between PLR, modeled as a continuous variable, and COPD risk is consistent with a linear dose-response pattern across the observed PLR range. The analysis supports a significant, linear increase in COPD risk with rising PLR levels. 3.4 Subgroup analysis and interaction effect tests To reduce the influence of confounding factors and evaluate the robustness of the relationship between PLR and COPD prevalence among different groups, in order to identify potential population differences, we conducted multiple-subgroup analysis and interaction tests.The results showed that the relationship between PLR and COPD prevalence remained stable across all the subgroups, which confirmed the stability of the relationship between PLR and COPD prevalence (Table 3). 4 Discussion This large-scale cross-sectional study, leveraging nationally representative NHANES data from 1999–2018, provides novel evidence on the relationship between platelet-to-lymphocyte ratio (PLR) and chronic obstructive pulmonary disease (COPD). Our analysis of 22,679 adults, including 973 individuals with COPD, revealed a significant positive linear association between elevated PLR levels and increased COPD prevalence. This association remained robust across extensive sensitivity and subgroup analyses, suggesting PLR may serve as a clinically relevant biomarker for COPD-related systemic inflammation. The linear relationship identified via restricted cubic splines (RCS) indicates a dose-response pattern: progressive increases in PLR correlate with rising COPD prevalence without evidence of a threshold effect. This aligns mechanistically with PLR's role as a composite marker of systemic inflammation[22,23]. Elevated platelets contribute to inflammatory cascades via cytokine release (e.g., TGF-β, PF4) and interactions with endothelial cells, potentially exacerbating pulmonary tissue damage and airway remodeling in COPD[24-26]. Concomitant lymphopenia—reflected in higher PLR—may signify chronic immune exhaustion or corticosteroid effects, further compromising antimicrobial defenses and tissue repair[27-29]. Our findings extend prior research linking isolated platelet counts or lymphocyte ratios to COPD by demonstrating the prognostic utility of their combined metric, PLR, which integrates both pro-inflammatory and immunosuppressive pathways. While PLR has been studied in acute exacerbations of COPD or respiratory infections, this is among the first investigations to establish its independent association with COPD prevalence in a general adult population[30,31]. Our results corroborate smaller clinical studies suggesting inflammatory biomarkers predict COPD severity. For instance, prior work linked neutrophilia and elevated C-reactive protein (CRP) to COPD pathogenesis[32-35]; PLR may offer complementary value by additionally capturing hematopoietic dysregulation and adaptive immune compromise[36]. Notably, the linear association contrasts with U-shaped relationships observed for some inflammatory markers in other diseases, underscoring PLR’s unique role in COPD’s chronic inflammatory milieu[37,38]. The consistency of our results across age, gender, smoking status, and comorbidity subgroups reinforces PLR’s robustness as a biomarker.Platelet activation promotes pulmonary microthrombosis and releases profibrotic mediators (e.g., serotonin, thromboxane A2), accelerating lung parenchymal destruction(39,40).Lymphocytopenia reflects systemic inflammation-induced apoptosis and margination, impairing pathogen clearance and repair mechanisms[41,42].Clinically, PLR’s accessibility via routine complete blood counts positions it as a pragmatic tool for risk stratification. Elevated PLR could signal subclinical inflammation in high-risk individuals (e.g., smokers), prompting earlier spirometry or preventive interventions. Furthermore, monitoring PLR dynamics might help track therapeutic responses to anti-inflammatory agents (e.g., statins, phosphodiesterase-4 inhibitors) in established COPD. This study benefits from NHANES’s rigorous sampling methodology, standardized laboratory protocols, and extensive covariate data, enhancing generalizability to the US adult population. The large sample size afforded precise effect estimation and detailed subgroup analyses. Nevertheless, limitations warrant consideration: 1.Cross-sectional design precludes causal inference; longitudinal studies are needed to determine if elevated PLR precedes COPD onset. 2.COPD diagnosis relied on spirometry without post-bronchodilator confirmation in all cycles, potentially underestimating prevalence. 3.PLR was measured once; intraindividual variability over time remains unaccounted for. 4.Residual confounding (e.g., unmeasured environmental exposures or genetic factors) cannot be fully excluded despite multivariable adjustment. 