Acta Physiologica Hungarica, Volume 101 (2), pp. 216–227 (2014) DOI: 10.1556/APhysiol.101.2014.2.10

The relationship between the metabolic syndrome and its components and bone status in postmenopausal women D Fodor1, S Vesa2, A Albu1, S Simon3, A Craciun4, L Muntean3 1 nd

2 Internal Medicine Department, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania 2 th 5 Internal Medicine Department, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania 3 Rheumatology Department, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania 4 Biochemistry Department, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania Received: December 18, 2012 Accepted after revision: December 9, 2013 The association between metabolic syndrome (MS) and bone status remains controversial. We aimed to study the relationships between MS, bone mineral density (BMD), and bone metabolism in postmenopausal women. Material and method: MS was assessed in 218 white postmenopausal women. BMD (lumbar spine and hip) was measured by dual energy X-ray absorptiometry (DXA). Serum carboxyterminal cross-linked telopeptide of type I collagen (CTX), undercarboxylated osteocalcin (uOC), bone alkaline phosphatase (BAP) and vitamin D were assayed. Results: Postmenopausal women with MS had a significantly higher lumbar spine BMD than women without MS (p < 0.05). A progressive increase of the BMD at both sites with the number of MS components was observed. Bone turnover markers and vitamin D levels were not significantly influenced by the presence of MS. BMD at both sites positively correlated with body mass index (BMI), waist circumference (WC) and glucose in unadjusted analysis. In multiple regression analysis, WC was independently associated with BMD at both sites, while hypertension was associated only with lumbar spine BMD. Conclusions: In postmenopausal women, MS is associated with increased lumbar spine BMD and this relation is explained mainly by the higher BMI and WC in the MS group. Keywords: metabolic syndrome, bone mineral density, bone turnover markers, vitamin D, postmenopausal women

Cardiovascular diseases and osteoporosis are two major global health problems with an increasing prevalence and a high impact on mortality and morbidity. There is more and more evidence that suggests a shared pathogenesis between osteoporosis and atherosclerosis. However, the relationship between these two entities is still controversial (7). The metabolic syndrome (MS) is a cluster of cardiovascular risk factors including dysglycemia, raised blood pressure, elevated triglyceride (TG) levels, low high-density lipoprotein cholesterol (HDL-C) levels, and obesity, particularly the central adiposity (4). These conditions are strongly associated with cardiovascular health and low grade inflammation (22).

Corresponding author: Laura Muntean, MD, PhD Rheumatology Department, “Iuliu Hatieganu” University of Medicine and Pharmacy 2–4 Clinicilor Str, 400006 Cluj Napoca, Romania Phone: +40-264-591942/442; Fax: +40-264-596912; E-mail: [email protected] 0231–424X/$ 20.00 © 2014 Akadémiai Kiadó, Budapest

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The relationship between MS, its components, and bone status has been previously studied, but not yet elucidated. Several researchers found higher BMD at lumbar spine and/ or femoral neck among postmenopausal women or men with MS, and this association was explained by higher BMI in those patients (16, 28). In contrast, in a recent cross-sectional study on a large population of women aged 18 years and over, lumbar spine BMD was significantly lower in women with MS, suggesting that MS may be a risk factor for osteoporosis (17). Also, in the Rancho Bernardo Study (36), men with MS had lower BMD than those without MS. However, other researchers did not find an association between MS and bone parameters (35, 43). High body mass index (BMI) is conventionally considered to be protective for bone (3, 21). However, in a recent study it was shown that morbid obesity (BMI > 30) may not be a protective factor against osteoporosis (12). The relationship between fasting plasma glucose and BMD is also inconclusive. In a population-based study, Kinjo et al. (21) found a trend for higher femoral neck bone mineral density (BMD) as fasting plasma glucose level increases. Von Muhlen et al. (36) found a positive association between fasting plasma glucose and lumbar spine BMD in women, and a negative association in men. In contrast, Hwang and Choi (17) found no difference in lumbar spine BMD between postmenopausal women with hyperglycemia and those with normal glucose levels. The relationships between other components of MS (e.g., serum levels of TG and HDL-C) and BMD are also contradictory. Hypertension was positively correlated with lumbar spine BMD (15) or no correlations could be established (17, 19). These divergent results are probably explained by differences in the race and ethnicity of the studied populations, by different modalities used for the definition of MS, and, also possibly reflect the wide variety of DXA equipment used. Recent studies have documented a decrease in both bone formation and bone resorption markers in patients with MS (34, 42). The reduced levels of osteocalcin together with increased waist circumference and glucose levels, seems to be related to a common underlying factor-insulin resistance (42). The aim of this cross-sectional study was to evaluate the relationships between MS and its components, and BMD, bone turnover markers and vitamin D levels in postmenopausal women. Materials and Methods Between September 2009 and September 2010, 218 white postmenopausal women were consecutively enrolled from the patients referred for BMD assessment at the Rheumatology Clinic of the “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania. Written informed consent for participation was obtained from each subject prior to enrolment. The Ethics Committee of University approved the study protocol (ANCS 42107/2008 PNII Grant). Women were eligible if menopause had occurred at least two years prior to their visit. Patients with hormonal replacement therapy or medication affecting bone metabolism (corticosteroids, anticonvulsants, oral anticoagulants, or osteoporosis therapy) were excluded. Also, patients with any condition that might interfere with bone metabolism (thyroid disorders, malabsorption, chronic renal and liver diseases, or alcoholism) were excluded. Data collected from patients included age, weight, height, BMI (BMI = weight/height2, kg/ m2), waist circumference, menarche, menopause. We recorded the patients’ medication history and associated diseases including coronary heart disease, stroke, hypertension, and diabetes. Blood pressure was measured with a sphygmomanometer in the right arm of the subject after a 10 minutes rest in the supine position. Acta Physiologica Hungarica 101, 2014

