https://orcid.org/0009-0008-6832-2731
Figures
Abstract
Background
Bone mineral density is an important indicator of osteoporosis, and its variation with volatile organic compounds exposure has rarely been studied. However, the relationship between chloroform (an essential volatile organic compounds component) and bone mineral density remains unclear. Consequently, we aimed to explore the relationship between chloroform alone and bone mineral density or bone mineral content.
Methods
Herein, 2,553 individuals aged 18 and above from the National Health and Nutrition Examination Surveys (NHANES) in 2009–2010, 2013–2014, and 2017–2020, were included. We employed two independent t-tests and multi-linear regression models to statistically assess the relationship between chloroform exposure and BMD/BMC in the spine and femoral area.
Results
A "V"-shaped correlation between chloroform exposure and bone mineral density or bone mineral content (BMD/BMC) was observed in the unadjusted model, particularly in the Ward’s triangle and femoral neck as a whole. A negative correlation was specifically observed for the Ward’s triangle BMD/BMC and L4 BMD/BMC. On the other hand, in the adjusted model, a dominantly negative correlation between the L4 BMC and chloroform exposure was observed over a range of exposure levels. The subgroup analysis revealed a negative correlation between chloroform concentrations and BMC in the femur and spine, especially in women and the 65–80 age population.
Citation: Li L, Liu X, Zhang X, Zhang Y, Li Q, Geng H, et al. (2024) Chloroform associated with bone mineral density and bone mineral content in adults: A population-based cross-sectional research. PLoS ONE 19(3): e0290132. https://doi.org/10.1371/journal.pone.0290132
Editor: Raffaele Vitiello, Policlinico Universitario A. Gemelli IRCCS - Universita Cattolica del Sacro Cuore Roma, ITALY
Received: August 1, 2023; Accepted: November 21, 2023; Published: March 1, 2024
Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This work was financially supported by the Xuzhou Medical University Affiliated Hospital Development Fund (XYFZ2020008), the China International Medical Exchange Foundation Endocrinology and Metabolism Elite Research Fund (2021-N-03), and the National Nature Science Foundation of China (NSFC-81870534). The funders had no role in research design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Osteoporosis is a frequent bone disease characterized by reduced bone volume, microstructural degeneration, and fragility fractures [1]. Fragility fractures, particularly in the most vulnerable areas, including the vertebrae, hip, and forearm, are one of the severe complications of osteoporosis. According to reports [2, 3], fragility fractures can cause emotional distress, reduced quality of life, and an increased socioeconomic burden. Approximately 79,000 people in the United Kingdom suffer hip fractures annually, with the cost in 2010 estimated at £3.5 billion and expected to rise to £5.5 billion each year by 2025, implying that osteoporosis will be a significant challenge in the future and its burden on the medical community must be removed [4]. According to osteoporosis research, enhancing Bone Mineral Density (BMD) is closely linked to decreasing the risk of vertebral and non-vertebral fractures [5]. Many factors, including aging, femininity, estrogen metabolism disturbances, and physical inactivity, are critical in lowering BMD and have been implicated in the pathogenesis of osteoporosis [6, 7].
People are frequently exposed to Volatile Organic Compounds (VOCs) such as chloroform, bromoform, dibromochloromethane, and dichlorobromomethane. The increased contact is due to the widespread use of disinfectants, as these VOCs are produced when disinfectants react with organic substances in water sources [8–10]. Compared to normal mice, the U.S. National Toxicology Program noted an increased incidence of sternal dysplasia in bromoform-exposed mice [11]. Other studies discovered a connection between VOCs exposure and bone-healing-related chemokines, with a downregulated osteoblast chemokine CXCL12 expression after exposure to benzene or its derivatives, and that CCL2 (a chemokine essential for osteoclast formation) production was induced by chlorobenzene exposure [12–14]. These findings imply that VOCs could impact BMD levels by affecting osteoblast activity. Additionally, individual and combined VOCs exposure was found to be associated with lower BMD in U.S. adults, and Alkaline Phosphatase (ALP), Body Mass Index (BMI), Fasting Insulin (F.I.), and High-Density Lipoprotein (HDL) were shown to be intermediaries in VOCs and BMD co-exposure [15]. Chloroform, a significant member of VOCs, is strongly absorbed through the pulmonary, oral, and dermal pathways and is linked with several acute and chronic illnesses, including neurological, respiratory, hepatic, and renal dysfunctions, reproductive abnormalities, and digestive or urinary malignancies [16, 17]. However, the connection between blood chloroform and BMD/BMC was rarely investigated alone in past studies.