5.NHANES lacks detailed pulmonary symptom data, limiting clinical phenotyping. For future research directions, we need to verify the predictive value of PLR for the incidence and progression of COPD. Explore the interaction between PLR and established biomarkers (such as fibrinogen, CRP) to optimize the risk model. To explore the role of PLR in the internal types of COPD (such as eosinophil and neutrophil inflammation). To evaluate whether reducing PLR through antiplatelet drugs or immunomodulators can alleviate the deterioration of COPD. 5 Conclusion This study establishes a significant, linear, and independent association between elevated PLR and COPD prevalence in a nationally representative cohort. PLR integrates dual aspects of inflammation—pro-thrombotic platelet activity and immunosuppressive lymphopenia—offering a holistic biomarker for COPD-related systemic inflammation. While causality requires longitudinal confirmation, our findings suggest PLR could enhance early risk identification and inflammation monitoring in clinical practice. Public health initiatives targeting modifiable PLR drivers (e.g., smoking cessation, metabolic health) may contribute to COPD prevention strategies, ultimately reducing the global burden of this debilitating disease. Abbreviations ALT Alanine aminotransferase AST Aspartate Aminortransferase BMI Body Mass index CDC Centers for Disease Control and Prevention CI Confidence interval COPD Chronicobstructive pulmonary disease CRP C-reactive protein LDL Low Density Lipoprotein NHANES National Health and Nutrition Examination Survey PLR Platelet-to-lymphocyte ratio PIR poverty-to-income ratio TC Total Cos TG Triglyceride Declarations Acknowledgements We sincerely thank the participants and staff of the NHANES for their valuable contributions and to all members who contributed to this work. Author contributions YL, HBG and XC contributed to study conception and design. YL, LC, DFZ,LYZ,XZ, QH, HJP, YH and ZBT organized the data and conducted the analyses.YL, HBG, XC and LC contributed to the interpretation of the results, revision.YL and HBG wrote and edited and finalization of the manuscript. All authors have reviewed and approved the final version of the manuscript. Funding This study was not funded. Availability of data and materials The datasets generated and/or analysed during the current study are available in the [NHANES] repository, [https://wwwn.cdc.gov/nchs/nhanes/Default.aspx]. Ethics approval and consent to participate The NHANES has been approved by the National Center for Health Statistics Ethics Review Board, and all participants were provided informed written consent at enrollment. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Andersson A, Andelid K, Brundin B, Ekberg-Jansson A, Lindén A. No evidence for additional systemic eosinophil mobilization during exacerbations in patients with COPD and chronic bronchitis but no allergy. Front Med (Lausanne). 2025;12:1572291. Pistenmaa CL, Hoffman EA, Prince MR, Hughes E, Dashnaw S, Lo Cascio CM, Oelsner EC, Shen W, Sun Y, Winther H, et al. 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Additional Declarations No competing interests reported. Supplementary Files table1CharacteristicsofthestudyparticipantsaccordingtoPLRindex.xlsx Table1：Characteristics of the study participants according to PLR index table2MultiplelinearassociationanalysisofPLRindexandCOPD.xlsx Table2：Multiple linear association analysis of PLR index and COPD table3SubgroupanalysisandinteractioneffecttestsfortheassociationbetweenPLRandCOPDprevalence.xlsx Table3：Subgroup analysis and interaction effect tests for the association between PLR and COPD prevalence Additionalfile1.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 31 Jul, 2025 Editor invited by journal 02 Jul, 2025 Editor assigned by journal 25 Jun, 2025 Submission checks completed at journal 23 Jun, 2025 First submitted to journal 23 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6906240","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495109307,"identity":"841cec46-8786-4476-8c59-2674ba4f0ad4","order_by":0,"name":"Yuan Luo","email":"","orcid":"","institution":"The First People's Hospital of Neijiang","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Luo","suffix":""},{"id":495109308,"identity":"c16a19e8-f4d4-49e5-b85a-7d65c4537073","order_by":1,"name":"Haibo Gong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYBACfvbm4x8+VNjI8fM3HyBOi2TPsTTGGWfSjCVnHEsgTovBjRwzZt6Ww4kbDuQYEOmyAwlmj3kb0owZDpz5eOMNg52cbgMBHYwNB9IN5+6wkWNs7t1sOYch2djsAAEtzEA9Em+BfmFmOLtNmofhQOI2QlrYgHokeNsOJ7Yx5DwjTgsPGzObJEhLD0MOG3FaJIB6DEGBLCFxzNhyjgERfrG///7jA1BU2p9vfnjjTYWdHEEtaFYSGzVIWkjVMQpGwSgYBSMCAABeCEeTPBplRgAAAABJRU5ErkJggg==","orcid":"","institution":"The First People's Hospital of Neijiang","correspondingAuthor":true,"prefix":"","firstName":"Haibo","middleName":"","lastName":"Gong","suffix":""},{"id":495109309,"identity":"a30dc4f6-86f9-4546-81c4-a748380e1c4f","order_by":2,"name":"Xiao Chen","email":"","orcid":"","institution":"The First People's Hospital of Neijiang","correspondingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Chen","suffix":""},{"id":495109310,"identity":"4223094c-4613-4b4a-af28-0c9d4aef9c92","order_by":3,"name":"Li Chen","email":"","orcid":"","institution":"The First People's Hospital of