Arch Gynecol Obstet DOI 10.1007/s00404-015-3698-x
GYNECOLOGIC ENDOCRINOLOGY AND REPRODUCTIVE MEDICINE
The relationship between bone mineral density and metabolic syndrome in peri- and post-menopausal Thai women Suchada Indhavivadhana1 • Panwad Rattanasrithong1
Received: 23 January 2015 / Accepted: 20 March 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract Purposes To compare the bone mineral density (BMD) measured in the lumbar spine and femoral neck in peri- and post-menopausal Thai women with and without metabolic syndrome, and to determine which contributory factors associated with metabolic syndrome influence BMD. Methods 427 peri- or post-menopausal Thai women were screened against the modified National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) for Asian populations’ criteria for metabolic syndrome. The BMD of those with and without metabolic syndrome was compared, and potential relationships between the factors associated with metabolic syndrome and BMD were sought. Results There was no difference in lumbar spine or femoral neck BMD between the groups (p = 0.605 and 0.415, respectively), but women with central obesity (waist circumference C80 cm, p = 0.004 and [88 cm, p = 0.002), low serum high-density lipoprotein cholesterol (HDL-C) concentration (p = 0.011) and a greater number of contributory factors to metabolic syndrome (p = 0.007) had significantly higher BMD at the femoral neck. Conclusions A diagnosis of metabolic syndrome did not correlate with either lumbar spine or femoral neck BMD. However, higher femoral neck BMD was significantly associated with increased waist circumference, low serum
& Suchada Indhavivadhana [email protected] 1
Gynecologic Endocrinology Unit, Division of Reproductive Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Prannok Rd, Bangkok Noi, Bangkok 10700, Thailand
HDL-C concentration and the number of contributory factors to metabolic syndrome. Keywords Metabolic syndrome Bone mineral density Menopause
Introduction Osteoporosis is characterized by low bone mass, microarchitectural deterioration of bone tissue leading to enhanced bone fragility, and a consequent increase in fracture risk. The prevalence of osteoporotic fracture increases with age. Osteoporosis affects women more than men, as postmenopausal estrogen deficiency is the main contributor to a rapid decline in bone density. As global populations age, osteoporosis is likely to become even greater a clinical problem [1, 2]. Prevention and early intervention in highrisk cases with rapid bone loss are likely the best management strategies. The bone mineral density (BMD) of the spine, hip and femur is measured using dual-energy X-ray absorptiometry-type bone densitometry (DXA). The T score and Z score are calculated with reference to the normal values for an age- and sex-matched population, and the diagnosis of osteoporosis is made according to the World Health Organization (WHO) criteria [3]. Metabolic syndrome comprises a combination of central obesity, dyslipidemia, impaired glucose tolerance and hypertension. Several expert groups have attempted to develop a definition for metabolic syndrome: the most widely accepted are those of the WHO, the European Group for the Study of Insulin Resistance (EGIR), the National Heart, Lung and Blood Institute and American Heart Association criteria (NHLBI/AHA), and the National Cholesterol
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Education Program-Third Adult Treatment Panel (NCEP ATP III), with the latter being in widest use [4, 5]. Several studies have demonstrated associations between metabolic syndrome and BMD, but their results have been inconsistent, as shown in Table 1. Most studies enrolled women of a wide variety of ages and none has focused on women in the menopausal or peri-menopausal state. The relationship between BMD and metabolic syndrome in menopausal or peri-menopausal Thai women has not been examined. We sought to compare BMD in the lumbar spine and femoral neck in women in this population with and without metabolic syndrome, and to determine which aspects of metabolic syndrome influence BMD, with the aim of identifying those most at risk of osteoporosis and to inform diagnostic strategy.
