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Human Papillomavirus Infections and Increased Risk of Incident Osteoporosis: A Nationwide Population-Based Cohort Study

Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
Department of Orthodontics and Dentofacial Orthopedics, Henry M. Goldman School of Dental Medicine, Boston University, Boston, MA 02118, USA
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
Department of Dermatology, Massachusetts General Hospital, Boston, MA 02114, USA
Department of Orthopedics, Taichung Veterans General Hospital, Taichung 407, Taiwan
Department of Orthopedics, Kaohsiung Veterans General Hospital, Kaohsiung 813, Taiwan
School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
Management Office for Health Data, China Medical University Hospital, Taichung 404, Taiwan
Institute of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
Graduate Institute of Integrated Medicine, China Medical University, Taichung 404, Taiwan
Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung 402, Taiwan
Department of Recreation Sports Management, Tajen University, Pingtung 907, Taiwan
Department of Emergency Medicine, Kaohsiung Veterans General Hospital, Kaohsiung 813, Taiwan
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Viruses 2023, 15(4), 1021;
Submission received: 14 December 2022 / Revised: 21 March 2023 / Accepted: 24 March 2023 / Published: 21 April 2023
(This article belongs to the Special Issue Virology Research in Taiwan)


Patients with viral infections are susceptible to osteoporosis. This cohort study investigated the correlation between human papillomavirus (HPV) infections and the risk of osteoporosis via 12,936 patients with new-onset HPV infections and propensity score-matched non-HPV controls enrolled in Taiwan. The primary endpoint was incident osteoporosis following HPV infections. Cox proportional hazards regression analysis and the Kaplan-Meier method was used to determine the effect of HPV infections on the risk of osteoporosis. Patients with HPV infections presented with a significantly high risk of osteoporosis (adjusted hazard ratio, aHR = 1.32, 95% CI = 1.06–1.65) after adjusting for sex, age, comorbidities and co-medications. Subgroup analysis provided that populations at risk of HPV-associated osteoporosis were females (aHR = 1.33; 95% CI = 1.04–1.71), those aged between 60 and 80 years (aHR = 1.45, 95% CI = 1.01–2.08 for patients aged 60–70; aHR = 1.51; 95% CI = 1.07–2.12 for patients aged 70–80), and patients with long-term use of glucocorticoids (aHR = 2.17; 95% CI = 1.11–4.22). HPV-infected patients who did not receive treatments for HPV infections were at a greater risk (aHR = 1.40; 95% CI = 1.09–1.80) of osteoporosis, while the risk of osteoporosis in those who received treatments for HPV infections did not reach statistical significance (aHR = 1.14; 95% CI = 0.78–1.66). Patients with HPV infections presented with a high risk of subsequent osteoporosis. Treatments for HPV infections attenuated the risk of HPV-associated osteoporosis.