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Overweight was defined as a BMI over 25 kg/m². Hypertension was defined as an average systolic blood pressure over 140 mmHg, an average diastolic blood pressure over 90 mmHg, or self-reported use of antihypertensive medication (1). Diabetes was defined as selfreported physician diagnosis of diabetes or according to the WHO guidelines definition (38). Laboratory assay Blood samples were drawn from the antecubital vein in the morning after the subject had fasted for 12 hours. The serum concentrations of total cholesterol, HDL-C, TG, glucose were determined by colorimetry (Cobas Mira Plus analyzer, Hoffman La Roche, Switzerland). By ELISA technique (Elisa reader: Organon Teknika Reader 230 S, Oss, The Netherlands) were determined serum collagen type 1 cross-linked C-telopeptide (CTX) (Serum CrossLaps, Immunodiagnostic-Systems GmbH, Frankfurt am Main, Germany, sensitivity = 0.02 ng/ml, intra-assay variation = 3%, inter-assay variation = 9.8%, normal ranges in postmenopausal women: 0.142–1.351 ng/ml), undercarboxylated osteocalcin (uOC) (Undercarboxylated Osteocalcin, TaKaRa Biomedicals, Shiga, Japan, intra-assay variation = 5.8%, inter-assay variation = 8.2%, normal ranges 0.098–2.374 ng/ml), and vitamin D (25-Hydroxy Vitamin D, Immunodiagnostic-Systems GmbH, Frankfurt am Main, Germany, sensitivity = 5 nmol/l, intra-assay variation = 5.3%, inter-assay variation = 7.8%, normal ranges in adults 47.7–144 nmol/l). Bone alkaline phosphatase (BAP) (Ostase, Beckman Coulter, Indianapolis, USA, sensitivity = intra-assay variation = 2.1%, inter-assay variation = 6%, normal range in postmenopausal women < 22.4 µg/l) was determined by chemiluminescence (Beckman Coulter Access2, USA). Ultra-High Sensitive C Reactive Protein (CRP U-hs) (DiaSys, Holzheim, Germany, intra-assay variation = 1.5%, inter-assay variation = 3.0%) was assessed by the immunoturbidimetric method (CST-240, Diru, China). Metabolic syndrome For definition of the MS we used the American Heart Association/National Heart, Lung, and Blood Institute criteria (13): waist circumference ≥ 88 cm, serum TG ≥ 150 mg/dl (or drug treatment for elevated serum TG), HDL-C < 50 mg/dl (or drug treatment for reduced HDL-C), blood pressure of at least 130 mm Hg systolic or 85 mm Hg diastolic (or the use of antihypertensive drugs), fasting blood glucose of ≥ 100 mg/dl (or drug treatment for elevated glucose). MS was identified in the presence of three or more components. Measurement of BMD BMD was measured at the lumbar spine (L2–L4) and at the hip (femoral neck and total hip) by dual energy X-ray absorptiometry (DXA), using a Lunar Prodigy Advance (GE Healthcare, USA) densitometer. Results were expressed as BMD in g/cm2 and T-score (standard deviation from peak adult BMD). All the measurements were performed by two operators. The interand intra-operator coefficient of variation was less than 1.3% and the coefficient of variation was 0.8% for spine measurements and 1.1% for femoral neck. We evaluate the vertebral fractures using lateral radiographs (from T4 to L5). A vertebral fracture was defined as a reduction of ≥ 20% at the anterior, middle and/or posterior height of vertebral body (10). Statistical analysis The statistical analysis was performed using MedCalc Software, Belgium; Version 12.3.0. The Kolmogorov–Smirnov one-sample test was used for testing the sample cumulative distribution. Continuous variables were expressed as the mean ± SD (standard deviation). Acta Physiologica Hungarica 101, 2014