Materials and methods The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and its protocol No. 337/2554(EC4) was approved by the Siriraj Institutional Review Board of Mahidol University, Bangkok, Thailand. We enrolled 427 peri- and post-menopausal Thai women undergoing BMD assessments at the Siriraj Menopause Clinic, Mahidol University Hospital, between 2004 and 2012. We recorded participants’ socio-demographic and clinical characteristics, history of comorbid disease (with a particular focus on diabetes mellitus, hypertension and cardiovascular diseases) and family history of comorbid disease, and undertook physical examination and blood tests. The detailed methods of physical examination (including measurement of height, body weight, blood pressure and waist circumference) and laboratory testing used to make the diagnosis of metabolic syndrome were described in our previous report [6]. The peri–postmenopausal women who had inadequate data for diagnosed metabolic syndrome and currently taking hormone therapy or osteoporosis treatment were excluded. Definition of menopausal status [7] Participants were categorized into one of three groups on the basis of their menopausal status (perimenopause, natural menopause or surgical menopause) using the same criteria as our previous report [6, 7]. Criteria for diagnosis of osteoporosis Bone mineral density was measured using DXA (Lunar Prodigy DF?15974), calibrated daily using the standard phantom provided by the manufacturer. The equipment
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was operated by experienced technicians in the Division of Endocrinology and Metabolism, Department of Medicine, Siriraj Hospital. The mean of second to fourth lumbar vertebral (lumbar spine BMD) and femoral neck BMD was recorded. Those with a BMD T score at or below -2.5 were diagnosed with osteoporosis based on the WHO criteria [3]. Criteria for diagnosis of metabolic syndrome We used the NCEP ATP III criteria modified for use in an Asian population to diagnose metabolic syndrome [5]. These require the presence of three of the five following factors: (i) abdominal obesity defined as Asian waist circumference (WC) C80 cm; (ii) elevated blood pressure defined as systolic BP C130 mmHg or diastolic BP C85 mmHg, or previously treated hypertension; (iii) elevated fasting plasma glucose C110 mg/dL, or previously diagnosed type 2 diabetes mellitus; (iv) reduced serum high-density lipoprotein cholesterol (HDL-C) concentration (\50 mg/dL); and (v) elevated serum triglyceride concentration (C150 mg/dL). Statistical analysis Data were analyzed using SPSS software (version 18). Data are presented as mean ± standard deviation (SD) or number (with proportion as a percentage) as appropriate. We undertook univariate analysis to determine whether metabolic syndrome significantly influenced lumbar spine or femoral neck BMD, analysis of variance (ANOVA) for continuous data and the Chi-square test for categorical data. Pearson’s rank-order correlation was used to determine the correlation coefficient (r) between the contributors to metabolic syndrome and BMD. A p value \0.05 was considered statistically significant.
Results Of the 427 women enrolled, 51 (11.9 %) had metabolic syndrome and 23 (5.4 %) had osteoporosis. None of the participants had received hormone treatment. The demographic and clinical characteristics of all subjects according to the presence or absence of metabolic syndrome are shown in Table 2. The mean age of all subjects was 52.6 ± 5.4 years, but the metabolic syndrome group was significantly older (54.7 ± 5.4 years compared with 52.3 ± 5.4 years, respectively; p = 0.004). There were no statistically significant differences in menopausal status, regions of residence, education, parity, lifestyle (for example, exercise, smoking and alcohol drinking habits), the use of calcium supplements and type of diet, or family