1. Introduction

Osteoporosis affects more than 200 million people and causes 8.9 million fractures annually [1], mainly in postmenopausal women [2] and in elderly man [3]. Subsequent hospitalization and surgery not only diminish quality of life but superimpose a growing economic burden on the health care system [4]. Apart from well-established risk factors including endocrine disorders, lifestyle determinants such as low physical activity, sleep disorders [5,6], and the use of glucocorticoids [1,7], the effect of immune system dysregulation on bone turnover rate was revealed to be involved in the regulation of the immune–skeletal interface, for which osteoporosis has been demonstrated to be associated with chronic immune-mediated diseases and inflammatory-related disorders [8]. Abundant cytokines, transcription factors, and cell networks, such as inflammatory cytokines including interleukin (IL)-1, IL-6, IL-17, tumor necrosis factor-alpha (TNF-α) and immunocytes including T cells, B cells, and dendritic cells, participated in the crosstalk of signaling pathways underlying the pathogenesis of severe bone loss and osteoporosis [9].
As a trigger of the immune-mediated mechanisms that could affect bone quality, increasing studies have demonstrated the relationships between low bone mineral density and infections by viruses including human immunodeficiency virus (HIV) [10], hepatitis B virus (HBV) [10,11], hepatitis C virus (HCV) [10], herpes zoster virus (VZV) [12], and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections [13,14]. For instance, HIV infections were found to elevate the B cell receptor activator of nuclear factor kappa-B ligand (RANKL) and diminish osteo-protegerin, which drives bone resorption [10]. Overall, perturbated by external factors such as acquired immune deficiency syndrome and chronic viral infections, there were trends toward an immunological pattern of immune senescence in osteoporosis, as characterized by the accumulation of activated cells and memory/effector lymphocytes secreting pro-inflammatory cytokines [9], which supported a viral etiology of altered systemic bone turnover rates driven by immune dysfunction.
As some of the most prevalent yet less addressed viral infections in the field of research on osteoporosis, human papillomavirus (HPV) infections are the most commonly diagnosed sexually transmitted disease [15], with more than 600,000 new cases per year around the world [16]. With an HPV-associated etiology, cervical cancer is the second most prevalent cancer among women worldwide and is the most common cancer among women in developing countries [17]. It is well established that HPV infections could be the primary cause of cervical cancers [18] and are also associated with the risk of head and neck cancer, oral cavity cancer, lung cancer, esophageal cancer, breast cancer, and anogenital lesions [19]. Effective approaches for the prevention of HPV-associated cancers include 2vHPV and 4vHPV vaccinations, which have been shown to effectively prevent high-grade intraepithelial lesions in the female genital area [20], the mechanism of which was related to the blocked immune evasion strategies of HPV infections, including alterations in gene expression, protein function, and antigen processing, which would have led to carcinogenesis in unvaccinated individuals [21].
HPV infections and other viral infections share several immune dysfunction pathogeneses that could contribute to the development of osteoporosis, which include a strongly elevated RANKL expression in the progression of HPV-associated cervical neoplasia [22]. Bone resorption and osteoclast formation are driven by RANKL/RANK signaling [23]. The binding between RANKL and RANK activates NF-κB and c-Fos, leading to osteo-clastogenesis. Moreover, it was found that excessive RANKL production by HPV-infected cells could both aggravate tumor burden and exacerbate osteoclast-mediated bone destruction [24]. As such, it was investigated in the present nationwide population-based cohort study as to whether HPV infections could be associated with subsequent risk of osteoporosis or osteoporotic fracture.

2. Materials and Methods

2.1. Data Source

The present population-based cohort study was performed using data from the National Health Insurance Research Database (NHIRD). The NHIRD contains registration files and original claim data, such as hospitalization records, diagnostic codes, records of outpatient visits, medication history, and personal information for over 99% of Taiwan’s population. All diagnostic records were validated by the Bureau of National Health Insurance (NHI) to ensure the accuracy of these data [25]. In this study, data were retrieved from the Longitudinal Health Insurance Research Database (LHIRD), a subset of NHIRD, which was composed of claims data of one million people randomly sampled from the study period between 1997 and 2013. The Institutional Review Board of Taichung Veterans General Hospital approved this study.

2.2. Study Population

In the present study, patients who had been clinically diagnosed with HPV infections between 2000 and 2013 were identified using International Classification of Disease Clinical Modification codes (ICD-9-CM code 079.4, 078.1, 078.10–078.12, 078.19, 759.05, 795.09, 795.15, 795.19, 796.75 and 796.79) [26,27]. Only patients with diagnosis of HPV from at least one inpatient admission or three outpatient visits were selected. The index date was defined as the date of HPV infection diagnosis. Individuals with osteoporosis before the index date or within 1 year after the index date were excluded. Patients aged under 50 years old or beyond 100 years old, or patients with missing information on gender were excluded. The control group was selected from LHIRD, propensity score-matched in a 1:4 ratio by age, sex, index year, co-morbidities and co-medications, using the same protocol as described in previous studies [28,29,30,31]. In the subgroup analysis, patients with HPV infections who had received treatment procedures within three months after the index date were categorized as “with treatment” group, and otherwise as “without treatment” group. Such treatment procedures included: (1) electrocauterization for condyloma, (2) condyloma, excision, and electrocauterization, (3) CO2 laser operation, (4) chemosurgery for condyloma, (5) simple or complicated electro cauterization, (6) liquid nitrogen cryosurgery, (7) simple or complicated cryotherapy that involved CO2 freezing and liquid nitrogen. All participants were tracked until presence of osteoporosis, missing, death, or the end of the study, December 2013. A total of 12,936 subjects were included in the HPV group and 51,744 subjects were included in the non-HPV control group.