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For the variables with non-normal distribution the data were expressed as median and the lower and upper quartiles (25th percentile and 75th percentile). Two independent samples t-test was used for inter-group comparison of continuous and normally distributed variables and the Mann–Whitney U test for variables with non-normal distribution. For categorical variables analysis the Pearson chi-square test was applied. For not normally distributed values the Spearman correlation test was applied. Analysis of covariance was performed also adjusting for age. Multivariate linear analysis (enter linear regression) models were constructed to analyse the association between MS and its components with BMD. Optimal cut-off values for lumbar spine BMD for diagnosis of MS as continuing variable were chosen to maximize the sum of sensitivities and specificities. The diagnostic performance of the tests was assessed by using receiver operating characteristics (ROC) curves. p ≤ 0.05 was considered statistically significant. Results We studied a total of 218 postmenopausal women with a mean age of 64.9 (SD 9.1) years. MS was present in 116 (53.2%) patients (Table I). Postmenopausal women with MS have had significantly longer time since menopause, higher BMI and increased waist circumference, higher serum level of TG and glucose, and lower serum HDL-C than women without MS. The prevalence of the individual components of the MS was significantly higher in the MS group compared with the non-MS group (p < 0.001). There were no statistically significant differences in the prevalence of coronary heart disease or stroke between these groups (p > 0.05, data not shown). The serum levels of CRP U-hs were higher in patients with MS as compared with controls, suggesting a trend for significance [5.94 (3.4–11.44) vs. 4.56 (2.35– 9.91) mg/dl; p = 0.059]. The percentage of subjects with abnormally low 25-hydroxy vitamin D values was 82% in the whole group of postmenopausal women. There was no difference in the median vitamin D levels, as well in the percentage of patients with abnormally low 25-hydroxy vitamin D values, between the patients with MS and those without MS. BMD measurements, bone turnover markers, and frequency of osteoporotic vertebral fractures in patients with and without MS are illustrated in Table II. The BMD at the lumbar spine was significantly higher in the MS group compared with the non-MS group (p = 0.034). This difference remained significant after adjustment for age (p = 0.021), but disappeared after age and BMI adjustment (p = 0.22). The femoral neck BMD values were similar between these two groups. Postmenopausal women with MS tended to have higher levels of total hip BMD than patients without MS, although the difference did not reach statistical significance (p = 0.106). There was no significant difference in the serum levels of CTX, osteocalcin, BAP, and vitamin D between the two groups. Also, we did not find a significant difference in the prevalence of osteoporotic vertebral fractures between women with MS and those without MS (all p > 0.05). The waist circumference was significantly higher in the group of patients with MS and vertebral fractures compared with patients without MS and vertebral fractures (p = 0.01). The BMI values were similar between these two groups. There was no significant difference in the serum levels of CTX, osteocalcin, BAP, and vitamin D between patients with MS and vertebral fractures and those without MS and vertebral fractures (all p > 0.05). When analysing the lumbar spine and femoral neck BMD in the whole group of patients according to the presence of different components of the MS (from 0 to 5, in all possible combinations) we observed a progressive increase in bone mass at both sites (Table III). This relationship was maintained after age adjustment. Acta Physiologica Hungarica 101, 2014

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Table I. Study group characteristics (whole group and groups divided according the absence/presence of the MS) Variable

All patients (n = 218)

Patients without MS (n = 102)

Patients with MS (n = 116)

Age (years)

64.86 ± 9.13

63.62 ± 9.18

65.96 ± 8.98

Time since menopause (years)

16 (10–25.5)

14 (8–23)

18 (12–26)*

29.02 ± 5.50

27.10 ± 5.23

30.72 ± 5.18‡

2

BMI (kg/m ) Waist circumference (cm)

95.28 ± 13.45

88.90 ± 13.05

100.9 ± 11.12‡

TC (mg %)

218.78 ± 53.31

217.44 ± 49.82

219.95 ± 56.39

HDL-C (mg %)

48.23 (42.81–56.99)

54.36 (47.34–62.65)

44.44 (40.27–48.91)‡

Triglycerides (mg %)

126 (91–167.25)

113.5 (84.75–145)

142 (95.75–186.75)‡

Glucose (mg %)

100 (91.75–114)

98 (89–100)

107 (96–130)‡

5.58 (3–10.81)

4.56 (2.35–9.91)

5.94 (3.4–11.44)

Hypertension

151 (69.3%)

42 (45.2%)

109 (93.9%)‡

Diabetes or glucose > 100 mg/dl

60 (27.5%)

10 (9.8%)

50 (43.1%)‡

TG > 150 mg/dl

69 (31.6%)

16 (15.6%)

53 (45.6%)‡

HDL-C < 50 mg/dl

121(55.5%)

31 (30.3%)

90 (77.5%)‡

Abdominal obesity (waist circumference > 88 cm)

164 (75.2%)

55 (53.9%)

109 (93.9%)‡

CRP U-hs Prevalence of the components of the MS

Values are shown as n (%), mean ± SD, or median (25th percentile–75th percentile). n: number of patients; MS: metabolic syndrome; BMI: body mass index; CRP U-hs: Ultra-High Sensitive C Reactive Protein; TC: Total cholesterol; HDL-C: HDL cholesterol. *p < 0.05, ‡p < 0.001

Table II. DXA parameters, bone turnover markers and osteoporotic vertebral fractures in study groups Variable Vitamin D (nmol/l)

All patients (n = 218)

Patients without MS (n = 102)

Patients with MS (n = 116)

19.5 (13.45–30.42)

19.37 (14.17–29.87)

19.61 (12.38–30.75)

uOC (µg/l)

1.75 (1.28–2.96)

1.95 (1.34–4.13)

1.70 (1.25–2.59)

CTX (ng/ml)

0.33 (0.22–0.43)

0.36 (0.23–0.47)

0.31 (0.19–0.42)

10.17 (7.58–12.48)

