The association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and bone mineral density in US adults: NHANES (2011-2018)

The association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and bone mineral density in US adults: NHANES (2011-2018) | 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 The association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and bone mineral density in US adults: NHANES (2011-2018) Zhengyu Sun, Yong Yue, Pengcheng Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4969279/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) represents a novel lipid marker. This study investigated the association between NHHR and lumbar bone mineral density (BMD) in the general American population. Methods Data from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2018 were used in this study, including 10,879 participants aged 20–59 years. To investigate the relationship between NHHR and lumbar BMD, we employed multivariate linear regression models along with stratified analyses. Additionally, we applied fitted smoothing curves and threshold effect analyses to explore the nonlinear association between NHHR and lumbar BMD. Results After adjusting for covariates, weighted multivariable linear regression models indicated a significant negative association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and lumbar bone mineral density (BMD) (β = -0.006, 95% CI: -0.008 to -0.003, P < 0.001). Stratified subgroup analyses based on age, gender, race, BMI, hypertension, and diabetes consistently demonstrated this inverse relationship in males (β = -0.005, 95% CI: -0.008 to -0.002, P = 0.002) and females (β = -0.007, 95% CI: -0.011 to -0.003, P < 0.001); non-Hispanic whites (β = -0.005, 95% CI: -0.009 to -0.001, P = 0.015), non-Hispanic blacks (β = -0.010, 95% CI: -0.017 to -0.004, P = 0.003), and other races (β = -0.007, 95% CI: -0.011 to -0.003, P = 0.001); participants aged 20–29 years (β = -0.006, 95% CI: -0.011 to -0.001, P = 0.022) and 40–49 years (β = -0.008, 95% CI: -0.013 to -0.003, P < 0.001); individuals with a BMI < 25 (β = -0.008, 95% CI: -0.014 to -0.002, P = 0.010) and those with a BMI between 25 and 30 (β = -0.011, 95% CI: -0.015 to -0.007, P < 0.001). For the total cohort, individuals of other races, and participants aged 30–39 years, a nonlinear relationship was examined with inflection points identified at NHHR values of 4.29, 5.26, and 2.91, respectively. Conclusions For US adults aged 20 to 59, our research identified an inverse relationship between the NHHR and lumbar BMD. This association was observed across the general cohort, individuals of other races, and participants aged 30–39 years, demonstrating a nonlinear relationship with inflection points at 4.29, 5.26, and 2.91, respectively. Consequently, NHHR could serve as a sensitive biomarker for the prevention of osteoporosis or osteopenia. NHANE Lumbar BMD Osteoporosis NHHR Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Osteoporosis has become a significant public health issue driven by the aging global population. This pervasive metabolic bone disease is characterized by reduced bone mineral density (BMD) and structural degeneration, which heightens the risk of fractures [ 1 , 2 ]. The International Osteoporosis Foundation reports that over 30% of women and 20% of men over 50 years old suffer from osteoporosis or osteopenia, placing them at substantial fracture risk [ 3 ]. The reduction in BMD is a crucial diagnostic criterion for osteoporosis, with early detection and prevention of bone mass loss being key to mitigating osteoporotic fractures, particularly in cases of senile and postmenopausal osteoporosis [ 4 , 5 ]. Various factors, including advanced age, female sex, genetic predisposition, and lipid metabolism abnormalities, contribute to the development of osteoporosis [ 6 , 7 ]. Therefore, effective management thus necessitates early identification and modulation of risk factors such as diet, environmental influences, and lifestyle choices to curb bone mass loss and enhance patient outcomes [ 8 , 9 ]. Emerging evidence underscores the intricate involvement of lipid metabolism in the pathogenesis of both osteoporosis and cardiovascular disease, with dyslipidemia potentially serving as a predictor for osteoporosis [ 10 , 11 ]. Low-density lipoprotein cholesterol (LDL-C), a recognized risk factor for cardiovascular disease due to its role in atherosclerotic plaque formation [ 12 ], exhibits a negative association with osteoporosis [ 13 ]. Metabolic disorders of total cholesterol (TC) and triglycerides (TG), primary contributors to atherosclerosis, often coincide with osteoporosis in the elderly, indicating a link between cholesterol, triglycerides, and BMD [ 14 ]. Research has increasingly focused on high-density lipoprotein cholesterol (HDL-C) and its relationship with BMD, though findings remain inconsistent. Some studies report a positive correlation between HDL-C levels and BMD, particularly in postmenopausal women [ 15 ], while others indicate negative correlations or no association at all [ 16 , 17 ]. Recently, the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) has emerged as a novel, comprehensive indicator, offering a new framework for understanding and developing therapies. Investigating the relationship between NHHR levels and BMD could reveal its potential as a predictive marker for osteoporosis. However, the relationship between the NHHR and lumbar BMD is poorly known. Therefore, this study aims to assess the relationship between NHHR and BMD in adults using data from the National Health and Nutrition Examination Survey (NHANES) 2011–2018. We hypothesize that NHHR is negatively associated with lumbar BMD. Materials and methods Data source and study population The National Health and Nutrition Examination Survey (NHANES) is a pivotal program in the United States that provides objective health statistics and addresses emerging public health issues. The survey methodologies were approved by the Institutional Review Board of the National Center for Health Statistics, with informed consent obtained from all participants [ 18 ]. Our analysis utilized data from 2011 to 2018, spanning four NHANES cycles and including a total of 39,156 participants. The exclusion criteria were as follows: (1) participants younger than 20 years or older than 59 years (n = 24,222), (2) individuals with missing NHHR (n = 1,427) and BMD data (n = 2,483), and (3) those with incomplete covariate data (n = 145). Consequently, our final analysis included 10,879 participants (Fig. 1). Assessment of NHHR In this study, the non-HDL-C to HDL-C ratio (NHHR) was utilized as the exposure variable. NHHR is defined as the ratio of non-HDL-C to HDL-C. Non-HDL-C is determined by subtracting HDL-C from TC using blood samples obtained from fasting individuals [ 19 , 20 ]. Enzymatic testing to assess TC and HDL-C levels was conducted with an automated biochemical analyzer. BMD measurements Total lumbar BMD served as the outcome variable in this analysis, calculated as the mean of measurements from the first to the fourth lumbar vertebra. Dual-energy X-ray absorptiometry is a widely utilized technology for evaluating BMD due to its efficiency, simplicity, and minimal radiation exposure [ 21 ]. Dual-energy X-ray absorptiometry was performed using a Hologic QDR 4500A device and Apex software version 3.2 by qualified radiology technologists to assess lumbar BMD. Covariates definitions The multivariate models accounted for variables that could potentially confound the association between NHHR and lumbar BMD. The analysis included the following covariates: age, race, educational attainment, marital status, smoking history, alcohol consumption, moderate physical activity, hypertension, diabetes, ratio of family income to poverty (PIR), body mass index (BMI), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum calcium, serum phosphorus, total protein, blood urea nitrogen, serum uric acid, TC, HDL-C, TG, and LDL-C. To mitigate sample size bias, the original NHANES categories "other Hispanic" and "other multiracial race" were consolidated into the variable "other race." Smoking, alcohol consumption, moderate physical activity, hypertension, and diabetes were assessed using questionnaires with the following questions: "Have you smoked at least 100 cigarettes in your lifetime?", "Have you ever consumed 4/5 or more drinks daily?", "Does moderate-intensity activity cause slight increases in breathing or heart rate?", "Has a doctor ever diagnosed you with diabetes?", and "Has a doctor ever diagnosed you with high blood pressure?" Detailed information on these covariates is available on the NHANES website ( https://www.cdc.gov/nchs/nhanes/ ). Statistical analysis All assessments incorporated NHANES sampling weights. Continuous variables were expressed as mean ± standard deviation, while categorical variables were represented as percentages. Participants were stratified into quartiles based on NHHR levels. To compare participant characteristics, weighted Student's t-tests were utilized for continuous variables, and weighted chi-square tests were applied for categorical variables. The relationship between NHHR and lumbar BMD was explored using weighted multivariate linear regression analyses across three models: Model 1 was unadjusted, Model 2 adjusted for age, gender, and race, and Model 3 further adjusted for educational level, marital status, smoking, alcohol consumption, moderate physical activity, hypertension, diabetes, PIR, BMI, ALT, AST, serum calcium, serum phosphorus, total protein, blood urea nitrogen, and serum uric acid. Subgroup analysis was performed using stratified multivariate regression analysis. Nonlinear associations were assessed with weighted smooth curve fitting and threshold effect analysis, employing a two-piecewise linear regression model to identify inflection points. All statistical analyses were conducted using R ( http://www.R-project.org , The R Foundation) and EmpowerStats software ( http://www.empowerstats.com , X&Y Solutions, Inc., Boston, MA), with a significance level set at P < 0.05. Results Participants characteristics Participants were divided into quartiles based on NHHR levels (Q1: 0.36–1.92; Q2: 1.93–2.68; Q3: 2.69–3.67; Q4: 3.68–26.85), as outlined in Table 1. This study included 10,879 individuals aged 20 to 59 years, with a mean age of 39.49 ± 11.70 years. The cohort was composed of 52.04% males and 47.93% females, with 61.55% identified as non-Hispanic white. Educational attainment was predominantly above high school (65.31%), and the majority were married (62.32%). The prevalence rates for smoking, alcohol consumption, hypertension, and diabetes were 41.30%, 15.70%, 22.62%, and 5.83%, respectively. Notable differences in baseline characteristics emerged across the NHHR quartiles. Participants in the highest NHHR quartile were more likely to be male, non-Hispanic white, and exhibited higher BMI, ALT, AST, total protein, serum uric acid, TC, TG, and LDL-C, alongside lower PIR, HDL-C, and lumbar BMD compared to those in the lower quartiles. Association between NHHR and BMD The results of the multivariate regression analysis are presented in Table 2. In Model 1, which included no covariate adjustments, lumbar BMD exhibited a negative correlation with NHHR (β = -0.009, 95% CI: -0.011 to -0.007, P < 0.001). This inverse relationship persisted after controlling for confounders in both Model 2 (β = -0.006, 95% CI: -0.008 to -0.004, P < 0.001) and Model 3 (β = -0.006, 95% CI: -0.008 to -0.003, P < 0.001). In the fully adjusted Model 3, participants in the highest NHHR quartile had a lumbar BMD that was 0.034 g/cm² lower compared to those in the lowest quartile, following the conversion of NHHR from a continuous variable to quartiles. Subgroup analysis Subgroup analyses stratified by age, gender, race, BMI, hypertension, and diabetes are presented in Table 2. In Model 3, the adverse association between NHHR and lumbar BMD remained significant in both males (β = -0.005, 95% CI: -0.008 to -0.002, P = 0.002) and females (β = -0.007, 95% CI: -0.011 to -0.003, P < 0.001). This negative relationship was also evident across racial groups, including non-Hispanic whites (β = -0.005, 95% CI: -0.009 to -0.001, P = 0.015), non-Hispanic blacks (β = -0.010, 95% CI: -0.017 to -0.004, P = 0.003), and other races (β = -0.007, 95% CI: -0.011 to -0.003, P = 0.001), but was not observed in Mexican Americans. Age-stratified results revealed a significant negative relationship between NHHR and lumbar BMD in participants aged 20–29 years (β = -0.006, 95% CI: -0.011 to -0.001, P = 0.022) and 40–49 years (β = -0.008, 95% CI: -0.013 to -0.003, P < 0.001). Among the BMI groups, a significant negative correlation was found in individuals with a BMI < 25 (β = -0.008, 95% CI: -0.014 to -0.002, P = 0.010) and those with a BMI between 25 and 30 (β = -0.011, 95% CI: -0.015 to -0.007, P < 0.001). A nonlinear correlation between NHHR and BMD Figures 2, 3, 4, and 5 illustrate the smooth curve fits and generalized additive models used to characterize the nonlinear relationship