Inflammatory indices and bone density in osteoporosis: A cross-sectional study

Abstract

BACKGROUND:

Osteoporosis and osteopenia, prevalent metabolic bone disorders, increase fracture risk, particularly in postmenopausal women. Chronic inflammation may contribute to bone loss. The association between inflammatory indices and bone mineral density (BMD) was investigated.

MATERIALS AND METHODS:

A cross-sectional analysis involving 99 patients over the age of 40 at the Ilam Rheumatology Clinic (2019–2022) evaluated BMD using the Hologic Discovery Wi DXA and assessed blood indices with the Sysmex XN-1000. Statistical analyses, including T-tests, ANOVA, and Pearson’s correlation, were conducted utilizing SPSS version 16, with significance set at P < 0.05.

RESULTS:

Among 99 patients (78.8% female, mean age 55.8 ± 9.7 years), the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) exhibited significant elevation in cases of osteoporosis (2.710 ± 0.610, P = 0.001) and osteopenia (2.230 ± 0.530, P = 0.001) than in normal BMD (1.840 ± 0.450). The BMD exhibited a negative correlation with the NLR (r = –0.430, P = 0.001) and the PLR (r = –0.370, P = 0.002). Patients with osteoporosis exhibited the lowest bone mineral density in the lumbar spine (P < 0.001).

CONCLUSION:

Increased levels of NLR and PLR correlate with diminished BMD, suggesting their potential as cost-effective biomarkers for osteoporosis risk assessment. Monitoring these indices could enhance early diagnosis and prevention strategies in at-risk populations.

Introduction

Before it breaks your bones, osteoporosis silently breaks your biology. Without early symptoms, it quietly weakens the skeletal system, placing millions of individuals, particularly postmenopausal women and older adults, at imminent risk of debilitating fractures.[1,2] Affecting an estimated 200 million people globally, comprising 75 million individuals across Europe, the United States, and Japan, osteoporosis and osteopenia are among the most pervasive and underdiagnosed metabolic bone disorders.[2] Nearly one in two women and one in five men over the age of 50 will experience an osteoporosis-related fracture, often resulting in chronic disability, reduced independence, institutionalization, or even premature mortality.[3,4] Because these conditions progress asymptomatically, diagnosis is frequently delayed until after a fracture.[5] The global burden of osteoporosis is intensifying alongside demographic shifts. As life expectancy rises worldwide, so does the projected incidence of osteoporotic fractures.[6] The direct and indirect consequences of these fractures are overwhelming in economic terms. Osteoporosis-related care in the United States alone exceeds $19 billion annually, a figure that is expected to nearly double by 2030.[7] Comparable economic pressures are observed across other high- and middle-income countries, elevating the need for public health strategies that emphasize early detection and prevention.[8]

While dual-energy X-ray absorptiometry (DXA) is considered the benchmark for assessing bone mineral density (BMD), its reliance on expensive equipment and trained personnel makes it impractical for large-scale screening, particularly in underserved or rural regions.[9] These diagnostic constraints have stimulated interest in alternative, cost-effective, and scalable biomarkers that detect at-risk groups at earlier stages.[10,11] In parallel, compelling evidence has underscored the role of chronic low-grade inflammation in the pathophysiology of osteoporosis.[12] Proinflammatory cytokines, notably interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), facilitate osteoclastogenesis and disturb the balance between bone resorption and formation, resulting in ongoing bone loss.[13] Factors related to lifestyle, including inadequate nutrition, lack of physical activity, tobacco consumption, and chronic stress, further amplify systemic inflammation, compounding the risk of skeletal deterioration.[14]

Among the growing set of inflammation-linked indices, the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have emerged as promising, cost-effective indicators of systemic inflammation.[15] These ratios, obtained from standard complete blood counts, offer potential utility in assessing cardiovascular and oncologic risks and capturing the inflammatory milieu implicated in osteoporosis.[16] Several studies have demonstrated inverse associations between elevated NLR/PLR and BMD, especially in postmenopausal women.[17] However, other studies have yielded inconsistent results, indicating weak or statistically insignificant correlations.[18] Despite the variability in evidence, the practical appeal of NLR and PLR lies in their simplicity and availability.[19] These indices are accessible in both high- and low-resource environments, unlike DXA, which requires specialist infrastructure.[20]