10.23 (7.68–12.48)

10.01 (7.56–12.56)

1.017 ± 0.195

0.987 ± 0.181

1.043 ± 0.203*

BAP (µg/l) Lumbar spine BMD (g/cm2) Lumbar spine T score

–1.41 ± 1.57

–1.61 ± 1.4

–1.23 ± 1.69

Femoral neck BMD (g/cm2)

0.845 ± 0.142

0.840 ± 0.128

0.850 ± 0.153

Femoral neck T score

–1.27 ± 1.12

–1.30 ± 1.03

–1.23 ± 1.21

Total hip BMD (g/cm )

0.910 ± 0.164

0.891 ± 0.158

0.927 ± 0.168

Total hip T score

–0.75 ± 1.26

–0.92 ± 0.2

–0.60 ± 1.31

34 (15.6)

13 (12.7)

21 (18.1)

2

Osteoporotic vertebral fractures (T4–L5)

Values are shown as n (%), mean ± SD, or median (25th percentile–75th percentile). n: number of patients; MS: metabolic syndrome; BMD: bone mass density; uOC: undercarboxylated osteocalcin; CTX: serum collagen type 1 cross-linked C-telopeptide; BAP: bone alkaline phosphatase; *p < 0.05 Acta Physiologica Hungarica 101, 2014

0.164

–0.014

–0.154

0.057

0.008

0.500

0.816

0.021

0.562

0.129

0.179

0.046

–0.016

–0.157

–0.039

–0.093

Triglycerides

Glucose

CRP U-hs

Vitamin D

uOC

CTX

BAP

0.104

–0.13

0.036

0.14

0.012

0.021

0.056

0.603

0.04

0.855

0.754

0.05

0.029

0.264

0.95

0.292

r p < 0.001

r 0.242



–0.150

–0.089

–0.072

0.169

0.038

0.153

0.012

–0.038

0.029

0.289

0.234

0.076 –0.171

0.026

0.092

0.093

0.089

0.092

0.038

0.070

–0.015

0.191

0.291

0.013

0.572

0.024

0.862

0.581

0.672

< 0.001

–0.339 < 0.001 –0.172

0.354

–0.301 < 0.001

0.012

0.264

0.178

0.172

0.192

0.178

0.581

0.301

0.822

0.001

0.011

< 0.001



p

r –



p

0.194

0.069

0.075

0.098

0.045

0.053

0.036

–0.042

–0.001

0.06

0.004

0.31

0.275

0.153

0.51

0.436

0.59

0.54

0.99

0.382

–0.156 0.023





BMD: bone mass density; BMI: body mass index; WC: waist circumference; CTX: serum collagen type 1 cross-linked Ctelopeptide; CRP U-hs: Ultra-High Sensitive C Reactive Protein; uOC: undercarboxylated osteocalcin; TC: Total cholesterol; HDL-C: HDL cholesterol; BAP: bone alkaline phosphatase

0.111

0.527

0.023

0.842

0.384

0.131

0.149

0.016

0.076

0.030

0.004

0.072

0.133

0.888

0.001

0.003





p

3 (n = 42)

–0.043

0.064

–0.102



0.001 –0.203

0.001

r –

2 (n = 65)

0.172

0.147

0.152

–0.097

HDL-C

0.230

0.900

p –

Controlling for age and BMI

1 (n = 28)

–0.010

0.001

0.231

–0.172

0.020

–0.009

–0.158

Time since menopause

0.229

< 0.001

TC

0.237

BMI



r

Controlling for age

0.232

p

Femoral neck BMD Unadjusted correlation coefficients

Controlling for age

Controlling for age and BMI

Lumbar spine BMD

0 (n = 9)

WC

–0.081

Age

r

Unadjusted correlation coefficients

Table IV. Lumbar spine and femoral neck BMD correlations with clinical, laboratory data (unadjusted, controlling for age, and controlling for age and BMI)

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Table III. L2–L4 lumbar spine and femoral neck BMD depending of the number of components of the metabolic syndrome Number of metabolic syndrome components 4 (n = 53) 5 (n = 21) p value

Lumbar spine BMD 0.885±063 0.933±0.36 1.025±0.23 1.025±0.029 1.028±0.029 1.156±0.041 < 0.01 – unadjusted 0.882±0.062 0.923±0.036 1.025±0.023 1.026±0.03 1.026±0.026 1.156±0.041 < 0.01 – adjusted for age

Femoral neck BMD 0.805±0.047 0.805±0.026 0.861±0.017 0.862±0.022 0.870±0.019 0.900±0.031 < 0.05 – unadjusted 0.798±0.043 0.779±0.025 0.860±0.016 0.861±0.02 0.862±0.018 0.900±0.028 < 0.001 – adjusted for age

