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Journal of Endocrinology & Metabolism

Original Article

Volume 12, Number 4-5, October 2022, pages 125-133

Bone Mineral Density as a Predictor of Cardiovascular Disease in Women: A Real-World Retrospective Study

Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death in women. One in three fatalities among females are attributable to it [1]. Women with ischemic heart disease have worse outcomes and a greater mortality rate even though cardiovascular mortality in both sexes has significantly decreased over the past few decades [2-4]. The most likely reason is that risk variables and outcomes differ according to gender [5]. Gender-specific risk factors for cardiovascular disease in women include menopause, polycystic ovary disease, pre-eclampsia, gestational hypertension (HTN), depression and autoimmune inflammatory disease.

Osteoporosis is a major health problem with a significant risk of serious fractures, disability and mortality. It is estimated that more than 200 million have the disease worldwide, with an expected rise given the steady increase in the ageing population [6]. In postmenopausal women, osteoporosis and cardiovascular disease are prevalent disorders with shared underlying risk factors like obesity, HTN, diabetes mellitus (DM), smoking, and physical inactivity. Low bone mineral density (BMD) is linked to female cardiovascular mortality in numerous epidemiological studies [7-9]. Regardless of any risk factors, the majority of societies in the United States and Canada, including the United States Preventive Services Task Force, advocate screening for BMD in postmenopausal women when they are over 65 years old [10]. BMD can be determined at a low cost and in large quantities using dual-energy X-ray absorptiometry (DXA) scanning. Our study aim was to investigate lower BMD as a predictor of ASCVD events in females who underwent DXA scanning. The DXA scan has the potential to be an excellent tool for risk classification in women due to its low cost and widespread use. Given that it is a routine test used for women’s osteoporosis screening, it will offer an efficient screening tool without placing a financial burden on the healthcare system.

A retrospective observational study was conducted in multiple Rochester Regional Health centers in New York. Women aged 50 - 80 years who underwent DXA scanning from 2012 to 2014 were enrolled in the study. For women who underwent repeated DXAs during the study period, only the first DXA was included. Patients who had scanning of the right hip, left hip and spine were noted. Scanning at other sites like the elbow was not included in the study. We excluded patients with a history of previous myocardial infarction (MI), transient ischemic attack (TIA) or stroke, history of malignant tumor, previous pathological fracture, chronic kidney disease ≥ stage 3a, previous osteoporosis treatment, patients without complete BMD measurements and those without follow-up data (185 patients had no follow-up). Finally, a total of 1,995 patients were included in the analysis.

Data were collected through a chart review and using the Epic electronic medical records (EMR) SlicerDicer tool to identify comorbidities and outcomes. The Institutional Review Board approved the study (approval number 2111A). The study was conducted in compliance with the ethical standards of the responsible institution on human subjects as well as with the Helsinki Declaration.

Baseline characteristics were noted from reviewing the chart and using the Epic EMR SlicerDicer tool (Table 1). Age, sex, race, history of HTN, hyperlipidemia (HLD), DM, body mass index (BMI), and smoking status were noted. Smoking status was noted from the history taken at the initial provider encounter. HTN was defined by blood pressure of more than 140/90 or the use of antihypertensive medication within the last 6 months. DM was defined by hemoglobin A1c or more than 6.5% or the use of insulin or oral hypoglycemic medications within the previous 6 months. Smoking status was noted from the history taken at the initial provider encounter.

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Table 1. Baseline Characteristics of the Enrolled Population

BMD was measured at the left femur, right femur and total hip using a single DXA scanner. Osteopenia was defined as a T score between -1.0 and -2.5, and osteoporosis was defined as a T score below -2.5 in either hip or one of the femurs, in accordance with World Health Organization guidelines.

The primary outcome of interest is the composite of MI, stroke, and cardiovascular death. Cardiovascular death was defined as death during the same hospitalization for an acute cardiac event or stroke. Primary endpoint analysis was done by chart review and chart follow-up.

In this study, statistical analyses were performed with the use of SAS Studio (SAS Institute) to conduct logistic regression to assess the relationship between cardiovascular events and T scores (normal range, osteopenia, and osteoporosis). Cardiac event was defined as if a patient experienced stroke, MI or cardiac death. Descriptive statistics for all the study variables were reported. Logistic regression results of these analyses were reported with point estimates, 95% confidence intervals (CIs) and P values. Mixed linear regression results were reported with estimates, 95% CIs and P values. P value ≤ 0.05 was considered to be statistically significant.