between NHHR and lumbar BMD. Utilizing a two-piecewise linear regression model, the association between NHHR and lumbar BMD was found to be nonlinear, with an inflection point at 4.29 (Table 3). Among participants from other racial groups, this association exhibited a reverse-L curve, with an inflection point at 5.26 (Table 4). Similarly, in participants aged 30–39 years, the relationship between NHHR and lumbar BMD also followed a reverse-L curve, with an inflection point at 2.91 (Table 5). Discussion In this study, we utilized the latest representative data from NHANES (2011–2018) to evaluate the associations between NHHR and BMD. Our multivariate linear regression analyses revealed a negative correlation between NHHR and lumbar BMD. Curve fitting and threshold effect analyses indicated a nonlinear relationship between the variables, with an inflection point at 4.29. Specifically, in the other race group and participants aged 30–39 years, we identified a nonlinear relationship between NHHR and lumbar BMD, with inflection points at 5.26 and 2.91, respectively. Emerging research underscores the intricate relationship between lipid profiles and BMD, elucidating the differential effects of various lipid components on bone health through distinct cellular and molecular mechanisms [ 14 , 22 , 23 ]. In a cross-sectional study, elevated levels of LDL-C were positively associated with osteoporosis and low bone mass in elderly females [ 24 ]. This finding is corroborated by other studies, which demonstrate that LDL-C exerts a negative impact on lumbar spine BMD in postmenopausal women, particularly when LDL-C levels are below 3.52 mmol/L [ 22 ]. Mechanistically, LDL-C and its oxidized form, ox-LDL, impair osteoblast function and promote osteoclast activity, resulting in increased bone resorption and decreased bone mass [ 25 , 26 ]. This deleterious process is mediated through oxidative stress and inflammation, as LDL-C induces the production of reactive oxygen species (ROS) and pro-inflammatory cytokines such as TNF-α, IL-6, and IL-1β, which in turn damage bone cells and the extracellular matrix [ 27 , 28 ]. Similarly, elevated cholesterol levels have been associated with lower BMD or osteoporosis in multiple studies [ 29 , 30 ]. For instance, Fang et al. reported a negative correlation between serum TC and lumbar spine BMD after adjusting for confounders [ 31 ]. High TC levels contribute to systemic inflammation and oxidative stress, which disrupt bone metabolism by favoring resorption over formation [ 32 ]. Additionally, a nationwide cross-sectional study found that elevated TG levels were inversely associated with whole-body BMD in both men and women, with a relationship potentially modulated by vitamin D status among older adults [ 33 ]. HDL-C, traditionally recognized for its cardiovascular benefits, also appears to support bone health [ 34 , 35 ]. A study by Zolfaroli et al. found that HDL-C positively impacts BMD of the lumbar spine and femoral neck in postmenopausal women [ 15 ]. HDL-C exhibits antioxidant properties that mitigate oxidative stress, thereby reducing ROS levels and protecting osteoblasts from oxidative damage [ 36 ]. Furthermore, HDL-C inhibits the expression of RANKL, decreasing osteoclastogenesis and promoting bone formation [ 37 ]. However, some studies report negative correlations or no association between HDL-C and BMD, indicating that the mechanisms through which HDL-C influences bone density may be complex. For example, a large sample survey found a negative correlation between HDL-C levels and total BMD in male adolescents aged 12 to 19 [ 38 ]. Similarly, two studies from China identified an inverse relationship between HDL-C levels and BMD, suggesting a potential adverse impact on bone density [ 39 , 40 ]. Conversely, other studies have found no association between HDL-C levels and osteoporosis across various locations [ 16 ]. These discrepancies likely arise from differences in study design, population characteristics, and confounding factors such as age, sex, and comorbidities. The heterogeneity in study outcomes highlights the need for comprehensive research to clarify the pathways through which cholesterol influences bone density. Personalized approaches to osteoporosis prevention and treatment, tailored to individual lipid profiles and demographic characteristics, may offer the most effective strategies for mitigating bone loss and fracture risk. Integrating insights from lipid metabolism, endocrinology, and bone biology can enhance our understanding of the complex interplay between cholesterol and bone health, ultimately improving outcomes for individuals at risk of osteoporosis. Our research, after adjusting for covariates, demonstrates that a higher NHHR is significantly associated with lower BMD in adults aged 20–59 years, according to weighted multiple linear regression models. In accordance with the STROBE statement, we conducted a subgroup analysis to identify specific groups exhibiting varied trends [ 41 ]. Among the total cohort, other race individuals, and participants aged 30–39 years, we discovered a nonlinear relationship with inflection points at 4.29, 5.26, and 2.91, respectively. Based on this relationship, regulating NHHR by lowering LDL-C and TG levels while maintaining or increasing HDL-C levels could offer a more comprehensive approach to preventing and treating osteoporosis. Strengths and limitations This study presents several noteworthy strengths. Foremost, it conducts a comprehensive examination of the association between NHHR and lumbar BMD in American adults, utilizing extensive and representative data from the NHANES 2011–2018 cycles. The findings position NHHR as a potential novel biomarker for bone health, highlighting the crucial role of lipid metabolism disorders in bone loss mechanisms. The employment of advanced statistical methodologies, including multivariate linear regression, stratified analyses, and threshold effect analysis, enhances the robustness of the results. Nonetheless, certain limitations must be acknowledged. The cross-sectional design of the study inherently limits the ability to draw definitive causal inferences between NHHR and BMD. Additionally, the generalizability of the findings to other populations or ethnic groups remains uncertain due to genetic and environmental heterogeneity. The reliance on self-reported data for certain covariates may introduce recall bias, and residual confounding factors may persist despite adjustments. Therefore, further prospective clinical and basic research is essential