2.3. Primary Endpoint and Covariates

All subjects in both groups were tracked from the index date to the first osteoporosis event. The primary endpoint of this study was the occurrence of new-onset osteoporosis, which was diagnosed based on clinical history or spinal or hip bone mineral density (BMD) by dual-energy X-ray absorptiometry (DEXA) evaluation and the use of one of the following medications: denosumab, alendronate, risedronate, ibandronate, zoledronate, raloxifene, bazedoxifene, teriparatide, strontium ranelate [32]. Patients diagnosed with osteoporosis or the use of aforementioned medications before the index date or within one year after the index date were excluded. The use of osteoporosis medications as alternative representatives of osteoporosis patients, in addition to BMD or DEXA assessment, was aimed to intensify the diagnostic validity. To calculate the co-payment exemption of these medications, the NHI bureau used an auditing mechanism to minimize diagnostic uncertainty and misclassification of osteoporosis. To eliminate potential bias, factors including the demographic variables and relevant co-morbidities including hypertension, diabetes mellitus, hyperlipidemia, rheumatoid arthritis, chronic obstructive pulmonary disease (COPD), alcohol-related illness, chronic kidney disease (CKD), inflammatory bowel disease (IBD), HBV, HCV, cirrhosis, celiac disease, syphilis, HIV, chlamydia, gonococcus, hyperthyroidism, hyperparathyroidism, vitamin D deficiency, premature menopause, male hypogonadism, adrenal cortical steroids, smoking, and bone mineralization affecting [33] co-medications including long-term glucocorticoid use [34], phenobarbital, phenytoin, carbamazepine, heparin, warfarin, cyclosporine, tricyclic antidepressants (TCAs) or selective serotonin reuptake inhibitors (SSRIs), proton pump inhibitors, furosemide, thiazide, statin, and beta-blockers. Baseline characteristics within two years before the index date were retrieved and adjusted in the analyses.

2.4. Statistical Analysis

The chi-square test was used to compare the distribution of age, sex, index date, and baseline co-morbidities between the two groups, including those with versus without a previous history of HPV infections. The mean age of onset was compared using Student’s t-test. The incidence rate of osteoporosis was estimated by dividing the amount of osteoporosis by follow-up person-years for HPV-infected cases and non-HPV controls. Multivariable Cox proportional hazards regression models were used to estimate the crude HRs (cHRs) and adjusted HRs (aHRs) for osteoporosis in patients with HPV infections, as compared to non-HPV controls. The covariates considered in the multivariable regression models included sex, age, index date, comorbidities, and co-medications. A multivariable Cox regression model adjusted for the covariates was used to reveal the effect of sex, age, and follow-up time on the incidence of osteoporosis. The HRs adjusted for covariates were calculated each subgroup, as stratified by sex, age, comorbidities, and co-medications. The cumulative incidence curve was obtained from the Kaplan-Meier method and examined by the log-rank test. All data analyses were performed using SAS (version 9.4; SAS Institute, Inc., Carey, NC, USA). The statistical significance level was set at p-value < 0.05 in the two-tailed test.

3. Results

3.1. Basline Characteristics of Study Populations

In this retrospective cohort study, 12,936 HPV-infected patients and 51,744 propensity score-matched non-HPV controls were included. Baseline characteristics are shown in Table 1. The mean ages of the patients in the HPV and non-HPV groups were 63.26 and 63.13 years, respectively.

3.2. Incidence of Osteoporosis in Patients with HPV Infections

The cumulative incidence of osteoporosis in patients with HPV was significantly higher than that in non-HPV controls (log-rank test p-value = 0.01) (Figure 1). The Cox proportional hazards regression models revealed that patients with HPV infections presented with significantly greater risk of osteoporosis (aHR = 1.32, 95% CI = 1.06–1.65) (Table 2). Consistent with previous studies [1,35,36], the risk of osteoporosis was lower in men (aHR = 0.23; 95% CI = 0.18–0.3), and in populations of high socioeconomic status [37] (aHR = 0.30; 95% CI = 0.14–0.64); while the risk of osteoporosis was higher in frequent out-patient department (OPD) visitors (aHR = 1.01; 95% CI = 1.01–1.01) and in patients with comorbidities including COPD (aHR = 1.35; 95% CI = 1.08–1.68), vitamin D deficiency (aHR = 18.3; 95% CI = 2.56–131.09), long term glucocorticoid use (aHR = 2.05; 95% CI = 1.44–2.92), and TCAs/SSRIs use (aHR = 1.60; 95% CI = 1.05–2.43). The risk of osteoporosis was also higher in the older age groups [38], in which patients aged between 60–70 (aHR = 4.29; 95% CI = 3.10–5.93), aged between 70–80 (aHR = 7.32; 95% CI = 5.23–10.26) and aged beyond 80 (aHR = 9.63; 95% CI = 6.22–14.88) were associated with a significantly high risk of osteoporosis (Table 2).