n: number of patients; BMD: bone mass density

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The lumbar spine BMD was positively correlated with BMI, waist circumference, time since menopause, glucose serum levels, and negatively correlated with uOC levels (all p < 0.05, Table IV). After age adjustment, these correlations persisted, and in addition, a positive correlation between triglyceride levels and lumbar spine BMD was observed. Furthermore, lumbar spine BMD correlated with hypertension (p < 0.001), but not with diabetes (p = 0.15). The femoral neck BMD was positively correlated with BMI, waist circumference, glucose and vitamin D serum levels, and negatively correlated with BAP levels (all p < 0.05, Table IV). After age adjustment the correlations remained, except for glucose and vitamin D. For both sites age and BMI adjustment reversed the relation with waist circumference (Table IV). Multiple linear regression analysis (enter linear regression) showed that among components of the MS, waist circumference and hypertension were independently associated with lumbar spine BMD (standardized b coefficient = 0.135; p = 0.047, respectively, standardized b coefficient = 0.161; = 0.023). Waist circumference was also independently associated with femoral neck BMD (standardized b-coefficient = 0.200; p = 0.001). The cut-off value of 1.165 g/cm2 for the lumbar spine BMD yielded 86.3% specificity and 31.9% sensitivity for diagnosis of MS (AUC = 0.583 [95% CI, 0.514–0.649, p = 0.03]). The presence of MS could be considered an independent factor for BMD >1.165 (OR 1.595; 95% CI 1.128 to 2.250; p = 0.008). From the components of the MS, only the presence of hypertension was independently associated with lumbar spine BMD > 1.165 g/cm2 (OR 1.612; 95% CI 1.027 to 2.53; p = 0.038). Discussions We performed a cross-sectional analysis of the relationship between the presence of MS and bone parameters in a cohort of postmenopausal women. We found that MS was related to lumbar spine BMD but not with femoral neck or total hip BMD and this relationship remained after age adjustment. The BMD values of both sites progressively increase with the number of MS components. The presence of MS could be considered an independent factor for lumbar spine BMD higher than 1.165 g/cm2. Bone turnover markers and vitamin D levels were not significantly influenced by the presence of MS. Our results agreed with previous studies that demonstrated a higher BMD at lumbar spine and/or hip among postmenopausal women or men with MS as compared with subjects without MS (16, 28). In the Camargo Cohort Study (16), women with MS had higher ageadjusted BMD at lumbar spine and hip than controls, and this was mainly due to a higher body weight in the MS group. In another study by the same group (15), this relationship was also found by comparison of the bone ultrasound parameters between women with MS and those without MS. Moreover, a recent meta-analysis (40), has documented a significant association of MS with increased spine BMD. Several researchers found that the association between BMD and MS was altered after BMI adjustment (15, 16, 36). In their meta-analysis, Xue et al. (40) concluded that when adjusting BMD for BMI, “the clinical sense of MS just disappeared, or was at least essentially modified”. We also found that BMI adjustment of BMD at both sites reversed the relationship with waist circumference. We concluded that the relationship between MS and BMD should be analysed with BMI as part of the MS not as a confounding factor. Some researchers found that patients with MS had lower BMD than patients without MS (17, 19), while others could not find any difference between BMD values of subjects with MS and controls (35, 43). Acta Physiologica Hungarica 101, 2014

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We found that lumbar spine and femoral neck BMD increased with the number of the individual components of the MS and this relation remained after age adjustment. Knowing that the vertebral bodies are made up of approximately 80% trabecular bone, while femoral neck comprised 65% trabecular bone and 35% cortical bone (32), our results suggest that MS may have an influence on trabecular and probably on cortical bone. Also, the increase in BMD was apparent independently of whichever of the 5 components of the MS was present. Kinjo et al. (21) found the same trend for a higher femoral neck BMD as the number of MS components increased. A reduced number of non-vertebral fractures by increasing the number of MS components was also reported (2). Abdominal obesity, a key component of the MS, was associated with high bone mass through the estrogen production from adipocytes (the main source for estrogen in postmenopausal women) and with insulin resistance (25). A larger body mass was associated with a higher mechanical load on bone due to gravitational effect, leading to an increase in bone mass in order to accommodate to a greater load (8, 33). The relationship seems to be more complex, the fat tissue also secreting various proinflammatory cytokines with a detrimental effect on the bone, for example leptin that may inhibit bone formation (6). In the study of Kim et al. (20) the waist circumference, as an indicator of visceral fat mass, and percentage of body fat were found to be related with low BMD and high risk for vertebral fracture. Also, Zhao et al. (44) correlated the fat mass with low BMD after the mechanical loading effects of body weight on bone mass were controlled. The authors suggest that body mass per se does not have a protective effect on bone mass. Yamaguchi et al. (41) underlined the role of gravity when the influence of the body weight (especially visceral fat) on the bone mass is analysed. In our study, hypertension was independently associated with lumbar spine BMD but we could not explain this relation. Hanley et al. (14) found also a positive relation between hypertension and lumbar spine, femoral neck, and trochanter BMD, a relationship unaltered after covariate variables adjustment. In the Lidfeldt et al. study (23) the wrist BMD was associated with systolic and diastolic blood pressure in postmenopausal women without hormone replacement. Tseng et al. (35) established a strong inverse correlation between diastolic blood pressure and bone-mineral loss. A direct relationship between hypertension and BMD was found also by Hernández et al. (16) and, moreover, Ahmed et al. (2) showed a protective effect of hypertension for non-vertebral fractures in men. None of these authors could offer a satisfactory physiopathological explanation for these findings. In contrast, in other studies high blood pressure was inversely correlated with BMD via abnormal calcium metabolism, secondary parathyroid hormone secretion, or sodium intake (5, 18, 27, 37). We found no correlation between HDL-C and BMD, while serum TG positively correlated with lumbar spine BMD after age and BMI adjustment. Szulc et al. (34) related the lower fracture risk to hypertriglyceridemia. Experimental data suggest that TG may mediate the interaction between protein matrix and BMD, improving the qualitative properties of the bone (39). In our study the glucose level was positively correlated with lumbar spine BMD. A positive correlation between glucose and BMD was demonstrated in some studies (6, 21, 36, 41, 44), but absence of correlation was found as well (16, 17). Reduced serum total OC was previously associated with MS in men (34, 42). CTX was found to be lower (15) and BAP higher in postmenopausal women with MS (19). We cannot confirm these associations because we obtained no significant differences between the nonMS and MS groups concerning the bone turnover markers or vitamin D. CRP U-hs is considered to be a marker for low-grade systemic inflammation (31) and association between CRP and MS is well known (26). In our study the serum levels of CRP U-hs were higher in Acta Physiologica Hungarica 101, 2014