Neijiang","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Chen","suffix":""},{"id":495109311,"identity":"aa4d9117-2960-44ae-98f9-6d03c6a23f68","order_by":4,"name":"Dingfan Zhou","email":"","orcid":"","institution":"The First People's Hospital of Neijiang","correspondingAuthor":false,"prefix":"","firstName":"Dingfan","middleName":"","lastName":"Zhou","suffix":""},{"id":495109313,"identity":"6694112e-a1c3-4b6c-8807-20bcf7f76495","order_by":5,"name":"Liyue Zhang","email":"","orcid":"","institution":"The First People's Hospital of Neijiang","correspondingAuthor":false,"prefix":"","firstName":"Liyue","middleName":"","lastName":"Zhang","suffix":""},{"id":495109314,"identity":"191d8473-dd61-43c5-befe-79201c845904","order_by":6,"name":"Xiong Zhang","email":"","orcid":"","institution":"The First People's Hospital of Neijiang","correspondingAuthor":false,"prefix":"","firstName":"Xiong","middleName":"","lastName":"Zhang","suffix":""},{"id":495109316,"identity":"390d062a-3a8f-48ff-bea1-257dedc0370e","order_by":7,"name":"Qi Huang","email":"","orcid":"","institution":"The First People's Hospital of Neijiang","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Huang","suffix":""},{"id":495109317,"identity":"0625041e-ec92-4156-9fc1-a45168d42822","order_by":8,"name":"Hongju Peng","email":"","orcid":"","institution":"The Second People's Hospital of Neijiang City","correspondingAuthor":false,"prefix":"","firstName":"Hongju","middleName":"","lastName":"Peng","suffix":""},{"id":495109318,"identity":"fea42ea6-9efd-4f0f-acda-935dfa5ceaa3","order_by":9,"name":"Yi Huang","email":"","orcid":"","institution":"The Second People's Hospital of Neijiang City","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Huang","suffix":""},{"id":495109319,"identity":"6e7e1865-afa9-4b8f-bc72-bb57ba05b3a6","order_by":10,"name":"Zhongbao Tang","email":"","orcid":"","institution":"Shuangcai Central Health Center","correspondingAuthor":false,"prefix":"","firstName":"Zhongbao","middleName":"","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2025-06-16 13:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6906240/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6906240/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88326130,"identity":"25c3c92f-3236-44ae-851f-94372aa94970","added_by":"auto","created_at":"2025-08-05 09:49:33","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":186634,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the selection of patients.\u003c/p\u003e","description":"","filename":"Figure1Flowchartoftheselectionofpatients..tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6906240/v1/e481325d18d4798dd7ec8f16.jpg"},{"id":88326139,"identity":"52cc7b3f-d938-412e-b67f-38661dabb40e","added_by":"auto","created_at":"2025-08-05 09:49:33","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":67981,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic spline analysis illustrating the relationship between PLR and COPD\u003c/p\u003e","description":"","filename":"Figure2RestrictedcubicsplineanalysisillustratingtherelationshipbetweenPLRandCOPD.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6906240/v1/8d2d2074b60e9810878d384f.jpg"},{"id":88327205,"identity":"8f5ddc7c-2fb1-4b28-8616-90a97a599d79","added_by":"auto","created_at":"2025-08-05 09:57:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":883916,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6906240/v1/b49b0655-5976-4f17-90b9-190186d37f09.pdf"},{"id":88326134,"identity":"0c6d0575-ac93-403f-9515-5227eacf25dd","added_by":"auto","created_at":"2025-08-05 09:49:33","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15580,"visible":true,"origin":"","legend":"\u003cp\u003eTable1：Characteristics of the study participants according to PLR index\u003c/p\u003e","description":"","filename":"table1CharacteristicsofthestudyparticipantsaccordingtoPLRindex.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6906240/v1/34b891cd321f9fb72889114d.xlsx"},{"id":88327199,"identity":"3caae2d1-c178-48b9-ac32-ac6e38dfc6bb","added_by":"auto","created_at":"2025-08-05 09:57:33","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11950,"visible":true,"origin":"","legend":"\u003cp\u003eTable2：Multiple linear association analysis of PLR index and COPD\u003c/p\u003e","description":"","filename":"table2MultiplelinearassociationanalysisofPLRindexandCOPD.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6906240/v1/992fd9d6dcd9f895e1d2d007.xlsx"},{"id":88326142,"identity":"3726c28b-234d-4669-98b7-266ff39877e2","added_by":"auto","created_at":"2025-08-05 09:49:33","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13149,"visible":true,"origin":"","legend":"\u003cp\u003eTable3：Subgroup analysis and interaction effect tests for the association between PLR and COPD prevalence\u003c/p\u003e","description":"","filename":"table3SubgroupanalysisandinteractioneffecttestsfortheassociationbetweenPLRandCOPDprevalence.