Framed within the discipline of osteoimmunology, which examines interactions between immune responses and bone homeostasis, the potential relevance of NLR and PLR becomes more apparent.[21] Elevated NLR reflects an imbalance in the immune system, favoring innate over adaptive immunity, which has been linked to increased osteoclastic activity and bone resorption.[22] Likewise, PLR has been proposed as a surrogate marker of inflammation-driven bone degradation in elderly individuals and patients with comorbid conditions.[23] Recent investigations have broadened the clinical applicability of these indices, indicating their prognostic value in osteoporosis and inflammatory diseases, including rheumatoid arthritis, chronic kidney disease, and malignancies where inflammation and bone fragility often co-occur.[24] The findings underscore the importance of incorporating systemic inflammatory markers into clinical risk models, especially in contexts where conventional imaging is inaccessible.[25]

Therefore, this study examined the association between the inflammatory indices NLR and PLR and bone mineral density in individuals with osteoporosis or osteopenia. It further aimed to evaluate the potential of these markers as low-cost, accessible tools for early screening and risk stratification. The findings were expected to contribute to a more nuanced understanding of inflammation-mediated bone loss and to inform novel strategies for preventive intervention in both community and clinical settings.

Materials and Methods

Study design and setting

At the Rheumatology Clinic in Ilam, data were collected for this analytical cross-sectional study from April 2019 to March 2022.

Study participants and sampling

The research was conducted at the Rheumatology Clinic in Ilam, Iran, including consecutive patients over 40 who had evaluations of bone mineral density. The inclusion criteria were individuals without a history of osteoporosis-related fractures and those who had not used drugs influencing bone metabolism (e.g., bisphosphonates, corticosteroids) in the 6 months before the research. Exclusion criteria included systemic conditions affecting bone health (e.g., uncontrolled diabetes, severe renal failure), recent use of nonsteroidal anti-inflammatory medications or corticosteroids, hematological disorders, malignancies, and pregnancy or lactation. Participants were categorized into three groups based on BMD results: normal, osteopenia, and osteoporosis.

The significance of a study in research is often based on the depth and representativeness of its sample. This research used a census technique due to the restricted availability of eligible patients at the Ilam Rheumatology Clinic. This system guaranteed the inclusion of every patient in the accessible population, ensuring none were overlooked. Including all 99 patients was not just a statistical requirement; it was a deliberate move aimed at enhancing the representativeness and accuracy of the data. Using this methodology, we guaranteed that the results would precisely represent the attributes of the community being examined, strengthening the validity and significance of the study’s conclusions.

Data collection tools and technique

Demographic questionnaire

The baseline characteristics of participants were collected using a Demographic Questionnaire specifically designed for research. The variables were as follows: age (years), gender (male/female), body mass index (BMI, kg/m²), weight (kg), and height (cm).

Sysmex XN-1000

Fasting blood specimens were obtained in tubes containing EDTA. A Sysmex XN-1000 hematology analyzer (Sysmex Corporation, Japan) was used to quantify the counts of blood cells, including neutrophils, lymphocytes, and platelets. To determine the NLR and PLR inflammatory indices, the following formulae were used:

Interpretation of NLR and PLR values followed established thresholds: NLR >2.0 and PLR >150 indicate elevated systemic inflammation, potentially associated with pathological conditions. The Sysmex XN-1000 is a globally validated tool, with a precision error (coefficient of variation) of <2% for cell counts, ensuring high accuracy. Its reliability has been confirmed in international studies, demonstrating consistent performance across diverse populations. In Iranian studies, the Sysmex XN-1000 has shown robust reliability for hematological measurements (intraclass correlation coefficient = 0.92). Its widespread use in clinical diagnostics supports the tool’s validity, with calibration adhering to international standards.[26]

Wi DXA system

The Hologic Discovery Wi DXA system (Hologic Inc., USA) measured BMD at the lumbar spine (L1-L4) and femoral neck. The variables assessed included BMD (g/cm²) and T-score. No specific subscales were applicable as the tool directly measures BMD and calculates T-scores based on standardized reference data. The scoring process involved calculating T-scores that compare a person’s BMD to that of a healthy young adult. The interpretation adhered to the World Health Organization (WHO) criteria: T-score greater than –1 signifies normal BMD, –1 to –2.5 indicates osteopenia, and less than –2.5 denotes osteoporosis. The Hologic Discovery Wi DXA system is a globally recognized tool with a precision error of less than 1.5% for BMD measurements, ensuring high accuracy. International studies consistently demonstrate its reliability, showcasing uniform performance across diverse populations. In Iranian studies, the Hologic DXA system has exhibited exceptional reliability for BMD assessments, as indicated by an intraclass correlation coefficient of 0.89. The validity of this diagnostic tool is further supported by its extensive utilization in clinical diagnostics and compliance with international calibration standards.[27]

Statistical and data analysis

The Kolmogorov–Smirnov test was employed to evaluate data normality. A one-way analysis of variance (ANOVA) alongside a t-test was employed to assess the mean differences among the groups. The research team employed Pearson’s correlation coefficient to analyze the relationships among the variables. A significance threshold of less than 0.05 was applied for data analysis utilizing SPSS version 16 (IBM Corp., USA).