to elucidate the underlying causal pathways and validate the observed associations. Conclusion In individuals aged 20 to 59 years, our study identified an inverse relationship between NHHR and lumbar BMD. This association followed a reverse-L curve across the entire cohort and was particularly pronounced among individuals of various racial backgrounds and those aged 30–39 years, with inflection points identified at NHHR values of 4.29, 5.26, and 2.91, respectively. These findings suggest that NHHR could serve as a sensitive biomarker for the early detection of osteoporosis, potentially informing and guiding therapeutic strategies. Abbreviations NHANES National Health and Nutrition Examination Survey DXA dual-energy X-ray absorptiometry PIR Ratio of family income to poverty BMI Body mass index ALT Alanine aminotransferase AST Aspartate aminotransferase TC Total cholesterol HDL-C High-density lipoprotein cholesterol TG Triglyceride LDL-C Low-density lipoprotein cholesterol BMD Bone mineral density Declarations Ethics approval and consent to participate In compliance with the Declaration of Helsinki, the ethics review board of the National Center for Health Statistics approved all NHANES protocols. Written informed consent was obtained from all participants. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This research did not receive any direct funding from third-party donors or funding institutions, whether public, commercial, or non-profit. Author Contribution Z.S. conducted and interpreted the statistical analyses and drafted the initial manuscript. Y.Y. was responsible for data collection and statistical analysis. P.L. designed the study and revised the manuscript. All authors reviewed and approved the final manuscript. Acknowledgement We acknowledge the data provided by the National Health and Nutrition Examination Survey (NHANES). Data Availability The dataset analyzed in this study is publicly available at NHANES: https://www.cdc.gov/nchs/nhanes/. References Wang L, Yu W, Yin X, Cui L, Tang S, Jiang N, Cui L, Zhao N, Lin Q, Chen L, et al. Prevalence of Osteoporosis and Fracture in China: The China Osteoporosis Prevalence Study. JAMA Netw Open. 2021;4:e2121106. https://doi.org/10.1001/jamanetworkopen.2021.21106 . Ensrud KE, Crandall CJ, Osteoporosis. 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Western-type diet differentially modulates osteoblast, osteoclast, and lipoblast differentiation and activation in a background of APOE deficiency. Lab Invest. 2018;98:1516–26. https://doi.org/10.1038/s41374-018-0107-7 . Gao-Xiang W, Jun-Tong L, De-Liang L, Shu-Fang C, Hui-Lin L, Heng-Xia Z, Ze-Bin F, Wei X. The correlation between high-density lipoprotein cholesterol and bone mineral density in adolescents: a cross-sectional study. Sci Rep. 2023;13. https://doi.org/10.1038/s41598-023-32885-x . Jiang J, Qiu P, Wang Y, Zhao C, Fan S, Lin X. Association between serum high-density lipoprotein cholesterol and bone health in the general population: a large and multicenter study. Arch Osteoporos. 2019;14:36. https://doi.org/10.1007/s11657-019-0579-0 . Li S, Guo H, Liu Y, Wu F, Zhang H, Zhang Z, Xie Z, Sheng Z, Liao E. Relationships of serum lipid profiles and bone mineral density in postmenopausal Chinese women. Clin Endocrinol (Oxf). 2015;82:53–8. https://doi.org/10.1111/cen.12616 . von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg. 2014;12:1495–9. https://doi.org/10.1016/j.ijsu.2014.07.013 . Tables Table 1 to 5 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table.zip Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACAwh1AEJ9MLCxI00L44yCtGTStDDzfDjE2EBIi7lE+jPpgj935Mz515hJ2xgcYGZgP3x0Az4tlj1nzKRn8Dwztpzxxkw6x+AOHwNPWtoNvA473sMmzSNxOHHDjTMgLc+YGSR4zPBrOcz+TJrH4HA9WIuFwWHGBoJajjeYSfMkHE4wON9jJs1AlJYzZ4yteQ4cNtxwg63YsscgLZmNoF9upD+8zfPnsLzB+cMbb/z4Y2PHz374GF4tCCCRAYkjNuKUgwD/8QfEKx4Fo2AUjIIRBQBsS0xpiSympgAAAABJRU5ErkJggg==","orcid":"","institution":"Jintang First People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Zhengyu","middleName":"","lastName":"Sun","suffix":""},{"id":349113880,"identity":"b72048f8-beba-465f-80cd-3f1b9a7fe16f","order_by":1,"name":"Yong Yue","email":"","orcid":"","institution":"Chiba University Center for Forensic Mental Health","correspondingAuthor":false,"prefix":"","firstName":"Yong","middleName":"","lastName":"Yue","suffix":""},{"id":349113882,"identity":"906132ad-bdb2-4035-8066-b8e24b98d895","order_by":2,"name":"Pengcheng Li","email":"","orcid":"","institution":"First Affiliated Hospital of Chengdu Medical College","correspondingAuthor":false,"prefix":"","firstName":"Pengcheng","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-08-24 13:01:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4969279/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4969279/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66840723,"identity":"2eca5521-bf96-49bf-bc80-651d4c16a818","added_by":"auto","created_at":"2024-10-17 05:01:35","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":288025,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure 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legend\u003c/p\u003e","description":"","filename":"Figure.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4969279/v1/19dc98bdf2d52f50a823fa2e.jpg"},{"id":66843426,"identity":"0fcf413f-35a4-4881-a78f-24c6d6f5c593","added_by":"auto","created_at":"2024-10-17 05:26:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2516910,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4969279/v1/c1922e57-6d7c-47d9-8c87-a138e2fb5639.pdf"},{"id":66840728,"identity":"df17ff51-1e8d-4e4f-91bc-33eaa67ca2e5","added_by":"auto","created_at":"2024-10-17 05:01:35","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":82485,"visible":true,"origin":"","legend":"","description":"","filename":"Table.zip","url":"https://assets-eu.researchsquare.com/files/rs-4969279/v1/6296a39f82cb90fef1a1ddbf.