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6906240/v1/d9a37dcf00058babb1328c3c.xlsx"},{"id":88327203,"identity":"a42f6de0-d575-47aa-a865-5062760d0d3b","added_by":"auto","created_at":"2025-08-05 09:57:33","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":10644,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6906240/v1/25d25e4fcc077c8bab7ed74b.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between platelet-to-lymphocyte ratio and chronic obstructive pulmonary disease：findings based on NHANES 1999–2018","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eChronic obstructive pulmonary disease (COPD) remains a leading cause of global morbidity and mortality, affecting over 300 million people worldwide and contributing significantly to healthcare burdens[1,2].As a complex inflammatory airway disorder, COPD is characterized by persistent respiratory symptoms and progressive airflow limitation, predominantly driven by chronic inflammation and oxidative stress[3-5]. Despite established clinical biomarkers such as C-reactive protein (CRP) and white blood cell count (WBC), there is growing interest in identifying readily accessible, cost-effective inflammatory indicators to enhance risk stratification and pathophysiological understanding[6-8].\u003c/p\u003e\n\u003cp\u003eThe platelet-to-lymphocyte ratio (PLR), an integrative hematological index derived from routine complete blood counts, has emerged as a novel biomarker reflecting systemic inflammation and immune activation[9-11]. Elevated PLR has been independently associated with adverse outcomes in cardiovascular diseases, malignancies, and other chronic inflammatory conditions, owing to its dual representation of thrombotic activity (via platelets) and immune regulation (via lymphocytes)[12-15]. However, evidence regarding its relationship with COPD prevalence and severity remains limited and inconsistent, with most prior studies constrained by single-center designs, small sample sizes, or restricted demographic coverage.\u003c/p\u003e\n\u003cp\u003eLeveraging the National Health and Nutrition Examination Survey (NHANES) 1999–2018—a nationally representative database with standardized protocols—this study aims to comprehensively investigate the association between PLR and COPD in a large, multi-ethnic adult population. We hypothesize that elevated PLR is independently associated with increased COPD prevalence and may serve as an accessible indicator of chronic inflammatory burden in these patients. \u0026nbsp;Our analysis further explores potential nonlinear relationships and subgroup variations, addressing critical gaps in existing literature while providing epidemiological insights derived from high-quality, population-level data.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study design and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is a cross-sectional study, and the database is from NHANES. NHANES is a comprehensive survey aimed at collecting data on the health status of the US population. NHANES adopted a stratified multi-stage random sampling method, ensuring the representativeness of the national sample[16]. NHANES was approved by the Ethics Review Committee of the National Center for Health Statistics, and each participant provided informed consent by signing an agreement[17]. These datasets contain complete files and protocols, which are publicly available on the NHANES website and are consistent with the laboratory technicians and anthropometric procedures in our previous research[18].\u003c/p\u003e\n\u003cp\u003eWe screened and analyzed the data from 1999 to 2018. To ensure the integrity and reliability of the results, specific exclusion criteria were applied, including (1) individuals under 20 years old (n=46235); (2) There is no PLR index (n=5459); (3) Individuals lacking COPD (n=3); (4) The data of Cancer, LDL, TC and TG are incomplete. A total of 22,679 subjects were enrolled in our study (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Chronic obstructive pulmonary disease(COPD) definition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, COPD diagnosis was primarily ascertained based on self-reported medical history. Utilizing questionnaire data from the NHANES database, participants were classified as having COPD if they responded \"YES\" to either of the following items: \"Has a doctor or other health professional ever told you that you have emphysema?\" or \"Has a doctor or other health professional ever told you that you have chronic bronchitis?\" [19].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Platelet-to-lymphocyte ratio(PLR) assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePLR (platelet-to-lymphocyte ratio) was calculated from complete blood count (CBC) data obtained during NHANES physical examinations. Blood specimens were processed, stored, and shipped to designated laboratories at the National Center for Environmental Health and Centers for Disease Control and Prevention (CDC) for analysis. Certified CDC laboratory technicians performed all procedures following standardized protocols. PLR was derived by dividing absolute platelet count by absolute lymphocyte count. The accuracy and reliability of these measurements were ensured through rigorous NHANES quality control procedures [20].