This research aimed to explore the relationship between blood chloroform and BMD/BMC using data from the National Health and Nutrition Examination Survey (NHANES). We, therefore, obtained femur BMD/BMC and spine BMD/BMC datasets published in 2009–2010, 2013–2014, and 2017–2020 from NHANES.
Materials and methods
Study design and participants
Herein, data from the NHANES, a cross-sectional survey of more than 5,000 respondents conducted yearly by the Center for Disease Control and Prevention’s (CDC) Center for Health Statistics, was used. We specifically used NHANES data from 2009–2010, 2013–2014, and 2017–2020. We selected 22,333 adults (of whom 6,227 had blood chloroform data) from 36,272 available subjects. Subsequently, 2637 individuals with femur and spine Dual-Energy X-ray Absorptiometry (DEXA) data were selected. After excluding patients with a history of osteoporosis treatment, 2553 subjects aged ≥18 years were included in the final statistical analysis. The Ethics Review Committee of the National Center for Health Statistics approved all protocols and all participants were informed of the details of the poll and signed an informed consent form. Fig 1 depicts the flowchart for participant exclusion.
Variables
In this study, we used blood chloroform concentration as the exposure variable. Chloroform concentration in the blood was analyzed using Capillary Gas Chromatography (G.C.) and Mass Spectrometry (M.S.) with Selected Ion Monitoring (SIM) detection and isotope dilution. The chloroform detection limits ranged from 0.00148 to 0.602 ng/ml, and for lower LLOD (Lower Limit of Detection) values, an interpolated LLOD value divided by the square root of 2 was used. The dependent variables were the femoral and spinal Bone Mineral Density (BMD) and Bone Mineral Content (BMC). In Shepherd’s laboratory, Dual-Energy X-ray Absorptiometry (DXA) was used to measure the spine and femur BMC, whereas the Hologic software APEX v4.0 (Hologic) sector beam densitometry was used to scan and calculate the spine and femur BMC and BMD. All variables included as covariates in the study are listed below: Sex (male, female), ancestry (Mexican-American, Non-Hispanic white, Non-Hispanic black, other Hispanic, other), Household Poverty-Income Ratio (PIR by poverty line: values 0 to 0.99 indicate below poverty, ≥1.00 indicate poverty or above poverty) [18], Excessive alcohol consumption (>1 drink /day for women or >2 drinks /day for men (in the past 12 months)), Hypertension (blood pressure ≥140/90 mmHg or taking anti-hypertensive medication), Diabetes mellitus (self-reported diabetes history, Fasting Blood Glucose (FPG) level ≥7.0 mmol/L, HbA1c ≥6.5% or taking anti-diabetic medication), Arthritis, Cardiovascular disease (self-reported congestive heart failure, coronary artery disease, heart attack or stroke history), Thyroid problems (self-reported hyperthyroidism, hypothyroidism, thyroiditis), COPD(Chronic Obstructive Pulmonary Disease), Smoking (self-described as having smoked ≥100 cigarettes in a lifetime), History of osteoporosis treatment and osteopenia (Bone Mineral Density (BMD) T-score ≤ -2.5 in lumbar spine or femoral neck) [19]. Age, body weight, abdominal circumference, and BMI were all continuous covariates in our analysis. The blood chloroform, BMD, BMC, and covariance data were obtained from the NHANES website.
Statistical analysis
Statistical analyses were conducted using R software (version 3.6.1), IBM SPSS version 25(IBM, Armonk, New York, USA), and GraphPad Prism9. The mean and Standard Deviation (S.D.) values were used for variables with continuous features, whereas categorical variable represented frequency. The Spearman correlation test was used to assess differences between the classification variables in the exposure group. The Kruskal-Wallis test or one-way ANOVA was used to examine differences in continuous variables between groups. Blood chloroform levels were grouped into tertiles (tertile 1: <33%, tertile 2: 33–66%, tertile 3: >66%) and univariate and multivariate linear regression models were tested to analyze the relationship between the different blood chloroform categories. We adjusted the confounding variables in the multi-linear regression model to investigate the correlation between blood chloroform levels and BMD/BMC (femoral and spine). These included Model 1 (the unprecedented model), Model 2 (for sex, age, ancestry, and BMI adjustment), and Model 3 (for sex, age, ancestry, BMI, osteoporosis, COPD, and thyroid problems adjustments, and further adjustment for arthritis, smoking and excessive drinking). Regression analysis results were expressed as β (beta) coefficients, 95% confidence intervals, and statistically significant P values (P values<0.05).