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patients with MS as compared with controls, but the difference suggests only a trend for significance. Probably the modality of selection of the study group (from referred patients, including patients hospitalized in Internal Medicine or Rheumatology departments) is the cause for the lack of significance. In our study group there was a high prevalence of the MS (53.2%). One explanation could be the modality of selection – from patients referred for DXA measurement (including in-hospital patients) and not from the community. Also, the higher frequency of the components of the MS in our study group is probably related to the postmenopausal status and to the mean age around 65 years. We do not know the real prevalence of MS in the general population of Romania but Matei et al. (24), in a cross-sectional study on 1326 patients from a Romanian cardiology department found 42.8% prevalence for MS. More extensive studies on MS prevalence in the Romanian population are required. The high frequency of the MS in the general population of the Balkan countries (one out of three or four persons) highlights the epidemic character of the problem and the necessity for effective preventive measures (29). Another important problem, already underlined in a previous published paper (9), is the poor vitamin D status of the patients included in the study. The unexpectedly high prevalence of hypovitaminosis D among these women living in a region with temperate climate can be explained by several factors. One possible explanation is that we did not take into account the considerable fluctuation of vitamin D values that are usually observed in various months. The enrolment period in this study lasts from September 2009 until September 2010, but the majority of the patients were enrolled during winter. In addition, many subjects in our study were in-hospital patients with cardiovascular risk factors or established cardiovascular diseases. In Romania low levels of vitamin D were found also in elderly patients with diabetes mellitus (11) or in healthy people (30) suggesting the possibility of a national health problem concerning the vitamin D status. Our study has several limitations. First, the cross-sectional nature of the study implies that no causal inferences can be drawn and the temporal relationship between BMS and MS was not assessed. As we already mentioned, the study group was selected from patients who had been referred for DXA measurement and not from the community, and there might have been a selection bias. Also, the results cannot be generalized regarding men, premenopausal women or non-Caucasian subjects. The sample size was not large enough to make definite conclusions. Other variables known to affect BMD and vitamin D status, as calcium intake and physical activity were not assessed. Moreover, we did not measure parathormone levels, which could have provided valuable information on bone turnover in this group characterized by a high rate of vitamin D deficiency. In our study population we decided not to collect data on non-vertebral fractures since the number of patients that could be enrolled in the study was unlikely to be adequate to give reliable information on this clinical endpoint. Residual confounding by factors which we failed to control could have also influenced our findings. In conclusion, we found that postmenopausal women with MS had higher lumbar spine BMD, suggesting a protective effect of the MS on bone. The relation was explained mainly by the higher BMI and waist circumference in the MS group. In addition, hypertension seems to influence the lumbar spine BMD in this group. The BMD values of the lumbar spine and femoral neck progressively increase with the numbers of MS components. Further large longitudinal studies, in different populations, are required for clarification of the relationship between MS and BMD. Acta Physiologica Hungarica 101, 2014

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Funding Sources This work was supported by the ANCS (Romanian National Authority for Scientific Research) 42107/2008 PNII grant.

Authors’ Contribution DF: conception, design, interpretation, coordination of the work, and writing the manuscript; SV: execution of the statistical analysis and interpretation of the study; AA: recruitment of subjects, revision of the manuscript; SS: execution and interpretation of BMD; AC: execution of biochemical studies and interpretation of the results; LM: execution and interpretation of BMD, revision of the manuscript, corresponding author.

Conflict of Interest There is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.