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Covariate variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe covariates assessed in this study comprised: gender (male, female), age (years), race/ethnicity (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Other Race), education level (\u0026lt; high school, high school or equivalent, \u0026gt; high school), marital status (married/cohabiting, widowed/divorced/separated, never married), family poverty income ratio (PIR), body mass index (BMI; \u0026nbsp;kg/m²), smoking status (never smoker: \u0026lt;100 lifetime cigarettes; \u0026nbsp; former smoker:\u0026nbsp;≥100 lifetime cigarettes, not current; \u0026nbsp; current smoker:\u0026nbsp;≥100 lifetime cigarettes, currently smoking), alcohol consumption (current drinker: \u0026gt;12 drinks/year; \u0026nbsp; never drinker; \u0026nbsp;unknown), hypertension (defined as average systolic blood pressure\u0026nbsp;≥140 mmHg, and/or diastolic blood pressure\u0026nbsp;≥90 mmHg, self-reported diagnosis, or use of antihypertensive medication [21]), diabetes mellitus (defined as fasting blood glucose\u0026nbsp;≥7.0 mmol/L [≥126 mg/dL], glycated hemoglobin (HbA1c) \u0026gt;6.5%, self-reported diagnosis, or use of hypoglycemic agents/insulin), cancer (self-reported physician-diagnosed cancer; \u0026nbsp;MCQ220), stroke (self-reported physician-diagnosed stroke; \u0026nbsp;MCQ160f), and heart disease (self-reported physician-diagnosed heart failure [MCQ160b], coronary heart disease [MCQ160c], angina [MCQ160d], or myocardial infarction [MCQ160e]). \u0026nbsp;Laboratory variables included aspartate aminotransferase (AST; \u0026nbsp; U/L), alanine aminotransferase (ALT; \u0026nbsp; U/L), triglycerides (TG; \u0026nbsp;mg/dL), total cholesterol (TC; \u0026nbsp;mg/dL), and low-density lipoprotein cholesterol (LDL-C; \u0026nbsp; mg/dL).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses accounted for NHANES's complex survey design using CDC-recommended sampling weights per National Center for Health Statistics (NCHS) guidelines. \u0026nbsp; \u0026nbsp;Weighted chi-square tests analyzed categorical variables, while continuous variables were assessed via weighted one-way ANOVA. \u0026nbsp; \u0026nbsp;The PLR-COPD relationship was evaluated through multivariable linear regression across three hierarchical models: Model 1 (unadjusted); \u0026nbsp; \u0026nbsp; Model 2 (adjusted for sex, age, and race); \u0026nbsp; \u0026nbsp;Model 3 (additionally adjusted for marital status, education level, BMI, poverty-income ratio, smoking status, alcohol consumption, hypertension, diabetes, heart disease, stroke, cancer, ALT, AST, total cholesterol, triglycerides, and LDL). \u0026nbsp; \u0026nbsp; Stratified analyses examined subgroups by sex (male/female), race/ethnicity (White/Black/Mexican American/other), alcohol intake (≥12/\u0026lt;12 drinks/year, unknown), smoking status (never/former/current), hypertension, diabetes, cancer, stroke, and heart disease. \u0026nbsp; \u0026nbsp; Nonlinear relationships were investigated using smooth curve fitting, with threshold effects analyzed via two-piecewise linear regression. \u0026nbsp; \u0026nbsp;All analyses were performed using R v4.1.3 with EmpowerStats, with statistical significance defined as two-tailed P \u0026lt; 0.05.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Baseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 22,679 participants (mean age 49.88 ± 18.16 years; \u0026nbsp;47.87% male) stratified by platelet-to-lymphocyte ratio (PLR) quartiles (Q1-Q4). \u0026nbsp;As detailed in Table 1, the highest PLR quartile (Q4) demonstrated significantly higher proportions of females (P \u0026lt; 0.05), Non-Hispanic White individuals (P \u0026lt; 0.05), and participants with advanced education (P \u0026lt; 0.05). \u0026nbsp; Conversely, the lowest quartile (Q1) was associated with lower poverty-income ratios and higher body mass index values. \u0026nbsp;Participants with diabetes, hypertension, heart disease, and COPD were predominantly distributed in lower PLR quartiles, with COPD patients exhibiting significantly reduced PLR values compared to non-COPD counterparts (P \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Relationship between PLR and CODP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this multiple linear regression analysis examining the association between platelet-to-lymphocyte ratio (PLR) and chronic obstructive pulmonary disease (COPD), continuous PLR per standard deviation increase showed a significant positive association across all models. \u0026nbsp; Specifically, in the unadjusted Model 1, the β coefficient was 1.003 (95% CI: 1.002–1.004, p\u0026lt;0.00001), which attenuated but remained significant in Model 2 after adjusting for gender, age, and race (β=1.001, 95% CI: 1.000–1.002, p=0.026), and in the fully adjusted Model 3 (β=1.002, 95% CI: 1.001–1.003, p\u0026lt;0.0001). \u0026nbsp;For categorical PLR quartiles, with Q1 as the reference, Q4 