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"The association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and bone mineral density in US adults: NHANES (2011-2018)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOsteoporosis has become a significant public health issue driven by the aging global population. This pervasive metabolic bone disease is characterized by reduced bone mineral density (BMD) and structural degeneration, which heightens the risk of fractures [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The International Osteoporosis Foundation reports that over 30% of women and 20% of men over 50 years old suffer from osteoporosis or osteopenia, placing them at substantial fracture risk [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The reduction in BMD is a crucial diagnostic criterion for osteoporosis, with early detection and prevention of bone mass loss being key to mitigating osteoporotic fractures, particularly in cases of senile and postmenopausal osteoporosis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Various factors, including advanced age, female sex, genetic predisposition, and lipid metabolism abnormalities, contribute to the development of osteoporosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, effective management thus necessitates early identification and modulation of risk factors such as diet, environmental influences, and lifestyle choices to curb bone mass loss and enhance patient outcomes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEmerging evidence underscores the intricate involvement of lipid metabolism in the pathogenesis of both osteoporosis and cardiovascular disease, with dyslipidemia potentially serving as a predictor for osteoporosis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Low-density lipoprotein cholesterol (LDL-C), a recognized risk factor for cardiovascular disease due to its role in atherosclerotic plaque formation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], exhibits a negative association with osteoporosis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Metabolic disorders of total cholesterol (TC) and triglycerides (TG), primary contributors to atherosclerosis, often coincide with osteoporosis in the elderly, indicating a link between cholesterol, triglycerides, and BMD [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Research has increasingly focused on high-density lipoprotein cholesterol (HDL-C) and its relationship with BMD, though findings remain inconsistent. Some studies report a positive correlation between HDL-C levels and BMD, particularly in postmenopausal women [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], while others indicate negative correlations or no association at all [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecently, the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) has emerged as a novel, comprehensive indicator, offering a new framework for understanding and developing therapies. Investigating the relationship between NHHR levels and BMD could reveal its potential as a predictive marker for osteoporosis. However, the relationship between the NHHR and lumbar BMD is poorly known. Therefore, this study aims to assess the relationship between NHHR and BMD in adults using data from the National Health and Nutrition Examination Survey (NHANES) 2011\u0026ndash;2018. We hypothesize that NHHR is negatively associated with lumbar BMD.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source and study population\u003c/h2\u003e \u003cp\u003eThe National Health and Nutrition Examination Survey (NHANES) is a pivotal program in the United States that provides objective health statistics and addresses emerging public health issues. The survey methodologies were approved by the Institutional Review Board of the National Center for Health Statistics, with informed consent obtained from all participants [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our analysis utilized data from 2011 to 2018, spanning four NHANES cycles and including a total of 39,156 participants. The exclusion criteria were as follows: (1) participants younger than 20 years or older than 59 years (n\u0026thinsp;=\u0026thinsp;24,222), (2) individuals with missing NHHR (n\u0026thinsp;=\u0026thinsp;1,427) and BMD data (n\u0026thinsp;=\u0026thinsp;2,483), and (3) those with incomplete covariate data (n\u0026thinsp;=\u0026thinsp;145). Consequently, our final analysis included 10,879 participants (Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of NHHR\u003c/h2\u003e \u003cp\u003eIn this study, the non-HDL-C to HDL-C ratio (NHHR) was utilized as the exposure variable. NHHR is defined as the ratio of non-HDL-C to HDL-C. Non-HDL-C is determined by subtracting HDL-C from TC using blood samples obtained from fasting individuals [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Enzymatic testing to assess TC and HDL-C levels was conducted with an automated biochemical analyzer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBMD measurements\u003c/h2\u003e \u003cp\u003eTotal lumbar BMD served as the outcome variable in this analysis, calculated as the mean of measurements from the first to the fourth lumbar vertebra. Dual-energy X-ray absorptiometry is a widely utilized technology for evaluating BMD due to its efficiency, simplicity, and minimal radiation exposure [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Dual-energy X-ray absorptiometry was performed using a Hologic QDR 4500A device and Apex software version 3.2 by qualified radiology technologists to assess lumbar BMD.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eCovariates definitions\u003c/h2\u003e \u003cp\u003eThe multivariate models accounted for variables that could potentially confound the association between NHHR and lumbar BMD. The analysis included the following covariates: age, race, educational attainment, marital status, smoking history, alcohol consumption, moderate physical activity, hypertension, diabetes, ratio of family income to poverty (PIR), body mass index (BMI), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum calcium, serum phosphorus, total protein, blood urea nitrogen, serum uric acid, TC, HDL-C, TG, and LDL-C. To mitigate sample size bias, the original NHANES categories \"other Hispanic\" and \"other multiracial race\" were consolidated into the variable \"other race.\" Smoking, alcohol consumption, moderate physical activity, hypertension, and diabetes were assessed using questionnaires with the following questions: \"Have you smoked at least 100 cigarettes in your lifetime?\", \"Have you ever consumed 4/5 or more drinks daily?\", \"Does moderate-intensity activity cause slight increases in breathing or heart rate?\", \"Has a doctor ever diagnosed you with diabetes?\", and \"Has a doctor ever diagnosed you with high blood pressure?\" Detailed information on these covariates is available on the NHANES website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/nhanes/\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/nhanes/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll assessments incorporated NHANES sampling weights. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while categorical variables were represented as percentages. Participants were stratified into quartiles based on NHHR levels. To compare participant characteristics, weighted Student's t-tests were utilized for continuous variables, and weighted chi-square tests were applied for categorical variables. The relationship between NHHR and lumbar BMD was explored using weighted multivariate linear regression analyses across three models: Model 1 was unadjusted, Model 2 adjusted for age, gender, and race, and Model 3 further adjusted for educational level, marital status, smoking, alcohol consumption, moderate physical activity, hypertension, diabetes, PIR, BMI, ALT, AST, serum calcium, serum phosphorus, total protein, blood urea nitrogen, and serum uric acid. Subgroup analysis was performed using stratified multivariate regression analysis. Nonlinear associations were assessed with weighted smooth curve fitting and threshold effect analysis, employing a two-piecewise linear regression model to identify inflection points. All statistical analyses were conducted using R (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.R-project.org\u003c/span\u003e\u003cspan address=\"http://www.R-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, The R Foundation) and EmpowerStats software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.empowerstats.com\u003c/span\u003e\u003cspan address=\"http://www.empowerstats.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, X\u0026amp;Y Solutions, Inc., Boston, MA), with a significance level set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eParticipants characteristics\u003c/h2\u003e \u003cp\u003eParticipants were divided into quartiles based on NHHR levels (Q1: 0.36\u0026ndash;1.92; Q2: 1.93\u0026ndash;2.68; Q3: 2.69\u0026ndash;3.67; Q4: 3.68\u0026ndash;26.85), as outlined in Table\u0026nbsp;1. This study included 10,879 individuals aged 20 to 59 years, with a mean age of 39.49\u0026thinsp;\u0026plusmn;\u0026thinsp;11.70 years. The cohort was composed of 52.04% males and 47.93% females, with 61.55% identified as non-Hispanic white. Educational attainment was predominantly above high school (65.31%), and the majority were married (62.32%). The prevalence rates for smoking, alcohol consumption, hypertension, and diabetes were 41.30%, 15.70%, 22.62%, and 5.83%, respectively. Notable differences in baseline characteristics emerged across the NHHR quartiles. Participants in the highest NHHR quartile were more likely to be male, non-Hispanic white, and exhibited higher BMI, ALT, AST, total protein, serum uric acid, TC, TG, and LDL-C, alongside lower PIR, HDL-C, and lumbar BMD compared to those in the lower quartiles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between NHHR and BMD\u003c/h2\u003e \u003cp\u003eThe results of the multivariate regression analysis are presented in Table\u0026nbsp;2. In Model 1, which included no covariate adjustments, lumbar BMD exhibited a negative correlation with NHHR (β = -0.009, 95% CI: -0.011 to -0.007, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This inverse relationship persisted after controlling for confounders in both Model 2 (β = -0.006, 95% CI: -0.008 to -0.004, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Model 3 (β = -0.006, 95% CI: -0.008 to -0.003, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the fully adjusted Model 3, participants in the highest NHHR quartile had a lumbar BMD that was 0.034 g/cm\u0026sup2; lower compared to those in the lowest quartile, following the conversion of NHHR from a continuous variable to quartiles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eSubgroup analyses stratified by age, gender, race, BMI, hypertension, and diabetes are presented in Table\u0026nbsp;2. In Model 3, the adverse association between NHHR and lumbar BMD remained significant in both males (β = -0.005, 95% CI: -0.008 to -0.002, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and females (β = -0.007, 95% CI: -0.011 to -0.003, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This negative relationship was also evident across racial groups, including non-Hispanic whites (β = -0.005, 95% CI: -0.009 to -0.001, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), non-Hispanic blacks (β = -0.010, 95% CI: -0.017 to -0.004, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), and other races (β = -0.007, 95% CI: -0.011 to -0.003, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), but was not observed in Mexican Americans. Age-stratified results revealed a significant negative relationship between NHHR and lumbar BMD in participants aged 20\u0026ndash;29 years (β = -0.006, 95% CI: -0.011 to -0.001, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022) and 40\u0026ndash;49 years (β = -0.008, 95% CI: -0.013 to -0.003, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Among the BMI groups, a significant negative correlation was found in individuals with a BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 (β = -0.008, 95% CI: -0.014 to -0.002, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) and those with a BMI between 25 and 30 (β = -0.011, 95% CI: -0.015 to -0.007, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eA nonlinear correlation between NHHR and BMD\u003c/h2\u003e \u003cp\u003eFigures 2, 3, 4, and 5 illustrate the smooth curve fits and generalized additive models used to characterize the nonlinear relationship between NHHR and lumbar BMD. Utilizing a two-piecewise linear regression model, the association between NHHR and lumbar BMD was found to be nonlinear, with an inflection point at 4.29 (Table\u0026nbsp;3). Among participants from other racial groups, this association exhibited a reverse-L curve, with an inflection point at 5.26 (Table\u0026nbsp;4). Similarly, in participants aged 30\u0026ndash;39 years, the relationship between NHHR and lumbar BMD also followed a reverse-L curve, with an inflection point at 2.91 (Table\u0026nbsp;5).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we utilized the latest representative data from NHANES (2011\u0026ndash;2018) to evaluate the associations between NHHR and BMD. Our multivariate linear regression analyses revealed a negative correlation between NHHR and lumbar BMD. Curve fitting and threshold effect analyses indicated a nonlinear relationship between the variables, with an inflection point at 4.29. Specifically, in the other race group and participants aged 30\u0026ndash;39 years, we identified a nonlinear relationship between NHHR and lumbar BMD, with inflection points at 5.26 and 2.91, respectively.