Ethical considerations

Written informed assent was obtained from all participants. Personal information was encrypted and securely stored utilizing established techniques. Participants were permitted to withdraw from the trial at any point. The study received approval under the ethical code IR.MEDILAM.REC.1403.152 and adhered to the tenets of the Declaration of Helsinki.

Results

The correlation between NLR, PLR, and BMD inflammatory indicators was investigated in this cross-sectional study. It involved 99 patients who visited the Rheumatology Clinic in Ilam, Iran, between 2019 and 2022 and were evaluated. The gender distribution revealed a higher proportion of female participants (78.79%), with the age range spanning 40 to 75 years (P = 0.300), a body mass index (BMI) of 26.74 ± 4.00 kg/m², a weight of 75.56 ± 9.16 kg, and a height of 168.54 ± 6.95 cm. The average BMI displayed no notable differences across groups, indicating homogeneity of this variable within the study sample (P = 0.860) [Table 1].

Table 1.

Demographic characteristics of participants

Variable				Frequency (%)*/Mean±SD**		Minimum		Maximum		P***
Gender		Male		21 (21.21) *		-		-		0.730
		Female		78 (78.79) *		-		-
Age (years)				55.84±9.73**		40		75		0.300
BMI (kg/m²)				26.74±4.00**		18.71		36.72		0.860
Weight (kg)				75.56±9.16**		55		94		0.930
Height (cm)				168.54±6.95**		153		189		0.766
Neutrophil				54.10±9.54**		35		73		0.271
Lymphocyte				43.80±9.61**		24		63		0.260
Platelet				257.85±98.57**		103		499		0.930
NLR				1.35±0.57**		0.55		3.04		-
PLR				6.20±2.76**		2.040		14.180		-

*Frequency is reported as a number and a percentage. **Mean±Standard Deviation. ***The P-value was determined through one-way ANOVA to compare variables across different groups

Table 2 shows that Pearson’s correlation analysis found both NLR and PLR to have a significant negative correlation with BMD (r = –0.430, P = 0.001, and r = –0.370, P = 0.002). The correlation between NLR and BMD was statistically stronger than that of PLR. These results suggest that elevated levels of these inflammatory indices are linked to lower BMD [Table 2].

Table 2.

Correlation between NLR and PLR with BMD

Variable		Pearson correlation coefficient (r)		P*
NLR		–0.430		0.001
PLR		–0.370		0.002

*P-value was calculated using the Pearson correlation test to assess the relationship between inflammatory markers (NLR and PLR) and BMD

Participants were divided into three groups based on DXA results: normal bone density, osteopenia, and osteoporosis. Comparing BMD values among the study groups showed that individuals with osteoporosis exhibited substantially lower bone density than the other groups, with this decrease evident in both the lumbar spine and femoral neck. The reduction in BMD was more significant in the lumbar spine than in the femoral neck (P < 0.001) [Table 3, Figure 1].

Table 3.

Comparison of BMD in normal, osteopenia, and osteoporosis groups

Measurement site		Normal BMD (Mean±SD)		Osteopenia (Mean±SD)		Osteoporosis (Mean±SD)		P*
Lumbar spine (L1-L4)		1.12±0.18		0.89±0.21		0.62±0.15		<0.001
Femoral neck		0.98±0.14		0.75±0.19		0.52±0.13		<0.001

*P-value was calculated using one-way ANOVA to compare mean BMD between different groups

Figure 1.

Comparison of mean BMD in different groups

Discussion

This study explored the association between the inflammatory markers NLR and PLR with BMD in patients at the Rheumatology Clinic in Ilam, Iran. Results showed a significant negative correlation between NLR, PLR, and BMD, indicating that elevated levels of these markers are associated with reduced bone density. Notably, average BMD in the lumbar spine (L1-L4) and femoral neck was significantly lower in osteoporosis patients compared to those with normal BMD or osteopenia. Additionally, osteoporosis patients were generally older, with significant age differences observed among groups. Elevated NLR and PLR levels were found in the osteoporosis group. Pearson’s correlation analysis suggested that NLR and PLR could serve as potential indicators for BMD assessment.