demonstrated significantly elevated risk in Model 1 (β=1.216, 95% CI: 1.022–1.446, p=0.027) and Model 3 (β=1.249, 95% CI: 1.036–1.506, p=0.020), but not in Model 2 (β=1.018, 95% CI: 0.850–1.218, p=0.850). \u0026nbsp; Q2 and Q3 showed no significant associations. Strong linear trends were observed for all models (p\u0026lt;0.00001 for Model 1, p=0.026 for Model 2, and p\u0026lt;0.0001 for Model 3)(Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Restricted cubic spline curves\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 2 presents restricted cubic spline (RCS) analysis evaluating the dose-response relationship between PLR and COPD. The overall association was highly statistically significant (P-overall \u0026lt; 0.001). The P-value for non-linearity was 0.204, indicating no statistically significant deviation from a linear relationship. This suggests that the association between PLR, modeled as a continuous variable, and COPD risk is consistent with a linear dose-response pattern across the observed PLR range. The analysis supports a significant, linear increase in COPD risk with rising PLR levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Subgroup analysis and interaction effect tests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo reduce the influence of confounding factors and evaluate the robustness of the relationship between PLR and COPD prevalence among different groups, in order to identify potential population differences, we conducted multiple-subgroup analysis and interaction tests.The results showed that the relationship between PLR and COPD prevalence remained stable across all the subgroups, which confirmed the stability of the relationship between PLR and COPD prevalence (Table 3).\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis large-scale cross-sectional study, leveraging nationally representative NHANES data from 1999–2018, provides novel evidence on the relationship between platelet-to-lymphocyte ratio (PLR) and chronic obstructive pulmonary disease (COPD). Our analysis of 22,679 adults, including 973 individuals with COPD, revealed a significant positive linear association between elevated PLR levels and increased COPD prevalence. This association remained robust across extensive sensitivity and subgroup analyses, suggesting PLR may serve as a clinically relevant biomarker for COPD-related systemic inflammation.\u003c/p\u003e\n\u003cp\u003eThe linear relationship identified via restricted cubic splines (RCS) indicates a dose-response pattern: progressive increases in PLR correlate with rising COPD prevalence without evidence of a threshold effect. \u0026nbsp;This aligns mechanistically with PLR's role as a composite marker of systemic inflammation[22,23]. \u0026nbsp;Elevated platelets contribute to inflammatory cascades via cytokine release (e.g., TGF-β, PF4) and interactions with endothelial cells, potentially exacerbating pulmonary tissue damage and airway remodeling in COPD[24-26]. Concomitant lymphopenia—reflected in higher PLR—may signify chronic immune exhaustion or corticosteroid effects, further compromising antimicrobial defenses and tissue repair[27-29]. \u0026nbsp;Our findings extend prior research linking isolated platelet counts or lymphocyte ratios to COPD by demonstrating the prognostic utility of their combined metric, PLR, which integrates both pro-inflammatory and immunosuppressive pathways.\u003c/p\u003e\n\u003cp\u003eWhile PLR has been studied in acute exacerbations of COPD or respiratory infections, this is among the first investigations to establish its independent association with COPD prevalence in a general adult population[30,31]. \u0026nbsp;Our results corroborate smaller clinical studies suggesting inflammatory biomarkers predict COPD severity. \u0026nbsp;For instance, prior work linked neutrophilia and elevated C-reactive protein (CRP) to COPD pathogenesis[32-35]; \u0026nbsp;PLR may offer complementary value by additionally capturing hematopoietic dysregulation and adaptive immune compromise[36]. \u0026nbsp;Notably, the linear association contrasts with U-shaped relationships observed for some inflammatory markers in other diseases, underscoring PLR’s unique role in COPD’s chronic inflammatory milieu[37,38]. \u0026nbsp; The consistency of our results across age, gender, smoking status, and comorbidity subgroups reinforces PLR’s robustness as a biomarker.Platelet activation promotes pulmonary microthrombosis and releases profibrotic mediators (e.g., serotonin, thromboxane A2), accelerating lung parenchymal destruction(39,40).Lymphocytopenia reflects systemic inflammation-induced apoptosis and margination, impairing pathogen clearance and repair mechanisms[41,42].Clinically, PLR’s accessibility via routine complete blood counts positions it as a pragmatic tool for risk stratification. Elevated PLR could signal subclinical inflammation in high-risk individuals (e.g., smokers), prompting earlier spirometry or preventive interventions. Furthermore, monitoring PLR dynamics might help track therapeutic responses to anti-inflammatory agents (e.g., statins, phosphodiesterase-4 inhibitors) in established COPD.