\u003c/p\u003e \u003cp\u003eEmerging research underscores the intricate relationship between lipid profiles and BMD, elucidating the differential effects of various lipid components on bone health through distinct cellular and molecular mechanisms [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In a cross-sectional study, elevated levels of LDL-C were positively associated with osteoporosis and low bone mass in elderly females [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This finding is corroborated by other studies, which demonstrate that LDL-C exerts a negative impact on lumbar spine BMD in postmenopausal women, particularly when LDL-C levels are below 3.52 mmol/L [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Mechanistically, LDL-C and its oxidized form, ox-LDL, impair osteoblast function and promote osteoclast activity, resulting in increased bone resorption and decreased bone mass [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This deleterious process is mediated through oxidative stress and inflammation, as LDL-C induces the production of reactive oxygen species (ROS) and pro-inflammatory cytokines such as TNF-α, IL-6, and IL-1β, which in turn damage bone cells and the extracellular matrix [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Similarly, elevated cholesterol levels have been associated with lower BMD or osteoporosis in multiple studies [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. For instance, Fang et al. reported a negative correlation between serum TC and lumbar spine BMD after adjusting for confounders [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. High TC levels contribute to systemic inflammation and oxidative stress, which disrupt bone metabolism by favoring resorption over formation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Additionally, a nationwide cross-sectional study found that elevated TG levels were inversely associated with whole-body BMD in both men and women, with a relationship potentially modulated by vitamin D status among older adults [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHDL-C, traditionally recognized for its cardiovascular benefits, also appears to support bone health [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. A study by Zolfaroli et al. found that HDL-C positively impacts BMD of the lumbar spine and femoral neck in postmenopausal women [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. HDL-C exhibits antioxidant properties that mitigate oxidative stress, thereby reducing ROS levels and protecting osteoblasts from oxidative damage [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Furthermore, HDL-C inhibits the expression of RANKL, decreasing osteoclastogenesis and promoting bone formation [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, some studies report negative correlations or no association between HDL-C and BMD, indicating that the mechanisms through which HDL-C influences bone density may be complex. For example, a large sample survey found a negative correlation between HDL-C levels and total BMD in male adolescents aged 12 to 19 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Similarly, two studies from China identified an inverse relationship between HDL-C levels and BMD, suggesting a potential adverse impact on bone density [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Conversely, other studies have found no association between HDL-C levels and osteoporosis across various locations [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These discrepancies likely arise from differences in study design, population characteristics, and confounding factors such as age, sex, and comorbidities. The heterogeneity in study outcomes highlights the need for comprehensive research to clarify the pathways through which cholesterol influences bone density. Personalized approaches to osteoporosis prevention and treatment, tailored to individual lipid profiles and demographic characteristics, may offer the most effective strategies for mitigating bone loss and fracture risk. Integrating insights from lipid metabolism, endocrinology, and bone biology can enhance our understanding of the complex interplay between cholesterol and bone health, ultimately improving outcomes for individuals at risk of osteoporosis.\u003c/p\u003e \u003cp\u003eOur research, after adjusting for covariates, demonstrates that a higher NHHR is significantly associated with lower BMD in adults aged 20\u0026ndash;59 years, according to weighted multiple linear regression models. In accordance with the STROBE statement, we conducted a subgroup analysis to identify specific groups exhibiting varied trends [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Among the total cohort, other race individuals, and participants aged 30\u0026ndash;39 years, we discovered a nonlinear relationship with inflection points at 4.29, 5.26, and 2.91, respectively. Based on this relationship, regulating NHHR by lowering LDL-C and TG levels while maintaining or increasing HDL-C levels could offer a more comprehensive approach to preventing and treating osteoporosis.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThis study presents several noteworthy strengths. Foremost, it conducts a comprehensive examination of the association between NHHR and lumbar BMD in American adults, utilizing extensive and representative data from the NHANES 2011\u0026ndash;2018 cycles. The findings position NHHR as a potential novel biomarker for bone health, highlighting the crucial role of lipid metabolism disorders in bone loss mechanisms. The employment of advanced statistical methodologies, including multivariate linear regression, stratified analyses, and threshold effect analysis, enhances the robustness of the results. Nonetheless, certain limitations must be acknowledged. The cross-sectional design of the study inherently limits the ability to draw definitive causal inferences between NHHR and BMD. Additionally, the generalizability of the findings to other populations or ethnic groups remains uncertain due to genetic and environmental heterogeneity. The reliance on self-reported data for certain covariates may introduce recall bias, and residual confounding factors may persist despite adjustments. Therefore, further prospective clinical and basic research is essential to elucidate the underlying causal pathways and validate the observed associations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn individuals aged 20 to 59 years, our study identified an inverse