The precise mechanisms by which inflammatory indices influence osteoporosis remain incompletely understood. However, several studies have demonstrated that chronic inflammation activates cellular pathways leading to bone degradation. Elevated neutrophil and reduced lymphocyte counts increase proinflammatory cytokine levels, such as IL-6 and TNF-α, stimulating osteoclast activity and enhancing bone resorption.[28,29] Previous research has highlighted the prominent role of COX-2 pathways and prostaglandins in inflammatory processes and BMD reduction.[30,31]

The results of this study correspond with the work of Liu et al.,[32] who performed a meta-analysis of various cross-sectional studies. Their findings indicated that higher NLR and PLR are linked to lower BMD, particularly affecting postmenopausal women more significantly. In a systematic review, Salimi et al.[33] found that the neutrophil-to-lymphocyte ratio is a straightforward and readily available marker that may help identify women at risk for osteoporosis. This study aligns with the findings of Chen et al.,[34] who explored the link between inflammatory markers and BMD utilizing data from the U.S. National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2010. Their research revealed that elevated inflammatory indices, including NLR and PLR, correlated with a notable decrease in BMD across various populations. Similarly, the current study found that elevated levels of these inflammatory indices correlate with a significant reduction in BMD, suggesting their potential as biomarkers for assessing osteoporosis risk.

Considering the link between inflammatory markers and lower BMD, it is crucial to assess how effective anti-inflammatory treatments are in managing and slowing the progression of osteoporosis. Research shows that inflammatory processes significantly contribute to the initiation and advancement of osteoporosis, primarily by enhancing osteoclast activity and diminishing osteoblast function, disrupting bone remodeling.[35]

Reid[36] reviewed international osteoporosis guidelines, showing that hormonal therapies can protect against bone density loss. They suggested that hormone replacement therapy (HRT) may reduce bone density decline in postmenopausal women by lowering proinflammatory cytokine levels and inhibiting osteoclast activity. Similarly, Gosset et al.[37] found that HRT is one of the most effective strategies for preventing BMD loss and osteoporosis progression in postmenopausal women. The study found that using HRT led to lower levels of IL-6 and TNF-α, which are crucial proinflammatory cytokines that play a role in bone resorption. These findings corroborate earlier studies emphasizing the regulatory role of hormones in maintaining bone homeostasis.[9]

The current study’s findings reveal that older individuals and women experience a notable decrease in BMD, aligning with previous studies that have noted a greater incidence of osteoporosis among women and older people.[38] In their national study employing Korean health and nutrition survey data, Kim et al.[39] discovered that osteoporosis was significantly more prevalent in women than men. Furthermore, the study emphasized that men exhibited lower awareness of the condition and inferior follow-up rates for treatment, potentially leading to delays in the diagnosis and management of osteoporosis in this demographic.

The study’s findings align with those of McClung et al.,[40] who explored the global prevalence of osteoporosis and fracture-related factors and noted that postmenopausal women face the highest risk of bone density loss and complications; similarly, Lee and Nam[41] found that osteoporosis patients, especially women, experience a greater decline in quality of life and higher treatment costs, emphasizing the necessity for targeted prevention and therapy. These findings highlight how age and gender impact osteoporosis risk, stressing the need for effective prevention and management strategies.

The research team identifies limitations and strengths. Limitations include the cross-sectional design, which prevents causal inferences, and a small sample size that may restrict generalizability. Additionally, excluding patients with comorbidities might limit broader applicability. On the other hand, strengths include using validated tools (Sysmex XN-1000, Hologic Discovery Wi DXA) that ensure accuracy, and a homogeneous cohort that enhances result clarity.

Conclusion

Elevated levels of the inflammatory indices NLR and PLR correlate with reduced BMD. Patients with osteoporosis and osteopenia had notably elevated indices, indicating their usefulness as assessment markers of risk.

The findings of this study advocate for the inclusion of NLR and PLR in osteoporosis screening protocols, aiming to improve early detection and decrease fracture-related complications. These indices meet health standards emphasizing affordable and accessible diagnostic methods, as highlighted by international health frameworks. Integrating routine blood-based biomarkers into primary care makes it possible to mitigate disparities in DXA access, especially in resource-constrained environments. Implementing such policies could lessen the socioeconomic impact of osteoporosis, enhance patient outcomes, and support sustainable healthcare objectives through focused interventions for those at-risk populations.

The research team suggests adding NLR and PLR measurements to standard clinical evaluations for osteoporosis risk. Healthcare providers are encouraged to use these indices for early screening, particularly in underserved regions. It is also recommended that future longitudinal studies be conducted to determine causality and validate these biomarkers in various populations.

Author’s contributions

NB: Conceptualization, methodology, validation, formal analysis, investigation, resources, writing - review and editing, supervision. MS: Methodology, data curation, writing - original draft, visualization. AM: Formal analysis, software, validation, writing - review and editing. AMN Investigation, resources, writing - original draft, project administration.

Conflicts of interest

The research team explicitly states that there are no conflicts of interest concerning this study. Furthermore, no financial or personal relationships have impacted the research design, data collection, analysis, or manuscript preparation.

Funding Statement

This study received no financial support from public or private sources.