Of the 1,995 patients who underwent DXA scanning, 1,709 patients were white (85.7%), 135 (6.8%) were black, and the average age was 72.5 years. Of the patients, 22.1% were found to have osteoporosis, and 57.2% had osteopenia based on combined BMD of the hip, right femur or left femur. All demographics collected at baseline, as noted in Table 1, included age, gender, race, height, weight, BMI, and baseline BMD of the hip, left and right femur. Traditional risk factors for coronary artery disease included HTN, DM, smoking, HLD, history of cardiac events and MI, and history of stroke.

The primary outcome (cardiovascular event) included MI, stroke, or cardiac death. During the mean follow-up of 9 years, patients with osteoporosis had higher odds of the primary outcome (cardiovascular events) independent of other risk factors. Combined low BMD was independently associated with a significant risk of ASCVD events (odds ratio (OR) 4.68 (2.783 - 7.867), P < 0.0001 (Tables 2, 3)). Low BMD at each site, the right femur, left femur, or hip was independently associated with an increased risk of ASCVD events (OR 6.50 (3.637 - 11.608), P < 0.0001; OR 5.07 (3.166 - 8.108), P < 0.000; OR 3.36 (2.127 - 5.312), P < 0.0001, respectively) (Table 2). After adjusting other covariables, osteoporosis is mainly associated with significant increase in the risk of MI (OR 4.25 (2.105 - 8.593), P < 0.0001) and stroke (OR 3.64 (1.720 - 7.703), P < 0.0007) (Tables 4-7). There was no increase in the risk of cardiovascular death in the osteoporosis group (Tables 8, 9). The linear regression model shows an inverse relationship between the BMD score and cardiac event risk (Table 10). T scores in the osteopenia range did not have any statistically significant increased risk of ASCVD events (OR 1.31 (0.779 - 2.212), P < 0.3062).

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Table 2. Logistic Regression Model for ASCVD and BMD

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Table 3. Logistic Regression Model for ASCVD, BMD and Other Covariates

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Table 4. Logistic Regression Model for BMD and MI

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Table 5. Logistic Regression Model for Stroke and BMD

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Table 6. Logistic Regression Model for MI, BMD and Other Covariates

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Table 7. Logistic Regression Model for Stroke, BMD and Other Covariates

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Table 8. Logistic Regression Model for BMD and Cardiac Death

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Table 9. Logistic Regression Model for Cardiac Death, BMD and Other Covariates

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Table 10. Linear Regression for BMD and ASCVD

Even though there is ample evidence of the association between cardiovascular disease and osteoporosis, BMD is not used for risk assessment of cardiovascular disease. According to the current study, women with osteoporosis have an increased risk of MI, stroke, and cardiovascular death. Osteopenia, on the other hand, did not appear to be related to cardiovascular events. The present findings support prior studies, which revealed a similar connection. In a meta-analysis of 25 studies with around 10,299 patients, decreased BMD was an independent risk factor for ASCVD events in postmenopausal women [11]. The MORE study enrolled 2,576 postmenopausal women with an average age of 66.5 years and followed for 4 years. There was a strong linear association between the severity of osteoporosis and the future risk of cardiovascular disease [12].

In a recent longitudinal study conducted in Korea with over 12,000 women, BMD has prognostic significance for ASCVD events [13]. Even after considering age and other risk variables, they also demonstrated incremental predictive value. Our study is the first to examine the predictive power of BMD for ASCVD in a mixed group of American women, with a preponderance of white and African American women.

The pathological relation between osteoporosis and atherosclerotic disease is poorly understood and cannot be explained only by age. The most plausible mechanisms include shared risk factors, shared pathophysiology, or a combination of both. Although DM, dyslipidemia, HTN, obesity and smoking are associated with an increased risk of osteoporosis, fracture and coronary artery disease, our study and earlier investigations revealed that osteoporosis is a risk factor for coronary artery disease independent of those conventional risk factors. This is suggestive of the common underlying pathophysiology. The two most frequently suggested hypotheses are a biological mechanism through circulating cytokines and a hormonal mechanism. Osteoprotegerin (OPG), also known as osteoclastogenesis inhibitory factor, is a soluble glycoprotein cytokine found in various tissue cells that is crucial to bone metabolism. Clinical studies reported an association between increased level of OPG and decreased BMD and consequently increased fracture risk [14-17]. On the other side, Bjerre et al, in a prospective cohort study of 4,063 patients with stable coronary artery disease, reported that OPG level was independently predictive of all-cause mortality and cardiovascular death in patients with stable coronary artery disease [18]. Several other studies showed that OPG levels correlate with the severity of coronary artery disease, low BMD and fractures [19-22]. In a study of 490 white postmenopausal women, OPG level was independently linked to the risk and severity of DM, stroke, cardiovascular disease and mortality and may be used as a marker for vascular calcification [21]. The hormonal mechanism relies on postmenopausal estrogen deficiency, which is associated with cardiovascular disease and low BMD [23, 24].

Cardiovascular disease is a leading cause of death in women. Compared to men, they are less likely to be diagnosed early and receive preventive management [25, 26]. In particular, women without traditional risk factors like HTN, DM, smoking, or HLD were assumed to have a lower risk of cardiovascular disease. However, there are substantial and underappreciated gender disparities in risk factors. Many non-traditional risk factors are specific to women that have been linked to cardiovascular disease. Pregnancy-associated complications like pre-eclampsia, gestational DM and preterm delivery are associated with increased ASCVD [27-29]. Autoimmune diseases like systemic lupus erythematosus (SLE) and rheumatoid arthritis are associated with a significantly increased risk of cardiovascular disease in women [30]. The current risk stratification and prediction algorithm are limited in assessing women and do not consider gender differences in the traditional risk factors. The 10-year ASCVD estimate with the pool cohort equation has not shown remarkable accuracy in the lower-risk women [31]. This necessitates the use of additional risk-stratification techniques for women. DXA scan is an easy, widely accessible test used to screen for osteoporosis in women over 65 and women under 65 with a high risk of fracture. According to our results, osteoporosis diagnosed with a low T score in the hip, left femur, or right femur is associated with a significantly increased risk of ASCVD. Therefore, BMD can be a reliable screening test for identifying women at risk for ASCVD or risk stratification. Further research is needed to determine the accuracy of BMD measurement in predicting ASCVD, and it may be necessary to compare the computed tomography coronary calcium score to BMD in assessing cardiovascular disease.

The retrospective medical records review design of the study is a limitation of the study. Since we used the SlicerDicer tool and coding from the Epic EMR, time to death or ASCVD outcome was not calculated. We were not able to use Cox proportional hazards regression due to the lack of this information. Steroid use and menopausal status were not checked. Another limitation is that the blood pressure and lipid levels were not measured. Instead, they were included as a binary variable depending on if the diagnosis of HTN or HLD was added to the chart for the analysis, so the severity of these conditions was not taken into consideration. Another limitation is that we did not account for any cardiovascular deaths or diagnosis occurring outside the medical system. But the change in outcome would be minimal as the chart would reflect such diagnosis from outside centers from updating of the chart by system primary care physician or subspecialist.

The strength of the study is that even in a mixed racial population group, typical of any US city, results were suggestive of a strong association between low BMD and ASCVD in females.

Osteoporosis is associated with an increased risk of cardiovascular disease in women. BMD measurement with DXA scan is widely used in postmenopausal women. Hence, it could stratify and predict the risk of ASCVD events in women. Further wide-scale studies are needed to determine the utility of this commonly used test as a predictor for ASCVD.

Acknowledgments

I would like to thank all those who are related to this project.

Financial Disclosure

No funding was obtained from any source for this study.

Conflict of Interest

All authors declare that they have no conflict of interest.

Informed Consent

Not applicable.

Author Contributions

Sarath Lal Mannumbeth Renjithlal, Sarah Mohamed, and Mohammed Magdi: conception or design of the work. Mostafa Reda Mostafa, Keerthi Renjith, Parvathi Pillai, and Viqarunnisa Zahid: data collection. Musaib Syed: data analysis. Nathan Ritter and Mallory Balmer-Swain: final approval of the version to be published. Amjad Makaryus and Nisha Pillai: critical revision of the article.

Data Availability

The authors declare that data supporting the findings of this study are available within the article.

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