relationship between NHHR and lumbar BMD. This association followed a reverse-L curve across the entire cohort and was particularly pronounced among individuals of various racial backgrounds and those aged 30\u0026ndash;39 years, with inflection points identified at NHHR values of 4.29, 5.26, and 2.91, respectively. These findings suggest that NHHR could serve as a sensitive biomarker for the early detection of osteoporosis, potentially informing and guiding therapeutic strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNHANES National Health and Nutrition Examination Survey\u003c/p\u003e \u003cp\u003eDXA dual-energy X-ray absorptiometry\u003c/p\u003e \u003cp\u003ePIR Ratio of family income to poverty\u003c/p\u003e \u003cp\u003eBMI Body mass index\u003c/p\u003e \u003cp\u003eALT Alanine aminotransferase\u003c/p\u003e \u003cp\u003eAST Aspartate aminotransferase\u003c/p\u003e \u003cp\u003eTC Total cholesterol\u003c/p\u003e \u003cp\u003eHDL-C High-density lipoprotein cholesterol\u003c/p\u003e \u003cp\u003eTG Triglyceride\u003c/p\u003e \u003cp\u003eLDL-C Low-density lipoprotein cholesterol\u003c/p\u003e \u003cp\u003eBMD Bone mineral density\u003c/p\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e In compliance with the Declaration of Helsinki, the ethics review board of the National Center for Health Statistics approved all NHANES protocols. Written informed consent was obtained from all participants.\u003c/p\u003e \u003ch2\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003ch2\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research did not receive any direct funding from third-party donors or funding institutions, whether public, commercial, or non-profit.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZ.S. conducted and interpreted the statistical analyses and drafted the initial manuscript. Y.Y. was responsible for data collection and statistical analysis. P.L. designed the study and revised the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe acknowledge the data provided by the National Health and Nutrition Examination Survey (NHANES).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe dataset analyzed in this study is publicly available at NHANES: https://www.cdc.gov/nchs/nhanes/.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWang L, Yu W, Yin X, Cui L, Tang S, Jiang N, Cui L, Zhao N, Lin Q, Chen L, et al. Prevalence of Osteoporosis and Fracture in China: The China Osteoporosis Prevalence Study. 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Int J Surg. 2014;12:1495\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijsu.2014.07.013\u003c/span\u003e\u003cspan address=\"10.1016/j.ijsu.2014.07.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 5 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"NHANE, Lumbar BMD, Osteoporosis, NHHR","lastPublishedDoi":"10.21203/rs.3.rs-4969279/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4969279/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) represents a novel lipid marker. This study investigated the association between NHHR and lumbar bone mineral density (BMD) in the general American population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2018 were used in this study, including 10,879 participants aged 20\u0026ndash;59 years. To investigate the relationship between NHHR and lumbar BMD, we employed multivariate linear regression models along with stratified analyses. Additionally, we applied fitted smoothing curves and threshold effect analyses to explore the nonlinear association between NHHR and lumbar BMD.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter adjusting for covariates, weighted multivariable linear regression models indicated a significant negative association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and lumbar bone mineral density (BMD) (β = -0.006, 95% CI: -0.008 to -0.003, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Stratified subgroup analyses based on age, gender, race, BMI, hypertension, and diabetes consistently demonstrated this inverse relationship in males (β = -0.005, 95% CI: -0.008 to -0.002, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and females (β = -0.007, 95% CI: -0.011 to -0.003, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); non-Hispanic whites (β = -0.005, 95% CI: -0.009 to -0.001, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), non-Hispanic blacks (β = -0.010, 95% CI: -0.017 to -0.004, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), and other races (β = -0.007, 95% CI: -0.011 to -0.003, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001); participants aged 20\u0026ndash;29 years (β = -0.006, 95% CI: -0.011 to -0.001, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022) and 40\u0026ndash;49 years (β = -0.008, 95% CI: -0.013 to -0.003, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); individuals with a BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 (β = -0.008, 95% CI: -0.014 to -0.002, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) and those with a BMI between 25 and 30 (β = -0.011, 95% CI: -0.015 to -0.007, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For the total cohort, individuals of other races, and participants aged 30\u0026ndash;39 years, a nonlinear relationship was examined with inflection points identified at NHHR values of 4.29, 5.26, and 2.91, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eFor US adults aged 20 to 59, our research identified an inverse relationship between the NHHR and lumbar BMD. This association was observed across the general cohort, individuals of other races, and participants aged 30\u0026ndash;39 years, demonstrating a nonlinear relationship with inflection points at 4.29, 5.26, and 2.91, respectively. Consequently, NHHR could serve as a sensitive biomarker for the prevention of osteoporosis or osteopenia.\u003c/p\u003e","manuscriptTitle":"The association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and bone mineral density in US adults: NHANES (2011-2018)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-17 05:01:30","doi":"10.21203/rs.3.rs-4969279/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65acb0b5-d8fa-420f-9335-4c6de376ec4c","owner":[],"postedDate":"October 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-17T05:01:33+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-17 05:01:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4969279","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4969279","identity":"rs-4969279","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}