REFERENCES 1.  Guidelines for the management of arterial hypertension. The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur. Heart J. 28, 1462–1536 (2007) 2.  Ahmed LA, Schirmer H, Berntsen GK, Fønnebø V, Joakimsen RM: Features of the metabolic syndrome and the risk of non-vertebral fractures: The Tromsø study. Osteoporos. Int. 17, 426–432 (2006) 3.  Albala C, Yáñez M, Devoto E, Sostin C, Zeballos L, Santos JL: Obesity as a protective factor for postmenopausal osteoporosis. Int. J. Obes. Relat. Metab. Disord. 20, 1027–1032 (1996) 4.  Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr; International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity: Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute: American Heart Association; World Heart Federation: International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 120, 1640–1645 (2009) 5.  Cappuccio FP, Meilahn E, Zmuda JM, Cauley JA: High blood pressure and bone-mineral loss in elderly white women: a prospective study. Study of Osteoporotic Fractures Research Group. Lancet 354, 971–975 (1999). 6.  Ducy P, Amling M, Takeda S, Priemel M, Schilling AF, Beil FT, Shen J, Vinson C, Rueger JM, Karsenty G: Leptin inhibits bone formation through a hypothalamic relay: a central control of bone mass. Cell 100, 197–207 (2000) 7.  Farhat GN, Cauley JA: The link between osteoporosis and cardiovascular disease. Clin. Cases Miner. Bone Metab. 5, 19–34 (2008) 8.  Felson DT, Zhang Y, Hannan MT, Anderson JJ: Effects of weight and body mass index in men and women: the Framingham study. J. Bone Miner. Res. 8, 567–573 (1993) 9.  Fodor D, Bondor C, Albu A, Simon SP, Craciun A, Muntean L: The value of osteopontin in the assessment of bone mineral density status in postmenopausal women. J. Investig. Med. 61, 15–21 (2013) 10.  Genant HK, Wu CY, van Kuijk C, Nevitt MC: Vertebral fracture assessment using a semiquantitative technique. J. Bone Miner. Res. 8, 1137–1148 (1993) 11.  Gradinaru D, Borsa C, Ionescu C, Margina D, Prada GI, Jansen E: Vitamin D status and oxidative stress markers in the elderly with impaired fasting glucose and type 2 diabetes mellitus. Aging Clin. Exp. Res. 24, 595–602 (2012) 12.  Greco EA, Fornari R, Rossi F, Santiemma V, Prossomariti G, Annoscia C, Aversa A, Brama M, Marini M, Donini LM, Spera G, Lenzi A, Lubrano C, Migliaccio S: Is obesity protective for osteoporosis? Evaluation of bone mineral density in individuals with high body mass index. Int. J. Clin. Pract. 64, 817–820 (2010) 13.  Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, Spertus JA, Costa F: American Heart Association; National Heart, Lung, and Blood Institute: Acta Physiologica Hungarica 101, 2014

226

Fodor D et al.

Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 112, 2735–2752 (2005) 14.  Hanley DA, Brown JP, Tenenhouse A, Olszynski WP, Ioannidis G, Berger C, Prior JC, Pickard L, Murray TM, Anastassiades T, Kirkland S, Joyce C, Joseph L, Papaioannou A, Jackson SA, Poliquin S, Adachi JD: Canadian Multicentre Osteoporosis Study Research Group: Associations among disease conditions, bone mineral density, and prevalent vertebral deformities in men and women 50 years of age and older: cross-sectional results from the Canadian Multicentre Osteoporosis Study. J. Bone Miner. Res. 18, 784–790 (2003) 15.  Hernández JL, Olmos JM, de Juan J, Martínez J, Ramos C, Valero C, Nan D, González-Macías J: Heel quantitative ultrasound parameters in subjects with metabolic syndrome: the Camargo Cohort Study. Maturitas 69, 162–167 (2011) 16.  Hernández JL, Olmos JM, Pariente E, Martinez J, Valero C, Garcia-Velasco P, Nan D, Llorca J, GonzalesMacias J: Metabolic syndrome and bone metabolism: the Camargo Cohort study. Menopause 17, 955–961 (2010) 17.  Hwang DK, Choi HJ: The relationship between low bone mass and metabolic syndrome in Korean women. Osteoporos. Int. 21, 425–431 (2010) 18.  Jeon YK, Lee JG, Kim SS, Kim BH, Kim SJ, Kim YK, Kim IJ: Association between bone mineral density and metabolic syndrome in pre- and postmenopausal women. Endocr. J. 58, 87–93 (2011) 19.  Kim HY, Choe JW, Kim HK, Bae SJ, Kim BJ, Lee SH, Koh JM, Han KO, Park HM, Kim GS: Negative association between metabolic syndrome and bone mineral density in Koreans, especially in men. Calcif. Tissue Int. 86, 350–358 (2010) 20.  Kim KC, Shin DH, Lee SY, Im JA, Lee DC: Relation between obesity and bone mineral density and vertebral fractures in Korean postmenopausal women. Yonsei Med. J. 51, 857–863 (2010) 21.  Kinjo M, Setoguchi S, Solomon DH: Bone mineral density in adults with metabolic syndrome: analysis in a population-based U.S. sample. J. Clin. Endocrinol. Metab. 92, 4161–4164 (2007) 22.  Lee WY, Park JS, Noh SY, Rhee EJ, Sung KC, Kim BS, Kang JH, Kim SW, Lee MH, Park JR: C-reactive protein concentrations are related to insulin resistance and metabolic syndrome as defined by the ATP III report. Int. J. Cardiol. 97, 101–106 (2004) 23.  Lidfeldt J, Holmdahl L, Samsioe G, Nerbrand C, Nyberg P, Scherstén B, Agardh CD: The influence of hormonal status and features of the metabolic syndrome on bone density: a population-based study of Swedish women aged 50 to 59 years. The women’s health in the Lund area study. Metabolism 51, 267–270 (2002) 24.  Matei C, Pop I, Jurcut R, Suceveanu M, Predescu D, Nechita E, Ionescu P, Ciovica D, Ginghina C: Romanian multicentric study of the prevalence of metabolic syndrome-ROMES. Hellenic J. Cardiol. 49, 303–309 (2008) 25.  Migliaccio S, Greco EA, Fornari R, Donini LM, Lenzi A: Is obesity in women protective against osteoporosis? Diabetes Metab. Syndr. Obes. 4, 273–282 (2011) 26.  Oda E, Kawai R: Comparison between high-sensitivity C-reactive protein (hs-CRP) and white blood cell count (WBC) as an inflammatory component of metabolic syndrome in Japanese. Intern. Med. 49, 117–124 (2010) 27.  Orwoll ES, Bevan L, Phipps KR: Determinants of bone mineral density in older men. Osteoporos. Int. 11, 815–821 (2000) 28.  Park KK, Kim SJ, Moon ES: Association between bone mineral density and metabolic syndrome in postmenoupausal Korean Women. Gynecol. Obstet. Invest. 69, 145–152 (2010) 29.  Pitsavos C: The prevalence of the metabolic syndrome is high in Balkan countries. Hellenic J. Cardiol. 49, 310–311 (2008) 30.  Porojnicu AC, Moroti-Constantinescu R, Laslau A, Lagunova Z, Dahlback A, Hristea A, Moan J: Vitamin D status in healthy Romanian caregivers and risk of respiratory infections. Public Health Nutr. 15, 2157–2162 (2012) 31.  Ridker PM, Wilson PWF, Grandy SM: Should C-reactive protein be added to metabolic syndrome and to assessment of global cardiovascular risk? Circulation 109, 2818–2825 (2004) 32.  Riggs BL, Melton Iii LJ 3rd, Robb RA, Camp JJ, Atkinson EJ, Peterson JM, Rouleau PA, McCollough CH, Bouxsein ML, Khosla S: Population-based study of age and sex differences in bone volumetric density, size, geometry, and structure at different skeletal sites. J. Bone Miner. Res. 19, 1945–1954 (2004) 33.  Skerry TM, Suva LJ: Investigation of the regulation of bone mass by mechanical loading: from quantitative cytochemistry to gene array. Cell Biochem. Funct. 21, 223–229 (2003) 34.  Szulc P, Varennes A, Delmas PD, Goudable J, Chapurlat R: Men with metabolic syndrome have lower bone mineral density but lower fracture risk-the MINOS study. J. Bone Miner. Res. 25, 1446–1454 (2010)