3.3. Factors Associated with HPV-Associated Osteoporosis

Findings in the subgroup analysis of Cox proportional hazards regression models provided that female patients with HPV infections (aHR = 1.33; 95% CI = 1.04–1.71), patients aged 60–70 (aHR = 1.45; 95% CI = 1.01–2.08) or aged 70–80 (aHR = 1.51; 95% CI = 1.07–2.12) with HPV infections, patients of the lowest (aHR = 1.32; 95% CI = 1.01–1.73) or the highest socioeconomic status (aHR = 8.22; 95% CI = 1.59–42.38) with HPV infections, and HPV-infected patients with long-term use of glucocorticoids (aHR = 2.17; 95% CI = 1.11–4.22) were predisposed to significantly great risk of HPV-associated osteoporosis (Table 3). Notably, HPV-infected patients who did not receive treatments for HPV infections had a significantly great risk of osteoporosis (aHR = 1.40; 95% CI = 1.09–1.80), compared to non-HPV controls; on the other hand, the risk of osteoporosis in HPV-infected patients who received treatments for HPV infections did not reach statistical significance (aHR = 1.14; 95% CI = 0.78–1.66) (Table 4). Overall, treatments for HPV infections attenuated the risk of osteoporosis in patients with HPV infections.

4. Discussion

In this 13-year nationwide population-based retrospective cohort study, there was a 32% increased risk of osteoporosis in patients with HPV infections, which was validated after adjusting for demographic variables, comorbidities, and co-medications. Patients who were women, aged between 60 and 80, of low and of high socioeconomic status, with long-term use of glucocorticoid, were susceptible to HPV-associated osteoporosis. Treatments for HPV infections lowered the risk of HPV-associated osteoporosis in patients with HPV infections.
Studies have shown that virus infections, such as HIV, HBV, HCV, and herpes zoster infections, were independently associated with a higher risk of osteoporosis [10,11]. Collectively, evidence from these studies provided the association between viral infections and the risk of osteoporosis. For instance, it was demonstrated that patients with herpes zoster infections presented with a 4.55-fold greater risk of osteoporosis [12], as associated with significantly high levels of interleukin (IL)-1b, IL-6, IL-8, IL-10, and tumor necrosis factor-alpha (TNF-α) [39]. Among those inflammatory biomarkers, IL-6 was suggested as a potent stimulator of osteoclast-induced bone resorption and thus was central to the pathogenesis of bone loss in the context of chronic inflammation [40]. Likewise, HIV-infected individuals were reported to have lower BMD compared to non-infected controls [41], as supported by a meta-analysis that observed a significant increase in the risk of fractures in HIV-infected individuals with an incidence rate ratio of 1.58 (95% CI = 1.25–2.00) [41]. It was further demonstrated that a B-cell RANKL/osteo-protegerin-driven pathogenesis contributed to the compromised total hip and femoral neck BMD in ART-naïve HIV-infected patients, indicating that B-cell dysregulation promoted HIV-induced bone loss through an imbalance in the RANKL/osteo-protegerin ratio [42]. In the case of HBV infections, patients with HBV infections were shown to present with a significant great risk of osteoporosis [11], which was in accordance with observations that the seropositivity of the surface antigen for hepatitis B in adult men was significantly associated with lower BMD [43]. Chronic HBV infections can induce the production of inflammatory cytokines, such as TNF-α, IL-1, and IL-6, which increases RANKL that stimulates osteo-clastogenesis and bone resorption [44]. Moreover, TNF-α can inhibit osteoblast differentiation and promote osteoblast apoptosis [45], for which HBV infection-associated osteoporosis was proposed to be driven by inflammatory pathways that contributed to decreased bone formation, increased bone resorption, and a subsequently decreased systemic BMD [11].
The exact mechanism of how HPV infections undermined bone loss or osteoporosis has not been studied. However, highly expressed RANKL has been observed during the progression of HPV infection-associated cervical cancer, which was secreted by HPV-infected cells [22]. The excessive production of RANKL released by tumor cells was reported to trigger osteoclast-mediated bone destruction and to increase tumor burden [24]. Subsequently, binding of RANKL to RANK receptors on osteoclasts was found to activate signals for bone resorption [22]. On the other hand, high levels of inflammatory mediators such as TNF-α in patients with HPV infections [46] could place those individuals in an inflammatory microenvironment that may intensify osteoclastic resorption [47] by promoting RANKL production [48], transducing RANKL-induced signal pathways, and amplifying osteo-clastogenesis [47,49]. Specifically, TNF-α, as triggered by infections, promotes osteoblasts apoptosis and reduces osteo-blastogenesis by stimulating DKK-1 and Sost expression [9]. Moreover, TNF-α could suppress osteoblast differentiation by inhibiting Smad signaling through an NF-κB-mediated process [50]. Collectively, osteo-clastogenesis in response to high concentrations of RANKL and TNF-α may explain bone resorption and osteoporosis in patients with HPV infections.