Non 706
NCEP ATP III WC C88
MS 60.2 ± 7.4
Non 59.2 ± 6.6
FBS C100
WC [85 Korea
Korea
Korea
Spain
America
America
Country
Similar (adjusted)
Higher
Lower
–
Higher
Similar (adjusted)
Higher
–
Result in lumbar BMD
Similar (adjusted)
Higher
–
Similar Lower
Higher
Similar (adjusted)
Higher
Similar (adjusted BMI)
Higher
Result in femoral neck BMD
HDL was negatively associated with BMD
Central obesity and hypertriglyceride had lower BMD
Triglyceride was negatively associated with BMD
HT and central obesity had higher BMD
Increased numbers of components had lower BMD
FBS was positively associated with BMD
Increased numbers of components and diabetes had higher BMD
Result in MS parameters
BMD bone mineral density, MS metabolic syndrome, WC waist circumference, FBS fasting blood sugar, HT hypertension, NCEP APT III National Cholesterol Education Program Adult Treatment Panel III, NHLBI/AHA National Heart Lung and Blood Institutes/American Heart Association, IDF International Diabetes Federation, ADA American Diabetes Association
Non 325
MS 74
Non 1964
Asia–Pacific and ADA 2003
MS 56.3 ± 9.7
Non 45.3 ± 11.1
Non 917 MS 511
NCEP ATP III
Non 56.6 ± 6.7
FBS C100
MS 191
WC C80
MS 60.7 ± 6.0
21–94
MS 231 Non 877
NHLBI/AHA IDF
MS 60.3 ± 6.4 Non 56.2 ± 6.6
FBS C100
Data are number, or range, or mean ± standard deviation, or percent
Park et al. [13]
Hwang and Choi [12]
Kim et al. [11]
Hernandez et al. [10] WC [88
FBS C110
Non 74.0 ± 0.5
Non 61.8 ± 9.6
Non 549
WC [88
MS 75.9 ± 0.9
MS 307
MS 122
NCEP ATP III
38–97
NCEP ATP III
Female 56 %
FBS C110
Non 44.2 ± 8.7
MS 66.7 ± 9.6
Non 6424
WC [88
MS 56.7 ± 16.7
von Muhlen et al. [9]
MS 1773
NCEP ATP III
[20
Kinjo et al. [8]
Sample size of women
Diagnostic criteria for MS
Age (year)
References
Table 1 Summary of cross-sectional studies surveying women with metabolic syndrome, its components and BMD
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Arch Gynecol Obstet Table 2 Characteristics of peri-/post-menopausal Thai
Characteristics
pa
Metabolic syndrome Non-MS
MS
N
N
Mean ± SD or n (%)
Mean ± SD or n (%)
Age, year
376
52.34 ± 5.36
51
54.66 ± 5.35
0.004
Age at menopause, yearb
283
48.67 ± 4.24
42
48.73 ± 4.9
0.930
Duration since menopause, yearb
283
4.87 ± 4.01
42
6.79 ± 6.05
0.008
Regions of resident, Bangkok
263
70.5
33
66
0.514
Education, lower education level
24
20.2
1
7.7
0.461
Occupation, no
77
21.6
19
37.3
0.013 0.379
Parity Nulliparous
131
35.0
15
28.6
243
65.0
37
71.2
90
23.9
9
17.6
Natural menopause
232
61.7
33
64.7
Surgical menopause
54
14.4
9
Parous Menstrual status Perimenopause
BMI, kg/M2
0.560
376
23.39 ± 3.46
\23.0
190
50.5
23.0–29.9
174
46.3 3.2
51
17.6 26.53 ± 3.27
0.000
5
9.8
0.000
39
76.5
C30.0
12
WC, cm
376
76.02 ± 7.02
51
7
84.84 ± 6.37
13.7
C80.0
118
31.4
46
90.2
0.000
[88.0
30
8.0
14
27.5
0.000
19
5.1
9
17.6
0.003
0.000
Blood pressure, mmHg C130/85 Exercise, yes Cardiovascular exercise
80
81.6
5
71.4
0.616
Regular exercise
81
84.4
6
75.0
0.614
Smoking, yes
2
0.5
2
3.9
0.072
Alcohol drinking, yes
11
2.9
2
3.9
0.660
Calcium, use
48
12.8
3
6.0
0.166
High fiber diet
81
77.9
9
81.8
1.000
High protein diet
30
28.8
5
45.5
0.306
High carbohydrate diet
22
21.2
5
45.5
Diet
Medical disease No
80.8
21
46.7
4
1.1
1
2.2
Hypertension
25
6.7
10
22.2
Dyslipidemia
37
9.9
4
8.9
6
1.6
9
20
231
62.3
31
62.0
42
11.3
7
14.0
Diabetes mellitus
At least two diseases Family History of metabolic disease No Diabetes mellitus
0.614 0.000
303
0.885
Hypertension
24
6.5
4
8.0
Dyslipidemia
37
10.0
3
6.0
At least two diseases
37
10.0
5
10.0
MS metabolic syndrome, BMI body mass index, WC waist circumference
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a