Results
Subject characteristics
This study had 2553 participants (1288 women and 1265 men). Based on the femoral and spinal DEXA data, the average age of the participants and the average chloroform levels in their whole blood was 48.83 years and 0.0171 ± 0.0182 ng/mL (ranging from 0.0021 to 0.1790 ng/mL), respectively. The weighted characteristics of these participants based on the third-class classification are shown in S1 Table. According to the femoral and spine DEXA data, differences among groups in baseline variables such as age, ancestry, height, BMI, waist circumference, hypertension, arthritis, thyroid illnesses, and smoking were statistically significant (P<0.05).
Connection between chloroform and BMD
Tables 1 and 2 and S2 Table illustrate the results. Blood chloroform concentration by tertile had a statistically significant relationship with total femoral BMD (P < 0.05); femoral neck BMD (P < 0.01); rotor BMD (P < 0.05); inter-rotor BMD (P < 0.05); Ward’s triangle BMD (P < 0.01); and L4 BMD (P < 0.01).
The multiple linear regression models and weighted univariate analyses are detailed in Tables 1 and 2. All regressions were conducted before adjusting for some of the covariates (model 1), except for total spine BMD (β -0.0020; 95% CI -0.0051, 0.0011), L1 BMD (β 0.0004; 95% CI -0.0030, 0.0039), L2 BMD (β - 0.0024; 95% CI -0.0057, 0.0009), and L3 BMD (β -0.0016; 95% CI -0.0048, 0.0016). A statistically significant correlation existed between increased blood chloroform concentration and total femoral BMD, femoral neck BMD, rotor BMD, inter-rotor BMD, Ward’s triangle BMD, and L4 BMD (P<0.05). The L4 BMD was negatively correlated with blood chloroform levels after adjusting for some covariates (model 2). After adjusting for more relevant covariates simultaneously (model 3), L4 BMD decreased with rising blood chloroform levels, but not at other sites.
Connection between chloroform and BMC
Detailed results are presented in Tables 1 and 2 and S2 Table. Weighted univariate and multiple linear regression analyses are illustrated in Tables 1 and 2. In model 1, blood chloroform levels were categorized by tertile, except for rotor BMC (β -0.0023; 95% CI -0.0066, 0.0021), and L1 BMC (β -0.0004; 95% CI -0.0058, 0.0049). There was a negative correlation between increased blood chloroform concentrations and BMC at several sites, including total femoral BMC, femoral neck BMC, Intertrochanter BMC, Ward’s triangle BMC, total spine BMC, L2 BMC, L3 BMC, and L4 BMC. Additionally, increased blood chloroform concentrations in the femur and spine were negatively correlated with BMC (P < 0.05). The L3 BMC and L4 BMC were negatively correlated with blood chloroform levels after adjusting for some covariates (model 2). Finally, in model 3, L3 BMC and L4 BMC decreased with increasing blood chloroform concentration.
Subgroup analysis
The findings of subgroup analyses adjusted for associated covariates are shown in Tables 3–5. According to the Multiple regression analysis in the femoral area, the femoral neck BMC blood chloroform level decreased in the male sex (β -0.0059; 95% CI -0.0115, -0.0002; P <0.05). According to the analysis by ancestry as a subgroup, the femoral neck BMD/BMC in Non-Hispanic White and other Ancestry -Including Multi-Racial subjects exhibited a negative correlation with blood chloroform concentration (P<0.05). In contrast, no meaningful correlation between blood chloroform and BMD or BMC was observed in Mexican-American, Non-Hispanic Black, and Other Hispanic subjects. A negative correlation between blood chloroform and femoral neck BMD/BMC was revealed by the results stratified by age but only in the 65–80 years-old participants (β -0.0100; 95% CI -0.0186, -0.0014; P<0.05); (β -0.0144; 95% CI -0.0234, -0.0054; P<0.05).