It was found in the present study that treatments for HPV infections attenuated the risk of HPV infections. This finding was in accordance with previous studies on benign lesions of anogenital warts [51], in which medical and surgical therapies were able to alleviate symptoms [52]. For instance, the primary clearance rate of lesions was estimated to be 44–87% for cryotherapy, 89–100% for scissor excision, 94–100% for electrocautery, and close to 100% for laser-assisted surgical treatments [53]. Moreover, as most HPV infections with genital warts could be eradicated within two years in immune-competent patients, early treatments of warts has been shown to exert higher clearance rates and lower incidence of malignancies [54], which may explain the observed beneficial effect of treatments for HPV infections on the reduced the risk of osteoporosis in the present study. However, as treatments may not eradicate all HPV-infected cells, long-term follow-ups for patients with HPV infections would still be necessary. In particular, it was demonstrated that there was a recurrence rate of 20–30% after therapies on HPV-associated wart lesions, which could increase during follow-ups [53]. The recurrence rate of wart lesions after treatments for HPV infections was 12–42% at 1 to 3 months and 59% at 12 months following cryotherapy, 9–29% following scissor excision, 22% following electrocautery, and 17–19% at 3 months and 66% at 12 months following laser surgery [53]. All in all, early treatments for HPV infections and long-term follow-ups were recommended. Clinical implications also included screening [55] in patients with HPV infections and patient education [56,57,58,59,60,61].
The major strength of the present study was the use of longitudinal data of large sample size and a long follow-up duration that was able to provide the temporal association between HPV infections and the risk of new-onset osteoporosis, and the effect of treatments for HPV infections on the attenuated risk of HPV-associated osteoporosis. Findings in the present cohort study were representative of the general population, and potential measurable confounders were balanced through propensity score matching [58,59,60] for demographics, comorbidities, and co-medications. In addition, both the diagnoses of HPV infections and osteoporosis were adjudicated by physicians, which ascertained the accuracy of the diagnoses. The outcome measurement of osteoporosis was further validated via requiring the use of medications for osteoporosis as part of the criteria. In addition, subgroup analyses were used to elucidate effect measure modifications. That said, several limitations exist in this study. First, there could be underestimated cases of HPV infections if there were no clinically recognized lesions, which could have excluded patients with self-resolving or asymptomatic infections from the study population. Second, most of the Taiwanese population are East Asians, so findings of the present study may not be generalizable to other populations. Third, as information on serotypes of HPV, history of HPV vaccinations, and lifestyle determinants such as physical activity were not available in the dataset, further studies are warranted to address whether these factors could alter the risk of HPV-associated osteoporosis. Finally, the differentiation between HPV positivity alone and pre-cancerous lesions are not clarified. A stratified analysis based on the degree of lesion needs further execution.

5. Conclusions

In conclusion, patients with HPV infections were associated with a significantly greater risk of subsequent osteoporosis, especially in female patients, those aged between 60 and 80 years, and individuals with long-term use of glucocorticoids. Treatments for HPV attenuated the risk of HPV-associated osteoporosis. Prospective studies on the association between HPV genotypes and osteoporosis and studies of mechanistic approaches may shed light on HPV-associated bone loss and osteoporosis.