Acta Physiologica Hungarica 101, 2014

Metabolic syndrome and bone status

227

35.  Tseng YH, Huang KC, Lui ML, Shu WT, Sheu WH: Association between metabolic syndrome (MS) and bone mineral loss: a cross-sectional study in Puli Township in Taiwan. Arch. Gerontol. Geriatr. 49 Suppl 2, S37–S40 (2009) 36.  von Muhlen D, Safii S, Jassal SK, Svartberg J, Barrett-Connor E: Associations between the metabolic syndrome and bone health in older men and women: the Rancho Bernado Study. Osteoporos. Int. 18, 1337–1344 (2007) 37.  Woo J, Kwok T, Leung J, Tang N: Dietary intake, blood pressure and osteoporosis. J. Hum. Hypertens. 23, 451–455 (2009) 38.  World Health Organization Department of Non-Communicable Disease Surveillance. Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications (1999) 39.  Xu S, Yu JJ: Beneath the minerals, a layer of round lipid particles was identified to mediate collagen calcification in compact bone formation. Biophys. J. 91, 4221–4229 (2006) 40.  Xue P, Gao P, Li Y: The association between metabolic syndrome and bone mineral density: a meta-analysis. Endocrine 42, 546–554 (2012) 41.  Yamaguchi T, Kanazawa I, Yamamoto M, Kurioka S, Yamauchi M, Yano S, Sugimoto T: Associations between components of the metabolic syndrome versus bone mineral density and vertebral fractures in patients with type 2 diabetes. Bone 45, 174–179 (2009) 42.  Yeap BB, Chubb SA, Flicker L, McCaul KA, Ebeling PR, Beilby JP, Norman PE: Reduced serum total osteocalcin is associated with metabolic syndrome in older men via waist circumference, hyperglycemia, and triglyceride levels. Eur. J. Endocrinol. 163, 265–272 (2010) 43.  Yoldemir T, Erenus M: The impact of metabolic syndrome on bone mineral density in postmenopausal women. Gynecol. Endocrinol. 28, 391–395 (2012) 44.  Zhao LJ, Liu YJ, Liu PY, Hamilton J, Recker RR, Deng HW: Relationship of obesity with osteoporosis. J. Clin. Endocrinol. Metab. 92, 1640–1646 (2007)

Acta Physiologica Hungarica 101, 2014

The relationship between the metabolic syndrome and its components and bone status in postmenopausal women.

The association between metabolic syndrome (MS) and bone status remains controversial. We aimed to study the relationships between MS, bone mineral de...
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