Data are analyzed using one-way ANOVA for continuous data, or Chi-square test for categorical data
b
Age at menopause and duration since menopause are calculated by excluding perimenopause cases
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history of comorbid metabolic disease between the groups. The duration of menopause was significantly longer in women with metabolic syndrome, who were also more likely to be unemployed and have higher body mass index (BMI), WC and blood pressure. Table 3 shows the risk factors for BMD. Lumbar spine BMD had a moderately significantly inverse relationship with age (r = - 0.335, p = 0.000) and duration of menopause (r = - 0.308, p = 0.000). Femoral neck BMD had mildly significantly inverse correlation with age (r = - 0.287, p = 0.000), time since menopause (r = - 0.231, p = 0.000) and serum triglyceride concentration (r = - 0.152, p = 0.000). Both BMI and WC correlated significantly with lumbar spine and femoral neck BMD. The association between metabolic syndrome, its components and BMD is shown in Table 4. Lumbar spine and femoral neck BMD were not significantly different in women with and without metabolic syndrome, even after adjustment for factors known to be associated with BMD (data not shown). None of the components of metabolic syndrome influenced lumbar spine BMD; however, women with central obesity (WC C80 cm, p = 0.004 and WC [88 cm, p = 0.002) and low serum HDL-C concentration (p = 0.011) had a significantly higher femoral neck BMD. Only femoral neck BMD was significantly influenced by the number of components of metabolic syndrome (p = 0.007).
Discussion Among the physiologic changes that occur during transition into menopause, those in reproductive endocrine function might particularly influence the risk of metabolic Table 3 Factors associating with bone mineral density in peri-/post-menopausal Thai
derangement. The incidences of increased WC, hypertension, impaired insulin sensitivity and dyslipidemia are reportedly increased in menopausal women [14, 15]. Consequently, the prevalence of metabolic syndrome increases with age, BMI and menopausal status [16, 17]. Furthermore, the risk of underlying comorbidities such as diabetes mellitus, hypertension and cardiovascular disease is increased [14]. We found that age, duration since menopause, central obesity and comorbidities were important factors. Level of education, exercise, smoking and alcohol intake did not appear to be risk factors for metabolic syndrome in our cohort. We also found that the incidence of osteoporosis was greater in more elderly women and those in the menopausal state. This broadly reflects the current understanding of osteoporosis, a disease of low bone mass and micro-architectural bone defects that increase the risk of bone fracture for which the risk factors include age, weight, low estrogen states, exercise, diet and genetic influences [1, 18, 19]. It is clear that the relationship between metabolic syndrome, its contributory factors and BMD is not yet fully understood. Kinjo and colleagues [8] reported in the Third National Health and Nutrition Examination Survey study that women with metabolic syndrome had higher lumbar BMD, which was consistent with findings in the femoral neck reported by Park and colleagues [13]. We found no statistically significant differences in BMD at either site in Thai women with or without metabolic syndrome. Notably, the menopausal women who participated in previous studies [8, 13] were of a broader age range, and generally had greater WC and BMI than our population. We did, however, find correlations between lumbar spine and femoral neck BMD and BMI, WC and since menopause. Interestingly, other investigators have reported similar
Factors
Lumbar spine BMD
Femoral neck BMD
r
p
r
p
Age (year)
-0.335