\u003c/p\u003e\n\u003cp\u003eThis study benefits from NHANES’s rigorous sampling methodology, standardized laboratory protocols, and extensive covariate data, enhancing generalizability to the US adult population. \u0026nbsp;The large sample size afforded precise effect estimation and detailed subgroup analyses. \u0026nbsp;Nevertheless, limitations warrant consideration: 1.Cross-sectional design precludes causal inference; \u0026nbsp;longitudinal studies are needed to determine if elevated PLR precedes COPD onset. 2.COPD diagnosis relied on spirometry without post-bronchodilator confirmation in all cycles, potentially underestimating prevalence. 3.PLR was measured once; \u0026nbsp;intraindividual variability over time remains unaccounted for. 4.Residual confounding (e.g., unmeasured environmental exposures or genetic factors) cannot be fully excluded despite multivariable adjustment. 5.NHANES lacks detailed pulmonary symptom data, limiting clinical phenotyping.\u003c/p\u003e\n\u003cp\u003eFor future research directions, we need to verify the predictive value of PLR for the incidence and progression of COPD. Explore the interaction between PLR and established biomarkers (such as fibrinogen, CRP) to optimize the risk model. To explore the role of PLR in the internal types of COPD (such as eosinophil and neutrophil inflammation). To evaluate whether reducing PLR through antiplatelet drugs or immunomodulators can alleviate the deterioration of COPD.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study establishes a significant, linear, and independent association between elevated PLR and COPD prevalence in a nationally representative cohort. PLR integrates dual aspects of inflammation\u0026mdash;pro-thrombotic platelet activity and immunosuppressive lymphopenia\u0026mdash;offering a holistic biomarker for COPD-related systemic inflammation. While causality requires longitudinal confirmation, our findings suggest PLR could enhance early risk identification and inflammation monitoring in clinical practice. Public health initiatives targeting modifiable PLR drivers (e.g., smoking cessation, metabolic health) may contribute to COPD prevention strategies, ultimately reducing the global burden of this debilitating disease.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eALT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAlanine aminotransferase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAST\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAspartate Aminortransferase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody Mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCDC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCenters for Disease Control and Prevention\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCOPD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eChronicobstructive pulmonary disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eC-reactive protein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLDL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLow Density Lipoprotein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNHANES\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNational Health and Nutrition Examination Survey\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePlatelet-to-lymphocyte ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePIR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epoverty-to-income ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTotal Cos\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTriglyceride\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank the participants and staff of the NHANES for their valuable contributions and to all members who contributed to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYL, HBG and XC contributed to study conception and design. YL, LC, DFZ,LYZ,XZ, QH, HJP, YH and ZBT organized the data and conducted the analyses.YL, HBG, XC and LC contributed to the interpretation of the results, revision.YL and HBG wrote and edited and finalization of the manuscript. \u0026nbsp;All authors have reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was not funded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available in the [NHANES] repository, [https://wwwn.cdc.gov/nchs/nhanes/Default.aspx].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe NHANES has been approved by the National Center for Health Statistics Ethics Review Board, and all participants were provided informed written consent at enrollment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAndersson A, Andelid K, Brundin B, Ekberg-Jansson A, Lind\u0026eacute;n A. 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The Analysis of Neutrophil to Lymphocyte Ratio (NLR), Lymphocyte to Monocyte Ratio (LMR), and Platelet to Lymphocyte Ratio (PLR) in Patients with Adenoidectomy and Tonsillectomy. \u003cem\u003eJ Clin Med.