Author Contributions

Conceptualization, R.-i.C., N.-C.C., K.S.-K.M., T.-Y.T. and J.C.-C.W.; methodology, K.S.-K.M. and H.-T.Y.; software, K.S.-K.M. and H.-T.Y.; investigation, R.-i.C., N.-C.C., K.S.-K.M., T.-Y.T. and J.C.-C.W.; resources, H.-T.Y.; writing—original draft preparation, N.-C.C., K.S.-K.M., T.-Y.T. and Y.-C.W.; writing—review and editing, K.S.-K.M. and J.C.-C.W. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

This study is supported in part by Taiwan Ministry of Health and Welfare Clinical Trial Center (MOHW108-TDU-B-212-133004), The study was approved by the Institutional Review Board of China Medical University (IRB permit number: CMUH-104-REC2-115).

Informed Consent Statement

Patient consent was waived by the IRB (approval No. CMUH-104-REC2-115) because NHIRD was a de-identified database.

Data Availability Statement

Data were acquired from the NHIRD in Taiwan. The NHI database was available upon application.


The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Kaplan-Meier curves for the cumulative incidence of new-onset osteoporosis in individuals with or without human papillomavirus infections.
Figure 1. Kaplan-Meier curves for the cumulative incidence of new-onset osteoporosis in individuals with or without human papillomavirus infections.
Viruses 15 01021 g001
Table 1. Baseline characteristics in HPV-infected patients and non-HPV controls.
Table 1. Baseline characteristics in HPV-infected patients and non-HPV controls.
No (N = 51,744)Yes (N = 12,936)
Gender 0.031
Age, year
 mean, (SD)63.13(9.81)63.26(9.87)0.013
Socioeconomic status (Monthly salaries in New Taiwan Dollar)
Out-patient visit frequency mean, (SD)30.8(26.3)32.2(23.8)0.055
 Celiac disease50.0110.010.002
 Vitamin D deficiency170.0330.020.006
 Premature menopause10.00210.010.008
 Male hypogonadism230.0490.070.011
 Adrenal cortical steroids 10.0020-0.006
 Long-term use of glucocorticoids20113.895264.070.009
 Phenobarbital, phenytoin, or carbamazepine3680.71990.770.006
 Heparin or warfarin 4180.811010.780.003
 Cyclosporine 400.0890.070.003
 TCAs or SSRIs 16623.214353.360.008
 Furosemide 14312.773482.690.005
 Thiazide 18163.514573.530.001
 Statin 532710.29133810.340.002
 Beta blockers 968218.71242218.72<0.001
SMD, Standard mean difference; COPD, Chronic obstructive pulmonary disease; IBD, Inflammatory bowel disease; HBV, Hepatitis B virus; HCV, Hepatitis C virus; HIV, Human Immunodeficiency Virus; RA, Rheumatoid arthritis; CKD, Chronic kidney disease; TCAs, Tricyclic antidepressants; SSRIs, Selective serotonin receptor inhibitors; PPIs, proton pump inhibitors.
Table 2. Factors associated with a diagnosis of osteoporosis in the Cox proportional hazard models.
Table 2. Factors associated with a diagnosis of osteoporosis in the Cox proportional hazard models.
VariablenPYIRcHR(95% CI)aHR(95% CI)
HPV infections
 non-HPV277302,9470.911.00 1.00
 HPV11691,8931.261.33(1.07, 1.65) *1.32(1.06, 1.65) *
 Female315197,5331.591.00 1.00
 Male78197,3070.400.25(0.19, 0.32) ***0.23(0.18, 0.3) ***
Age, year
 50–6051196,3240.261.00 1.00
 60–70150114,2441.315.04(3.67, 6.92) ***4.29(3.10, 5.93) ***
 70–8015168,3702.219.05(6.59, 12.4) ***7.32(5.23, 10.26) ***
 >804115,9022.5812.7(8.42, 19.3) ***9.63(6.22, 14.88) ***
Socioeconomic status (Monthly salaries in New Taiwan Dollar)
 <20,000249195,4131.271.00 1.00
 20,001–40,000137132,9881.030.79(0.64, 0.98) *1.06(0.86, 1.32)
 >40,000766,4390.110.08(0.04, 0.18) ***0.30(0.14, 0.64) **
Out-patient visit frequency 1.02(1.01, 1.02)1.01(1.01, 1.01) ***
  No126179,6757.011.00 1.00
  Yes267215,16512.411.89(1.53, 2.34) ***0.88(0.69, 1.12)
  No237275,7138.601.00 1.00
  Yes156119,12713.101.63(1.33, 2.00) ***1.00(0.8, 1.24)
  Yes159138,34311.491.47(1.20, 1.81) ***0.98(0.77, 1.24)
  Yes152100,61215.112.10(1.71, 2.58) ***1.35(1.08, 1.68) **
  Yes1316,9317.680.86(0.50, 1.50)
  Yes916,7145.380.62(0.32, 1.2)
  Yes8754110.611.25(0.62, 2.52)
  Yes180175,32210.271.13(0.92, 1.37)
 Celiac disease
  Yes0330.000.00(0, Inf)
  Yes3322,88914.421.66(1.16, 2.37) **0.99(0.69, 1.43)
  Yes2413,70117.522.11(1.39, 3.19) ***1.22(0.8, 1.88)
  Yes114307.000.80(0.11, 5.68)
  Yes03790.000.00(0, Inf)
  Yes050.000.00(0, Inf)
  Yes09830.000.00(0, Inf)
  Yes1714,17811.991.37(0.84, 2.23)
  Yes142923.332.65(0.37, 18.87)
 Vitamin D deficiency
  Yes110595.2310.4(1.45, 73.69) *18.3(2.56, 131.09) **
 Premature menopause
  Yes0180.000.00(0, Inf)
 Male hypogonadism
  Yes01760.000.00(0, Inf)
 Adrenal cortical steroids
  Yes000.00NA(NA, NA)NA
  Yes230496.560.88(0.22, 3.56)
  Yes410,7953.710.44(0.16, 1.17)
 Long-term use of glucocorticoids
  Yes3812,56830.243.47(2.48, 4.85) ***2.05(1.44, 2.92) ***
 Phenobarbital, phenytoin, or carbamazepine
  Yes5262219.071.98(0.82, 4.79)
 Heparin or warfarin
  Yes3229513.071.51(0.49, 4.71)
  Yes02820.000.00(0, Inf)
 TCAs or SSRIs
  Yes2510,25124.392.79(1.86, 4.19) ***1.60(1.05, 2.43) *
  Yes10790012.661.64(0.87, 3.08)
  Yes17727623.372.84(1.74, 4.62) ***1.14(0.69, 1.91)
  Yes2412,72218.862.05(1.36, 3.10) ***1.13(0.74, 1.74)
  Yes4429,55614.891.86(1.35, 2.55) ***1.23(0.87, 1.73)
 Beta blockers
  Yes8668,20512.611.40(1.10, 1.78) **0.85(0.65, 1.10)
PY, person-year; IR, Incidence rate; cHR, Crude Hazard ratio; aHR, Adjust Hazard ratio; OPD, Out-patient department; COPD, Chronic obstructive pulmonary disease; IBD, Inflammatory bowel disease; HBV, Hepatitis B virus; HCV, Hepatitis C virus; HIV, Human Immunodeficiency Virus; RA, Rheumatoid arthritis; CKD, Chronic kidney disease; TCAs, Tricyclic antidepressants; SSRIs, Selective serotonin receptor inhibitors; PPIs, proton pump inhibitors; *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Table 3. Subpopulations at risk of HPV-associated osteoporosis in patients with HPV infections.
Table 3. Subpopulations at risk of HPV-associated osteoporosis in patients with HPV infections.
VariableNPYIRnPYIRcHR(95% CI)aHR(95% CI)
 Female227154,01814.78843,51420.21.33(1.04,1.70) *1.33(1.04,1.71) *
 Male50148,9283.42848,3785.81.65(1.04,2.62) *1.29(0.80,2.08)
Age, year
 60–7010788,26312.14325,98016.61.28(0.90,1.83)1.45(1.01,2.08) *
 70–809749,29519.75419,07528.31.33(0.95,1.86)1.51(1.07,2.12) *
Socioeconomic status (Monthly salaries in New Taiwan Dollar)
 <20,000167146,30711.48249,10616.71.39(1.06,1.81) *1.32(1.01,1.73) *
 >40,000249,8320.4516,6073.07.47(1.45,38.56) *8.22(1.59,42.38) *
  No86139,0086.24040,6679.81.56(1.07,2.26) *1.50(1.02,2.20) *
  No163212,6197.77463,09411.71.48(1.13,1.95) **1.42(1.07,1.88) *
  No171227,3447.57066,88310.51.35(1.02,1.78) *1.41(1.06,1.87) *
  No26729,02469.211387,66212.91.35(1.08,1.68) **1.36(1.09,1.70) **
  No271290,4259.311387,70012.91.33(1.07,1.65) *1.33(1.07,1.67) *
  No272297,3539.111389,94512.61.32(1.06,1.64) *1.33(1.06,1.66) *
  No143168,6178.57050,90013.81.58(1.19,2.11) **1.58(1.18,2.12) **
  No250285,6168.811086,33412.71.40(1.12,1.75) **1.40(1.12,1.76) **
  No259292,5918.911088,54712.41.35(1.08,1.68) **1.34(1.07,1.68) *
  No263292,2249.011388,43712.81.36(1.09,1.70) **1.37(1.10,1.72) **
  No275294,9149.311489,13012.81.32(1.06,1.64) *1.32(1.06,1.65) *
 Long-term use of glucocorticoids
  No254293,6798.610188,59211.41.26(1.00,1.59) *1.27(1.00,1.6) *
  Yes23926824.815330045.41.75(0.91,3.35)2.17(1.11,4.22) *
 Phenobarbital, phenytoin, or carbamazepine
  No273301,0239.111591,19412.61.34(1.07,1.66) **1.35(1.08,1.68) **
 Heparin or warfarin
  No274301,2129.111691,33212.71.34(1.08,1.66) **1.35(1.08,1.68) **
 TCAs or SSRIs
  No259295,5648.810989,02512.21.34(1.07,1.68) **1.35(1.08,1.70) **
  No270297,1509.111389,78912.61.33(1.07,1.66) *1.34(1.07,1.67) *
  No266297,4588.911090,10512.21.31(1.05,1.64) *1.31(1.04,1.64) *
  No262293,2458.910788,87212.01.29(1.03,1.62) *1.30(1.03,1.63) *
  No246280,7488.810384,53512.21.34(1.06,1.68) *1.36(1.07,1.71) *
 Beta blockers
  No210251,6188.39775,01612.91.50(1.18,1.91) **1.49(1.17,1.91) **
PY, person-year; IR, Incidence rate; cHR, Crude Hazard ratio; aHR, Adjust Hazard ratio; OPD, Out-patient department; COPD, Chronic obstructive pulmonary disease; IBD, Inflammatory bowel disease; HBV, Hepatitis B virus; HCV, Hepatitis C virus; HIV, Human Immunodeficiency Virus; RA, Rheumatoid arthritis; CKD, Chronic kidney disease; TCAs, Tricyclic antidepressants; SSRIs, Selective serotonin receptor inhibitors; PPIs, proton pump inhibitors; *, p < 0.05; **, p < 0.01.
Table 4. Risk of osteoporosis in HPV-infected patients with or without treatments for HPV infections.
Table 4. Risk of osteoporosis in HPV-infected patients with or without treatments for HPV infections.
VariablenPYIRcHR(95% CI)aHR(95% CI)
Non-HPV277302,9470.911.00 1.00
Treatment for HPV infections
  with treatment †3132,5460.951.18(0.81,1.71)1.14(0.78,1.66)
  without treatment *8559,3461.431.39(1.09,1.77) **1.40(1.09,1.80) **
PY, person-year; IR, Incidence rate; cHR, Crude Hazard ratio; aHR, Adjust Hazard ratio. † “with treatment” group: HPV infected patients received any HPV-related treatment procedures (Cryotherapy, Electrocautery, Excision, Laser surgery) within three months after the index date. * “without treatment” group: HPV infected patients received no HPV-related treatment procedures or any procedures beyond three months after the index date; **, p < 0.01.
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Ma, K.S.-K.; Chin, N.-C.; Tu, T.-Y.; Wu, Y.-C.; Yip, H.-T.; Wei, J.C.-C.; Chang, R.-i. Human Papillomavirus Infections and Increased Risk of Incident Osteoporosis: A Nationwide Population-Based Cohort Study. Viruses 2023, 15, 1021.

AMA Style

Ma KS-K, Chin N-C, Tu T-Y, Wu Y-C, Yip H-T, Wei JC-C, Chang R-i. Human Papillomavirus Infections and Increased Risk of Incident Osteoporosis: A Nationwide Population-Based Cohort Study. Viruses. 2023; 15(4):1021.

Chicago/Turabian Style

Ma, Kevin Sheng-Kai, Ning-Chien Chin, Ting-Yu Tu, Yao-Cheng Wu, Hei-Tung Yip, James Cheng-Chung Wei, and Ren-in Chang. 2023. "Human Papillomavirus Infections and Increased Risk of Incident Osteoporosis: A Nationwide Population-Based Cohort Study" Viruses 15, no. 4: 1021.

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