0.000
-0.287
0.000
Duration since last menstrual perioda (year)
-0.308
0.000
-0.231
0.000
0.151
0.002
0.293
0.000
-0.067
0.169
-0.028
0.568
Waist circumference (cm)
0.102
0.035
0.229
0.000
Systolic blood pressure (mmHg)
0.028
0.561
0.016
0.745
Diastolic blood pressure (mmHg)
0.080
0.098
0.050
0.307
Fasting blood glucose (mg/dL)
-0.049
0.314
-0.052
0.287
Triglyceride (mg/dL)
-0.048
0.321
-0.152
0.000
0.014
0.770
0.058
0.236
Body mass index (kg/M2) Parity Components of metabolic syndrome
HDL-C (mg/dL)
BMD bone mineral density, HDL-C high-density lipoprotein cholesterol Data were analyzed using Pearson’s rank correlation a
Age at menopause and duration since menopause are calculated by excluding perimenopause cases
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Arch Gynecol Obstet Table 4 Components of metabolic syndrome using modified NCEP ATP III criteria and bone mineral density in peri-/post-menopausal Thai women Factors
Lumbar spine BMD N
Metabolic syndrome
p
Mean ± SD
Femoral neck BMD N
Mean ± SD
51
1.069 ± 0.144
50
0.859 ± 0.123
375
1.057 ± 0.154
376
1.845 ± 0.116
\80 cm
262
1.053 ± 0.148
263
0.833 ± 0.119
C80 cm
164
1.068 ± 0.160
0.337
163
0.867 ± 0.119
0.004
[88 cm
44
1.090 ± 0.488
0.148
44
0.899 ± 0.111
0.002
367
1.054 ± 0.150
59
1.088 ± 0.164
Non-metabolic syndrome
0.605
p
0.415
Components of MS Waist circumference
Blood pressure \130/85 mmHg C130/85 mmHg or HT treatment
0.116
367
0.844 ± 0.119
59
0.862 ± 0.104
0.268
Fasting blood glucose \100 mg/dL
325
1.059 ± 0.151
326
0.849 ± 0.118
C100 mg/dL or DM treatment
98
1.059 ± 0.156
0.987
97
0.842 ± 0.107
0.614
C110 mg/dL or DM treatment
44
1.065 ± 0.173
0.816
43
0.841 ± 0.114
0.736
\150 mg/dL
343
1.060 ± 0.152
344
0.843 ± 0.115
C150 mg/dL
83
1.053 ± 0.155
0.698
82
0.859 ± 0.126
0.283
Triglyceride
HDL-C \50 mg/dL
76
1.089 ± 0.169
0.060
76
0.878 ± 0.127
0.011
\50 mg/dL or DLP treatment
118
1.075 ± 0.165
0.182
118
0.861 ± 0.124
0.120
C50 mg/dL
348
1.052 ± 0.149
348
0.840 ± 0.114
0
176
1.045 ± 0.133
177
0.821 ± 0.112
1
114
1.054 ± 0.161
114
0.865 ± 0.114
2
87
1.082 ± 0.180
87
0.860 ± 0.126
Number of MS criteria
0.491
0.007
3
29
1.067 ± 0.132
28
0.882 ± 0.100
4
17
1.092 ± 0.172
17
0.854 ± 0.129
5
3
1.093 ± 0.029
3
0.898 ± 0.066
Data are analyzed using unpaired t test for continuous data, and Chi-square test (or Fisher’s exact test) for categorical data
results to ours after adjustment for all covariates including age and BMI, making it reasonable to conclude that metabolic syndrome per se does not influence BMD. Many studies have reported that there is a relationship between osteoporosis and central adiposity, which in itself is recognized as causing insulin resistance and chronic inflammation underpinned by mediators such as interleukin-6, tumor necrosis factor-alpha and C-reactive protein [20, 21]. Inflammation and insulin resistance may promote bone reabsorption, reducing bone mass and BMD. It has also been proposed that obesity or high BMI might protect against excessive bone loss in aging by increasing mechanical loading [9, 13]. The complex interaction between these two pathophysiologic phenomena may account for the inconsistent findings of a number of studies [8, 9, 11, 13], including ours. Kim and colleagues’ finding that three of the
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components of metabolic syndrome were negatively associated with femoral neck BMD after multivariate adjustment may reflect the difficulty of separating cardiovascular diseases and metabolic syndrome when the two are so closely linked, and the complexity introduced using different diagnostic criteria for metabolic syndrome [11]. In our cohort, the individual components of metabolic syndrome had no significant influence on lumbar spine BMD, consistent with previous findings [13]. Nonetheless, we identified that femoral neck BMD in our population was influenced by central obesity, low serum HDL-C concentration and the number of components of metabolic syndrome. Women with central obesity, lower HDL-C concentration and additional numbers of metabolic syndrome components might have higher BMD similar to the previous result. It has been proposed that the mechanism