\u003c/em\u003e2024;13:5457. \u003c/li\u003e\n\u003cli\u003eXie X, Fu X, Zhang Y, Huang W, Huang L, Deng Y, Yan D, Yao R, Li N. U-shaped relationship between platelet-lymphocyte ratio and postoperative in-hospital mortality in patients with type A acute aortic dissection. \u003cem\u003eBMC Cardiovasc Disord.\u003c/em\u003e2021;21:569.\u003c/li\u003e\n\u003cli\u003eYan C, Zhang W, Xiao Y, Sun Y, Peng X, Cai W. The predictive role of the platelet-to-lymphocyte ratio for the risk of non-alcoholic fatty liver disease and cirrhosis: a nationwide cross-sectional study. \u003cem\u003eFront Endocrinol (Lausanne).\u003c/em\u003e2024;15:1376894. \u003c/li\u003e\n\u003cli\u003eAlkarithi G, Duval C, McPherson HR, Stewart L, De Simone I, Macrae FL, Ari\u0026euml;ns RAS. Fibrin film on clots is increased by hematocrit but reduced by inflammation: implications for platelets and fibrinolysis. \u003cem\u003eJ Thromb Haemost.\u003c/em\u003e2025; 23:1247\u0026ndash;1259. \u003c/li\u003e\n\u003cli\u003eOkabe R, Chen-Yoshikawa TF, Yoshizawa A, Nakajima N, Saito M, Hamaji M, Date H. Association Between Pretransplant Serum Carcinoembryonic Antigen Levels and Immunohistochemical Staining of Explanted Native Lungs in Patients Who Underwent Lung Transplantation. \u003cem\u003eSemin Thorac Cardiovasc Surg.\u003c/em\u003e2021;33:608\u0026ndash;615. \u003c/li\u003e\n\u003cli\u003eDomagała-Kulawik J, Kwiecień I, Bielicki P, Skirecki T. Fas-positive lymphocytes are associated with systemic inflammation in obstructive sleep apnea syndrome. \u003cem\u003eSleep Breath.\u003c/em\u003e2019;23:673\u0026ndash;678. \u003c/li\u003e\n\u003cli\u003eWang X, Balaji S, Steen EH, Li H, Rae MM, Blum AJ, Miao Q, Butte MJ, Bollyky PL, Keswani SG. T Lymphocytes Attenuate Dermal Scarring by Regulating Inflammation, Neovascularization, and Extracellular Matrix Remodeling. \u003cem\u003eAdv Wound Care (New Rochelle).\u003c/em\u003e2019;8:527\u0026ndash;537.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"platelet-lymphocyte ratio, chronic obstructive pulmonary disease, NHANES, cross-sectional study, population-based study","lastPublishedDoi":"10.21203/rs.3.rs-6906240/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6906240/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003eThe platelet-lymphocyte ratio (PLR) is one of the recognized indicators of systemic inflammation. Currently, there are no studies on the relationship between this individual indicator of PLR and chronic obstructive pulmonary disease. This study aims to clarify the relationship between the inflammatory response indicator platelet-lymphocyte ratio (PLR) and chronic obstructive pulmonary disease in the adult population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod:\u003c/strong\u003e Adults with chronic obstructive pulmonary disease who were included in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 are the subjects of the current cross-sectional survey. The relationship between PLR and the prevalence of COPD was analyzed using the generalized linear model. Then visualize the relationship between them using restricted cubic splines (RCS). Subgroup analysis was conducted to evaluate the robustness of the relationship between the PLR index and the prevalence of COPD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult:\u003c/strong\u003e This study included a total of 22,679 subjects, of whom 973 were diagnosed as having COPD. The restricted cubic spline (RCS) curve demonstrated a linear relationship between the PLR index and COPD prevalence. A positive association was observed between the PLR index and COPD (β = 1.002, 95% CI: 1.001–1.003, P \u0026lt; 0.001). Subgroup analyses and interaction tests confirmed the robustness of this relationship, which remained consistent across most subgroups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study found that there is a linear relationship between the PLR index and the prevalence of COPD, which has an impact on public health. The control of PLR inflammatory indicators plays a key role in reducing the occurrence of COPD and improving long-term health outcomes.\u003c/p\u003e","manuscriptTitle":"Association between platelet-to-lymphocyte ratio and chronic obstructive pulmonary disease：findings based on NHANES 1999–2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-05 09:49:28","doi":"10.21203/rs.3.rs-6906240/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-07-31T08:50:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-02T10:17:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-25T17:09:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T13:33:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2025-06-23T13:30:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e5ab015e-37da-472a-a5f3-26e86e83f49f","owner":[],"postedDate":"August 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-05T09:49:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-05 09:49:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6906240","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6906240","identity":"rs-6906240","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}