Results of the multiple regression analysis of Ward’s triangle region revealed that stratified by sex, female Ward’s triangle BMD decreased while chloroform levels increased and that female Ward’s triangle BMC was negatively correlated with chloroform. According to the results stratified by ancestry, blood chloroform concentration was negatively correlated with BMD/BMC except for Hispanic white subjects (β -0.0124; 95%CI -0.0224, -0.0024; P<0.05); (β -0.0136; 95% CI -0.0244, -0.0027; P<0.05). Additionally, although BMC was not statistically significant, chloroform concentrations were correlated with BMD in Mexican-American, Other Hispanic, Non-Hispanic Black and Other Ancestry -Including Multi-Racial participants. The results stratified by age revealed no statistically significant association between chloroform concentrations and BMD and BMC at all femoral sites in all age groups.
Female L4 BMC decreased with increasing blood chloroform in the spinal region following stratification by sex (β -0.009; 95% CI -0.0149, -0.0022; P<0.01). When stratified by ancestry, we discovered a significant correlation between Non-Hispanic White BMC and blood chloroform (β -0.0078; 95% CI -0.0152, -0.0005; P<0.05). Additionally, there was a significant negative correlation between BMC and chloroform in the 45–65 and 65–80 age groups when age was used as a stratification factor (β -0.0073; 95% CI -0.0145, -0.0001; P<0.05); (β -0.0154; 95% CI -0.0282, -0.0026; P< 0.05).
Discussion
Osteoporosis is a degenerative bone disease that increases the risk of fracture [20]. With the aging population, osteoporosis is becoming a major public health concern worldwide [21, 22]. The current era of rapid global economic development characterized by various industrial processes, including increased production of automobiles, tobacco, cleaning products, building materials, and other household products, has made VOCs more common in the human environment [23–27]. Several studies have demonstrated that some VOCs, such as Perfluoro and Polyfluoroalkyl Substances (PFAS), Urinary Polycyclic Aromatic Hydrocarbons (UPAHs), trichlorophenol, and many other organics are negatively associated with BMD/BMC levels at specific sites in the human body [28–30]. The safety of urban centralized water supply largely relies on water disinfection as it kills pathogens and prevents waterborne infectious diseases. However, water Disinfection Byproducts (DBPs) mostly contain certain VOCs, including chloroform, bromine, dibromochloromethane, and dichlorobromomethane, with chloroform presence being exceptionally high in these DBPs. A survey specifically focused on chloroform was conducted in China to evaluate the health risks associated with municipal water supply. It analyzed the distribution pattern and seasonal chloroform variation characteristics in the municipal water supply in Xi’an and the average daily chloroform exposure dose. According to the results, the average daily exposure dose of chloroform in the Xi’an municipal water supply was 7.39*10^-4 mg/(kg*d), with drinking water consumption as the leading source for the non-carcinogenic risk of chloroform. Another survey found that the carcinogenic risk of ten contaminants in city drinking water, including chloroform, exceeded the acceptable level. All these studies indicate that chloroform could potentially harm human health, but no conclusive study has proven the dangers of chloroform exposure to public safety. Although some studies have associated chloroform co-exposure with bone health indicators [15], no link with BMD has been reported. In our study, we hypothesize that there could be a connection between blood chloroform and BMD/BMC. After adjusting for confounders, we discovered a negative correlation between BMD/BMC and blood chloroform in L3 BMC and L4 BMD/BMC. Our analysis revealed a negative association between chloroform and femoral neck BMD in participants aged 65–80 years and Non-Hispanic White subjects, as well as Ward’s triangle BMD in women and Non-Hispanic White subjects. For BMC, a negative correlation was found between blood chloroform and femoral neck BMC, Non-Hispanic White and Other Ancestry-Including Multi-Racial subjects femoral neck BMC, female Ward’s triangular BMC, Ward’s Triangular BMC of female Non-Hispanic White and 65–80 years old subjects, Female L4 and Non-Hispanic White Subjects BMC, and L4 BMC of 45–65 years and 65–80 years old subjects.
Multiple linear regression analysis and analysis within the Asian group revealed the relationship between blood chloroform and BMD/BMC in most areas of the femur and spine before adjusting for confounding factors. However, after adjusting for confounding variables, it was discovered that the correlation between blood chloroform and femoral BMD/BMC was not as strong. This finding implies that the relationship between blood chloroform and femoral BMD/BMC is largely influenced by age, sex, and ancestry. On the one hand, this phenomenon may be attributed to femur and lumbar spine structures, which theoretically have the most substantial BMD changes in postmenopausal women with a higher proportion of cancellous bone [31–33]. On the other hand, it could be attributed to the sample population’s old age (48.8 ± 16.8 years), where hormonal drugs used by some older individuals exert a greater influence on femoral BMD/BMC than on lumbar spine BMD/BMC, making blood chloroform less likely to be associated with femoral BMD/BMC [34]. Furthermore, after adjusting for relevant covariates, stratified analysis by age, sex, and ancestry revealed that chloroform concentration was negatively correlated with BMC at most sites. Blood chloroform concentration at L4 was significantly negatively correlated with BMC in women in the subgroup analysis. Contrastingly, no correlation between chloroform concentration and femoral or spinal BMC was observed in men, implying that blood chloroform levels may have some predictive value for bone mass in women. This phenomenon may be attributed to the sample population’s older age (48.8 ± 16.8 years) and the substantial decline in sex hormone levels in postmenopausal women resulting in lower femoral BMD quantity. Men, on the other hand, showed no such specific changes. We hypothesized that the varying sex hormone levels might influence the femoral neck, Ward’s triangle, or L4 BMC differently. Furthermore, the association between blood chloroform and femoral and spinal BMC was closer than that of BMD, which may be explained by the significant variations in the bone area resulting from individual differences.
Both BMD and BMC have been shown by studies to be significant osteoporosis indicators and to play a critical role in osteoporotic fracture development [35]. Our study revealed a negative correlation between blood chloroform in some spine regions and BMD/BMC. Chloroform is used as a solvent to soften material during endodontic treatment, and case studies revealed that during the patients’ endodontic retreatment visit, chloroform was extruded through the perforation into the periodontal ligament space, resulting in necrosis of the tooth-supporting bone [36]. Our findings on the negative effect of chloroform on bone loss are consistent with another research which discovered that organochlorine contaminants-exposure could impact fertility, the menstrual cycle, and other aspects of the human reproductive system [37, 38]. In a pharmaceutical company, female personnel exposed to a mixture of organic solvents (including chloroform) exhibited higher Thyroid-Stimulating Hormone (TSH) levels than the non-exposed group, with a significant correlation between chloroform and TSH levels [39]. According to some clinical studies, a positive correlation exists between TSH and femoral and spinal BMD in early postmenopausal women [40]. Consequently, we speculate that chloroform may have a positive association with BMD/BMC mediated by hormones in vivo, and this hypothesis is supported by the "V"-shaped correlation between chloroform, and BMD/BMC discovered in our study (Figs 2 and 3). Additionally, we hope to find the link between chloroform and bone metabolism through preliminary data analysis and further basic research. In this regard, our group has already started collecting environmental exposure samples and establishing a sample bank.
Sex, age, ancestry (Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, other ancestries), BMI, smoking, alcohol consumption, arthritis, COPD, history of osteoporosis, thyroid problems were adjusted.
Sex, age, ancestry (Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, other ancestries), BMI, smoking, alcohol consumption, arthritis, COPD, history of osteoporosis, thyroid problems were adjusted.
With this cross-sectional research, we plan to further explore the effect of chloroform exposure on BMD/BMC. Herein, we used raw data on blood chloroform and femoral and spinal BMD/BMC from adults selected from NHANES in 2009–2010, 2013–2014, and 2017–2020 to perform a Restricted Cubic Splines (RCS) analysis of the relationship between chloroform and BMD/BMC. The non-linear connection between blood chloroform and spinal BMD/BMC revealed a "V" shaped correlation and a statistically significant association between chloroform levels within the 0–0.02 ng/ml range and spinal BMD/BMC (Figs 2 and 3). According to the literature review in some studies, chloroform harms BMD/BMC. Contrastingly, some studies suggest that chloroform may have a positive association with BMD/BMC. However, no specific reference in the literature demonstrates a clear connection between chloroform and BMD/BMC; thus, more research is required to determine the optimal level of chloroform exposure in relation to BMD/BMC levels. The above findings imply that exposure to VOCs such as chloroform remains a major public health concern. Disinfection byproducts are ubiquitous, and people (particularly older adults) with prolonged exposure to the chloroform from these products must be especially aware of their long-term risks.
Limitation
Our study had several limitations. First, the data used in this investigation was obtained from NHANES, and therefore it was difficult to establish the exact timing between chloroform exposure and changes in BMD. Consequently, we could only develop correlations but not causality at this point. More research through prospective studies is therefore required to investigate this further. Second, our data on subjects were primarily from a single time point, making it difficult to determine the association between chloroform and BMD/BMC over time, potentially leading to bias in classifying specific populations. Third, some data were from self-reported questionnaires, which may have resulted in recall or misclassification bias. Fourth, missing whole-body skeletal BMD/BMC data impeded a comprehensive examination of the chloroform and BMD/BMC correlation. Finally, the residual confounding problem persisted despite employing multivariate adjustment techniques. We are developing a cohort of VOCs exposure (including chloroform) in our city and expect that more convincing evidence elucidating the link between chloroform and BMD/BMC will soon be available.
Conclusion
After adjustment for confounders, we established a "V" shaped correlation between blood chloroform and femoral spine BMD/ BMC, with a negative correlation at 0–0.02 ng/ml (p<0.05), especially for L4 BMC. Our research provides epidemiological evidence for further investigation into the correlation between chloroform and BMD/ BMC.
Supporting information
S1 Table. Related demographic characteristics of participants included in NHANES from 2009 to 2010 and 2013 to 2014 and 2017–2020.
Means with standard deviation (SD) were used for continuous characteristic variables and categorical variables were expressed as frequencies. Differences in categorical variables between exposed groups were analyzed by Kruskal Wallis test or Mann Whitney test. Spearman correlation analysis was used to analyze the differences of continuous variables between groups.
https://doi.org/10.1371/journal.pone.0290132.s001
(XLSX)
S2 Table. Blood chloroform and area, BMC, and BMD based on chloroform tristimulus.
Data are expressed as means (standard deviation, SD). BMC, bone mineral content, BMD, bone mineral density, Area (cm2), BMC (g), BMD (g/cm2).
https://doi.org/10.1371/journal.pone.0290132.s002
(XLSX)
Acknowledgments
This thesis would not have been possible without the consistent and valuable reference materials that I received from my supervisor whose insightful guidance and enthusiastic encouragement in the course of my shaping this thesis definitely gains my deepest gratitude.
References
- 1. Lane JM, Russell L, Khan SN. Osteoporosis. Clinical orthopaedics and related research. 2000(372):139–50. pmid:10738423
- 2. Farrah Z, Jawad AS. Optimising the management of osteoporosis. Clinical medicine (London, England). 2020;20(5):e196–e201. pmid:32934064
- 3. Zhang R, Huang Q, Su G, Wei M, Cui Y, Zhou H, et al. Association between multiple vitamins and bone mineral density: a cross-sectional and population-based study in the NHANES from 2005 to 2006. BMC musculoskeletal disorders. 2023;24(1):113. pmid:36765290
- 4. Clynes MA, Harvey NC, Curtis EM, Fuggle NR, Dennison EM, Cooper C. The epidemiology of osteoporosis. British medical bulletin. 2020;133(1):105–17. pmid:32282039
- 5. Bouxsein ML, Eastell R, Lui LY, Wu LA, de Papp AE, Grauer A, et al. Change in Bone Density and Reduction in Fracture Risk: A Meta-Regression of Published Trials. Journal of bone and mineral research: the official journal of the American Society for Bone and Mineral Research. 2019;34(4):632–42. pmid:30674078
- 6. Levin VA, Jiang X, Kagan R. Estrogen therapy for osteoporosis in the modern era. Osteoporosis international: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2018;29(5):1049–55. pmid:29520604
- 7. Chen LR, Hou PH, Chen KH. Nutritional Support and Physical Modalities for People with Osteoporosis: Current Opinion. Nutrients. 2019;11(12). pmid:31757101
- 8. Li AJ, Pal VK, Kannan KJEC, Ecotoxicology. A review of environmental occurrence, toxicity, biotransformation and biomonitoring of volatile organic compounds. 2021.
- 9. McGraw KE, Riggs DW, Rai S, Navas-Acien A, Xie Z, Lorkiewicz P, et al. Exposure to volatile organic compounds—acrolein, 1,3-butadiene, and crotonaldehyde—is associated with vascular dysfunction. Environmental research. 2021;196:110903. pmid:33636185
- 10. Wei C, Chen Y, Yang Y, Ni D, Huang Y, Wang M, et al. Assessing volatile organic compounds exposure and prostate-specific antigen: National Health and Nutrition Examination Survey, 2001–2010. Frontiers in public health. 2022;10:957069. pmid:35968491
- 11. NTP Toxicology and Carcinogenesis Studies of Methyl Bromide (CAS: 74-83-9) in B6C3F1 Mice (Inhalation Studies). National Toxicology Program technical report series. 1992;385:1–212. pmid:12637959
- 12. Smith JT, Schneider AD, Katchko KM, Yun C, Hsu EL. Environmental Factors Impacting Bone-Relevant Chemokines. Frontiers in endocrinology. 2017;8:22. pmid:28261155
- 13. Lehmann I, Röder-Stolinski C, Nieber K, Fischäder G. In vitro models for the assessment of inflammatory and immuno-modulatory effects of the volatile organic compound chlorobenzene. Experimental and toxicologic pathology: official journal of the Gesellschaft fur Toxikologische Pathologie. 2008;60(2–3):185–93. pmid:18514500
- 14. Fischäder G, Röder-Stolinski C, Wichmann G, Nieber K, Lehmann I. Release of MCP-1 and IL-8 from lung epithelial cells exposed to volatile organic compounds. Toxicology in vitro: an international journal published in association with BIBRA. 2008;22(2):359–66. pmid:17993253
- 15. Zhou HL, Su GH, Zhang RY, Di DS, Wang Q. Association of volatile organic compounds co-exposure with bone health indicators and potential mediators. Chemosphere. 2022;308(Pt 1):136208. pmid:36041527
- 16. Batterman S, Su FC, Li S, Mukherjee B, Jia C. Personal exposure to mixtures of volatile organic compounds: modeling and further analysis of the RIOPA data. Research report (Health Effects Institute). 2014(181):3–63. pmid:25145040
- 17. Toxicity of chloroform. Prescrire international. 1998;7(37):149. pmid:10915422
- 18. Cui Y, Zhou HL, Wei MH, Song WJ, Di DS, Zhang RY, et al. Multiple vitamin co-exposure and mortality risk: A prospective study. Clinical nutrition (Edinburgh, Scotland). 2022;41(2):337–47. pmid:34999328
- 19. Lee S, Ko K, Shin S, Park HS, Hong N, Rhee Y. Adipopenia is associated with osteoporosis in community-dwelling non-underweight adults independent of sarcopenia. Archives of osteoporosis. 2023;18(1):44. pmid:36949274
- 20. Song S, Guo Y, Yang Y, Fu D. Advances in pathogenesis and therapeutic strategies for osteoporosis. Pharmacology & therapeutics. 2022;237:108168.
- 21. Hernlund E, Svedbom A, Ivergård M, Compston J, Cooper C, Stenmark J, et al. Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Archives of osteoporosis. 2013;8(1):136. pmid:24113837
- 22. Salari N, Ghasemi H, Mohammadi L, Behzadi MH, Rabieenia E, Shohaimi S, et al. The global prevalence of osteoporosis in the world: a comprehensive systematic review and meta-analysis. Journal of orthopaedic surgery and research. 2021;16(1):609. pmid:34657598
- 23. Konkle SL, Zierold KM, Taylor KC, Riggs DW, Bhatnagar A. National secular trends in ambient air volatile organic compound levels and biomarkers of exposure in the United States. Environmental research. 2020;182:108991. pmid:31835113
- 24. Jain RB. Detection rates, trends in and factors affecting observed levels of selected volatile organic compounds in blood among US adolescents and adults. Environmental toxicology and pharmacology. 2017;56:21–8. pmid:28869856
- 25. Jain RB. Distributions of selected urinary metabolites of volatile organic compounds by age, gender, race/ethnicity, and smoking status in a representative sample of U.S. adults. Environmental toxicology and pharmacology. 2015;40(2):471–9. pmid:26282484
- 26. Liu B, Jia C. Effects of exposure to mixed volatile organic compounds on the neurobehavioral test performance in a cross-sectional study of US adults. International journal of environmental health research. 2015;25(4):349–63. pmid:25130197
- 27. Su FC, Jia C, Batterman S. Extreme value analyses of VOC exposures and risks: A comparison of RIOPA and NHANES datasets. Atmospheric environment (Oxford, England: 1994). 2012;62:97–106. pmid:25705112
- 28. Yan Z, Xiong X, Tao J, Wang S. Association of bone mineral density with trichlorophenol: a population-based study. BMC musculoskeletal disorders. 2023;24(1):202.
- 29. Kirk AB, DeStefano A, Martin A, Kirk KC, Martin CF. A New Interpretation of Relative Importance on an Analysis of Per and Polyfluorinated Alkyl Substances (PFAS) Exposures on Bone Mineral Density. International journal of environmental research and public health. 2023;20(5).
- 30. Yang R, Chen Z, Hu Y. Associations of Urinary Polycyclic Aromatic Hydrocarbons With Bone Mineral Density at Specific Body Sites in U.S. Adults, National Health and Nutrition Examination Survey 2001 to 2004. Endocrine practice: official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists. 2022;28(9):867–74. pmid:35764250
- 31. Wang C, Zhu Y, Long H, Ou M, Zhao S. Relationship between blood manganese and bone mineral density and bone mineral content in adults: A population-based cross-sectional study. PloS one. 2022;17(10):e0276551. pmid:36269752
- 32. Mosekilde L, Danielsen CC, Gasser J. The effect on vertebral bone mass and strength of long term treatment with antiresorptive agents (estrogen and calcitonin), human parathyroid hormone-(1–38), and combination therapy, assessed in aged ovariectomized rats. Endocrinology. 1994;134(5):2126–34. pmid:8156913
- 33. Yamauchi H, Kushida K, Yamazaki K, Inoue T. Assessment of spine bone mineral density in ovariectomized rats using DXA. Journal of bone and mineral research: the official journal of the American Society for Bone and Mineral Research. 1995;10(7):1033–9. pmid:7484278
- 34. Yin X, Zhao S, Xiang N, Chen J, Xu J, Zhang Y. Efficacy of Bushen Jiangu therapy in the treatment of glucocorticoid-induced osteoporosis: A systematic review and meta-analysis of randomized controlled trials. Medicine. 2023;102(11):e33278. pmid:36930100
- 35. Deng HW, Xu FH, Davies KM, Heaney R, Recker RR. Differences in bone mineral density, bone mineral content, and bone areal size in fracturing and non-fracturing women, and their interrelationships at the spine and hip. Journal of bone and mineral metabolism. 2002;20(6):358–66. pmid:12434164
- 36. Mohammadzadeh Akhlaghi N, Baradaran Mohajeri L, Fazlyab M. Tissue Necrosis due to Chloroform: A Case Report. Iranian endodontic journal. 2013;8(4):208–9. pmid:24790633
- 37. Bonde JP, Toft G, Rylander L, Rignell-Hydbom A, Giwercman A, Spano M, et al. Fertility and markers of male reproductive function in Inuit and European populations spanning large contrasts in blood levels of persistent organochlorines. Environmental health perspectives. 2008;116(3):269–77. pmid:18335090
- 38. Figà-Talamanca I. Occupational risk factors and reproductive health of women. Occupational medicine (Oxford, England). 2006;56(8):521–31. pmid:17151388
- 39. Hassani S, Namvar M, Ghoreishvandi M, Attarchi M, Golabadi M, Seyedmehdi SM, et al. Menstrual disturbances and hormonal changes in women workers exposed to a mixture of organic solvents in a pharmaceutical company. Medical journal of the Islamic Republic of Iran. 2014;28:156. pmid:25695014
- 40. Begić A, Begić A, Arnautović-Halimić A. Influence of thyroid hormones on bone density. Medicinski glasnik: official publication of the Medical Association of Zenica-Doboj Canton, Bosnia and Herzegovina. 2020;17(1):35–40. pmid:31663319