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underpinning the negative correlation between BMD and serum HDL-C concentration might be the relative lack of oxysterols available when serum HDL-C concentration is high, which in turn might reduce the osteogenic differentiation of mesenchymal stem cells [22]. Although our cross-sectional data were acquired retrospectively, the dataset was almost complete as a result of the comprehensive records made of all patients attending our clinic, and there were no missing data concerning metabolic components. Our study had several other limitations. First, serum calcium and phosphate concentrations were not measured, both of which may have influenced BMD. Second, we did not evaluate our subjects’ insulin resistance or inflammatory status, so we are unable to illuminate further the reported relationships between insulin resistance and inflammation [9, 20], or osteoporosis and inflammation [8, 9, 11, 13]. Finally, our subjects were selected solely from patients who visited our urban clinic, which may have resulted in selection bias that makes our findings less generalizable to the wider population of Thai women. In conclusion, we found that metabolic syndrome did not affect BMD in the lumbar spine or femoral neck in menopausal Thai women. However, some of the components of metabolic syndrome, including abdominal obesity, low serum HDL-C concentration and the number of contributory factors to metabolic syndrome were associated with a significantly increased femoral neck BMD. It may be beneficial to postpone BMD evaluation by DXA scan for determining osteoporosis, especially in the femoral neck, in menopausal women with these components of the metabolic syndrome. Acknowledgments The Siriraj Research Development Fund supported this study financially. The authors would like to thank all staff members in the Siriraj Menopause Clinic, and thanks also go to Miss Julaporn Pooliam and the Office for Research and Development for their kind assistance and valuable comments on research methodology. Conflict of interest Both authors are full-time staff members in the Faculty of Medicine, Siriraj Hospital, Mahidol University, which is a government non-profit university hospital; and neither has any conflict of interest to declare.
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4. Alberti KG, Zimmet P, Shaw J (2006) Metabolic syndrome—a new world-wide definition. A consensus statement from the international diabetes federation. Diabet Med 23:469–480 5. Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C (2004) Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation 109:433–438 6. Indhavivadhana S, Rattanachaiyanont M, Wongvananurak T, Kanboon M, Techatraisak K, Leerasiri P et al (2011) Predictors for metabolic syndrome in perimenopausal and postmenopausal Thai women. Climacteric 14:58–65 7. Utian WH (1999) The International Menopause Society menopause-related terminology definitions. Climacteric 2:284–286 8. Kinjo M, Setoguchi S, Solomon DH (2007) Bone mineral density in adults with the metabolic syndrome: analysis in a populationbased US sample. J Clin Endocrinol Metab 92:4161–4164 9. von Muhlen D, Safii S, Jassal SK, Svartberg J, Barrett-Connor E (2007) Associations between the metabolic syndrome and bone health in older men and women: the Rancho Bernardo Study. Osteoporos Int 18:1337–1344 10. Hernandez JL, Olmos JM, