Links between Atherosclerosis and Osteoporosis in Middle Aged and Elderly Men

Abstract

Background

Although the incidences of osteoporosis and atherosclerosis increase with age, there is growing evidence that the coincidental occurrence of both diseases may be independent of age. In general, studies in men are scarce and results are inconsistent.

Objective

to investigate the relationship between atherosclerosis and bone mineral density, and the influence of insulin sensitivity and low grade inflammation on this relationship in 332 men without CVD.

Methods

Aortic Pulse wave velocity (PWV), augmentation index (AIX) and measurements of carotid intima media thickness (CIMT) were assessed. BMD measurements were performed with dual-X-ray absorptiometry (DEXA), subcutaneous fat by ultrasonography. Serum concentrations of lipids, hsCRP, glucose and insulin were measured. Insulin sensitivity was calculated by use of the quantitative insulin sensitivity (QUICKI). We used multivariate linear regression models to examine the association of hsCRP, insulin sensitivity, PWV, Aix, CIMT with BMD.

Results

A higher CIMT was significantly associated with higher BMD after multivariate adjustment (β 99.7; p=0.02). Further adjustment for weight attenuated the estimates towards non-significant. No association was found between PWV or AIX and BMD. Lower insulin sensitivity was associated with higher BMD (β -645.1; p<0.01). After adjustment for weight this association was no longer significant. A similar effect was seen for the association between hsCRP and BMD.

Conclusion

In this population of healthy, non-obese, men without a history of cardiovascular disease the positively association between cardiovascular parameters and BMD was mainly explained by weight, suggesting that in this population weight plays a protective role in the development of osteoporosis

Introduction

Osteoporosis and atherosclerosis are chronic systemic diseases and major public health problems worldwide. They are both important causes of morbidity and mortality in aging men. Although the incidences of osteoporosis and atherosclerosis increase with age, there is growing evidence that the coincidental occurrence of both diseases may be independent of age (1). In healthy individuals, the relationship between atherosclerosis and bone mass has not been extensively studied. Most studies are conducted in postmenopausal women or subjects with cardiovascular disease, while only few studies studied the relationship between atherosclerosis and bone mineral density (BMD) in men with inconsistent results (2, 3, 4, 5). On the other hand, it is widely recognized that lifestyle measures and measures aimed at reducing adverse effects on bone of drugs and diseases have to be recommended throughout life in everyone (6).

The current evidence indicates that individuals with prevalent (sub)clinical cardiovascular disease (CVD) are at increased risk for bone loss and subsequent fractures (7). Measurement of the intimal media thickness (IMT) in the carotid arteries is a non-invasive, sensitive and reproducible technique for identifying subclinical cardiovascular disease. In postmenopausal women most of the studies reported an association of increased IMT with low bone density. In the one study that included men, findings were in line with the results in women (2).

Arterial wall calcification would be expected to increase arterial stiffness. Pulse wave velocity (PWV) and augmentation index (Aix) are measurements of arterial stiffness and both predictors of adverse cardiovascular events (8, 9). Bone loss is associated with increased arterial stiffness in postmenopausal females and hemodialysis patients (10, 11, 12). Few studies have addressed the question of an association between osteoporosis and arterial stiffness in healthy men (13, 14). Findings were not consistent, which may be due to the use of suboptimal measures of arterial stiffness and BMD (15).

Atherosclerosis and osteoporosis could be linked through common risk factors or a shared pathophysiological mechanism. Possible candidates of linking factors are low grade inflammation insulin sensitivity. Markers of inflammation, such as high sensitivity C-reactive protein (hsCRP) have been associated with cardiovascular mortality in both sexes (15) and levels of hsCRP were associated with lower BMD (16, 17). In patient with type 1 diabetes BMD is lower than in non-diabetic subjects. In patients with type 2 diabetes bone mineral density is similar to or higher than in non-diabetic subjects (18).

The aim of this study is to investigate the relationship between atherosclerosis measured by subclinical CVD (carotid IMT)and arterial stiffness (PWV and AIX) and BMD in independently living men aged 40 to 80 years. In addition, we studied the role of insulin sensitivity, low grade inflammation and body composition on these relationships.

Methods

Study population

For the present study data were used from a cross-sectional study among 400 independently living men aged 40–80 years. A random sample of 400 men was included in this study by sampling 100 men in each decade of age. Recruitment procedures have been described elsewhere in detail (19). The study was approved by the institutional review board of the University Medical Center Utrecht and written informed consent was obtained from all participants before enrolment in the study. Data collection took place between March 2001 and April 2002. For the present analysis, men with a history of CVD were excluded (n=68), leaving 332 men for analysis.

Cardiovascular risk factors

Height and weight were measured in standing position without shoes. Body mass index (BMI) was calculated as the weight in kilograms divides by the square of heights in meters.

Blood pressure was measured in the morning after 10 min rest, twice on the right upper arm (sitting position) with a semi-automated device (Dinamap 8100; Critikon Inc.,Tampa, Finland). Mean systolic and diastolic blood pressure was calculated as the average of the two measurements of systolic and diastolic blood pressure was used for analysis and further calculation.

Fasting venous blood samples were obtained. Automatic enzymatic procedure was used to determine serum total cholesterol (Synchron LX Systems; Beckman Coulter, USA). High density lipoprotein (HDL) cholesterol and triglycerides were measured similarly. Low-density-lipoprotein (LDL) cholesterol was calculated using the Friedewald formula [19]. Fasting blood glucose was determined by using a reagent-strip glucose oxidase method using a GlucoTouch reflectometer (LifeScan, Inc., Benelux). Fasting insulin levels were measured using an IMMULITE 2000 Analyzer (DPC, USA). To assess insulin sensitivity, the quantitative insulin sensitivity check index (QUICKI) was calculated, which has a high correlation with insulin sensitivity measured with the glucose clamp technique. QUICKI index can be determined from fasting insulin and glucose values according to the equation: QUICKI index = 1/[log (I0) + log (G0)], in which I0 is fasting insulin (mIU/liter) and G0 is fasting glucose (mg/dl = mmol/liter x 18.182) [21]. High sensitivity C-reactive protein (hc-CRP) was measured using a Behring Nefelmeter II (Dade Behring, Liederbach, Germany). The lower limit of detection was 0.175 mg/l and the inter assay variation was 2.4%. Hs-CRP levels > 10mg/l can be taken as evidence of active inflammation processes (e.g. infection, trauma), therefore subjects with hs-CRP >10 mg/l were excluded. 25OHD was determined using an automated assay for the quantitative determination of 25-hydroxyvitamin D (IDSiSYS, UK), with 100% 25OHD3 and 25OHD2 cospecificity. Assay range was 13.75–350 nmol/L and sensitivity 13.75 nmol/L.

Smoking was estimated from self-report and categorized in current, former and never smokers. Alcohol intake was estimated using a validated food frequency questionnaire (22, 23). A medical doctor obtained information about the prevalence of disease and medication use from a specified medical history. Fasting venous blood samples were drawn and analyzed.

Hypertension was defined as systolic blood pressure ≥140mmHg and/or diastolic blood pressure ≥90mmHg and/ or use of anti-hypertensive medication. Diabetes mellitus was defined as treatment with insulin or oral hypoglycemic agents and/or fasting plasma venous glucose >6.9 mmol/l.

Hyperlipidemia was defined as treatment with lipid lowering medication and/or serum total cholesterol >6.5 mmol/l. Presence of CVD was based on a positive answer in the questionnaire on history of coronary artery disease, peripheral artery disease or stroke. Physical activity was assessed using the validated Voorrips questionnaire for the elderly (24).

Assessment of functional and structural measures of the vessel wall

As structural measure of the vessel wall we used carotid intima-media thickness (CIMT) as a measure of the extent of subclinical atherosclerosis. Ultrasonography of both the left and right carotid artery was performed using a 7.5MHz linear array transducer (Acuson Aspen, Mountain View, CA, USA). Details of the procedure for CIMT measurement have been published previously (25).

As functional measures of the vessel wall, we used to measures of vascular stiffness; carotid-femoral pulse wave velocity (PWV) and aortic Augmentation Index (AIx). The PWV was determined noninvasively using a SphygmoCor device (PWV Medical, Sydney, Australia), which allowed an online pulse wave recording and automatic calculation of PWV using transducers (Millar SPT 301 pressure transducer; Milar Instruments, Sydney, Australia). Details of the procedure for aortic PWV measurement have been published previously (26).

The aortic AIx was derived by applantation tonometry of the radial artery and was calculated as the difference between the first and second systolic peaks of the ascending aortic waveform expressed as a percentage of the central pulse pressure (the difference between central systolic and diastolic pressure divided by pulse pressure). The details of this method have been described elsewhere (27).

Assessment of bone mineral density

BMD measurements were performed with Dual-Energy X-ray absorptiometry (DEXA) using a Hologic QDR1000 (Hologic Europe, Zaventem, Belgium). Scanning was performed according to the instructions of the manufacturer. Quality assurance, including calibration was performed routinely every morning for DEXA, using the standard provided by the manufacturer. Quality assurance, including calibration was performed routinely every morning for DEXA, using the standard provided by the manufacturer. In the analyses performed we used total body BMD.

Data analysis

Distributions of anthropometric measures, lifestyle characteristics, and laboratory measurements were expressed as mean and standard deviation for continuous variables and frequency and percentage for categorical variables.

Linear regression analysis was performed to estimate the strength of the associations between the cardiovascular parameters and BMD and described as the linear regression coefficient (β) and its standard error (SE). Assumptions for linear regression including linearity of the relationship between dependent and independent variables and normality of the variables was checked in advance and violations were fixed by transformations or excluding outliers. Two extreme values in PWV (2.75 and 30.51 m/s) were excluded, since they were considered biologically implausible. Hs-CRP levels > 10 mg/l can be taken as evidence of active inflammatory processes (for example, trauma, infection), therefore subjects with hsCRP >10 mg/l were excluded from the analysis (n=17). Both hsCRP and PWV were log-transformed because of their skewed distributions. Crude models were adjusted in five steps. First we adjusted for age. Second, we added the confounders that are necessary to take into account (alcohol consumption, smoking, physical performance and height). To elucidate whether and to what extent the associations might be explained by intermediate factors, further analyses also adjusted separately for weight. The level of statistical significance was set at p<0.05 in all analyses. Analyses will be performed with the SPSS statistical software package, version 15.0 (SPSS Inc, Chicago, III).

Results

Table 1 provides the characteristics of the study population. The median age of the total study group was 59 years (range 40–80).

Table 1.

Patient characteristics (n=332)

	Mean ± SD
Age (years)	59 ± 11
Body mass index (kg/m2)	26 ± 3
Bone mineral density (mg/cm2)	1147 ± 93
Smoking (pack years)	14.4 ± 19.4
Alcohol consumption (units/week)	13.3 ± 13.6
Physical activity (Voorrips score)	9.2 ± 1.7
Fasting glucose (mmol/l)	5.9 ± 1.4
Vitamin D (nmol/l)	61.9 ± 25.6
IMT (mm)	0.81 ± 0.15
Pulse wave velocity (m/s)	9.2 ± 2.8
Aix (%)	23.9 ± 10.3
hsCRP (mg/ml)	2.64 ± 5.9
Insulin sensitivity (QUICKI)	0.35 ± 0.04

A higher CIMT was statistically significantly associated with higher BMD after adjustment for age, smoking, alcohol, physical activity, vitamin D and height (β 99.7; p=0.02). Further adjustment for weight attenuated the estimates towards non-significant (Table 2).

Table 2.

Associations between cardiovascular parameters and BMD

CVD parameter	Model 1		Model 2		Model 3		Model 4
	ß (SE)	p-value	ß (SE)	p-value	ß (SE)	p-value	ß (SE)	p-value
PWV	-20.1 (21.0))	0.3	27.6 (27.2)	0.3	39.5 (27.6)	0.2	11.2 (25.9)	0.3
Aix	-0.2 (0.5)	0.8	0.2 (0.5)	0.7	0.9 (0.5)	0.1	0.4 (0.5)	0.4
CIMT	-14.6 (35)	0.7	98.8 (44.9)	0.03	108.6(44.6)	0.02	56.5 (38.6)	0.1

Model 1: crude model; Model 2: adjusted for age; Model 3: multivariable adjusted for age, smoking, alcohol, height and physical activity; Model 4: model 3 additionally adjusted for weight.

We found no association between PWV or AIx and BMD (Table 2). Linear regression analyses showed that lower insulin sensitivity was associated with higher BMD (β-645.1; p0.00). After adjustment for weight this association was no longer significant (Table 3). A similar effect was seen for the association between hsCRP and BMD (Table 3).

Table 3.

Associations between insulin sensitivity, hsCRP and BMD

CVD parameter	Model 1		Model 2		Model 3		Model 4
	ß (SE)	p-value	ß (SE)	p-value	ß (SE)	p-value	ß (SE)	p-value
Insulin sensitivity	-441.9 (142.2)	0.00	-573.1 (142.7)	0.00	-645.1 (141.1)	0.00	127.7 (149.9)	0.4
hsCRP	9.6 (5.3)	0.07	14.5 (5.4)	0.01	16.8 (5.4)	0.00	6.6 (4.8)	0.18

Model 1: crude model; Model 2: adjusted for age; Model 3: multivariable adjusted for age, smoking, alcohol, height and physical activity; Model 4: model 3 additionally adjusted for weight.

This population-based cross-sectional study of middle-aged and elderly men, without a history of CVD, showed that CIMT, serum levels of hsCRP and insulin sensitivity were related to BMD. Adjustment for weight attenuated the association between CIMT, insulin sensitivity and hsCRP and BMD, suggesting that apart from a direct effect on bone CIMT and insulin sensitivity might be particularly associated with weight, which in turn is related to BMD. Arterial stiffness, measured by PWV and Ax, was not associated with BMD in this population. To the best of our knowledge, this cross-sectional study is the first to investigate the association between low BMD and atherosclerosis in a large sample of middle-aged and elderly men without history of cardiovascular disease.

To appreciate these findings some issues need to be addressed. First, the interpretability of the results may be restricted by several factors inherent to the cross-sectional design and does not provide direct evidence of cause and effect. Second, we studied total BMD, while in clinical practice femoral and lumbar BMD are used. On the other hand, in studies evaluating the association between low bone mass and vascular calcification, an independent association was shown between BMD at cortical sites, as represented by low hip BMD and vascular calcification, while studies measuring BMD at predominantly trabecular sites, namely spinal sites, failed to demonstrate an association. This may be related to the fact that the trabecular bone compartment is more metabolically active than the cortical compartment due to its larger surface area and exposure.

In the present study, subclinical atherosclerosis measured by CIMT was related to higher BMD, an effect that was no longer significant after adjustment for weight. Schaffer et al found similar results in young and middle-aged (<60) men and women, whereas in older individuals, BMD was inversely associated with CIMT (2). Other studies relating the degree of atherosclerosis and bone mineral density have shown variable results (no association or inversely associated), perhaps because populations, methods, and the anatomical sites chosen to assess osteoporosis and atherosclerosis vary dramatically between and among studies. Most studies included post-menopausal women or older men with cardiovascular disease or DM (2, 28, 29, 30).

We found no association of AIx and PWV with BMD. Previous literature regarding the association between PWV and AIx is inconsistent and only few studies included men (31-34). A link between osteoporosis and PWV in men has been recently suggested in a clinical study in Japanese men. This study found a correlation between brachial ankle PWV and ultrasound detected osteoporosis (14). Another study, in healthy men >60 years found no correlation between osteoporosis and PWV (13). Aix and bone loss is scarcely studied. One study found that Aix was increased in osteoporotic postmenopausal women free of cardiovascular disease and risk factors.

The association we found between insulin sensitivity and BMD is in line with several observational studies (35, 36, 37). After adjustment weight, the association was no longer significant. Complex pathophysiological mechanisms associated with insulin resistance and hyperglycemia are involved in deleterious effects on osteoblast function and bone formation (19). Higher levels of hsCRP are associated with increased fracture risk, although previous studies on CRP and BMD have yielded conflicting results and evidence supporting an association in men has been limited. Most studies finding an association between low grade inflammation and BMD are conducted in patients with manifest cardiovascular disease (38, 39, 40, 41). In our study, excluding subjects with pre-existing cardiovascular disease, we found no association between hsCRP and BMD, after adjusting for weight. These contrasting results may be explained by the fact that in our healthy study population inflammation levels are negligible in comparison with a patients with manifest cardiovascular disease and therefore not affect BMD.

As written above and shown in Table 2 and 3 after adjustment for weight the significant associations we found were no longer significant, suggesting that the relation between subclinical atherosclerosis (measured by CIMT), hsCRP ad insulin sensitivity and BMD, in our healthy study population, was partly explained by weight. Interestingly, obesity is considered to have opposites effects on bone and arterial aging. It is well known that overweight and obesity increase arterial stiffness, these effects being partially related to increased blood pressure in overweight subjects, but also to the several other mechanisms such as metabolic disturbances, which can also increase arterial stiffness. Body weight and obesity have been reported to increase BMD due to purely mechanical loading reasons. Mechanical loading appears to stimulate bone formation by decreasing apoptosis and increasing proliferation and differentiation of both osteoblasts and osteocytes by an activation of the intracellular signalling Wnt/β-catenin. Body fat mass, a component of body weight and one of the most important indices of obesity, may have beneficial effects on bone through several molecular and hormonal pathways (adipocytokine). It has also been reported that excessive fat mass may promote osteoporosis probably due to the presence of associated metabolic disorders (insulin sensitivity) and low-grade inflammation. So, the interaction between body weight and BMD is very complex and both positively and inversely associations are defined (figure 1). We conclude that the negative effects of weight on bone are mostly attribute to excessive fat mass and its associated low grade inflammation and metabolic disorders. Since our study population consisted of healthy mostly non-obese men (only 39 subject (11%) were obese), this explains the protective effect of weight on BMD in this population.

Figure 1.

Associations obesity and BMD and atherosclerosis Discussion

In line with this, Benetos et al studied the individual effects of lean and fat mass on bone mineral density and arterial stiffness in elderly men. Bone and arterial aging were differently influenced by lean and fat mass. Aortic stiffness increased with fat mass and presence of associated metabolic disorders, but was not influenced by lean mass. On the other hand, bone mineral density was positively and strongly correlated with lean mass, whereas fat mass and associated metabolic disorders had no effect (13).

In summary, in this population of healthy middle aged and elderly men without a history of cardiovascular disease the positively association between cardiovascular parameters and BMD was mainly explained by weight. Suggesting that in non-obese men without cardiovascular disease weight plays a protective role in the development of osteoporosis.

Conflict of Interest

Frederiek van den Bos – Reports no disclosures; Marielle Emmelot-Vonk – Reports no disclosures; Harald Verhaar – Reports no disclosure; Yvonne van der Schouw – Reports no disclosures

Ethical standard

The study was approved by the Institutional Review Board of UMC Utrecht. All participants signed written informed consent.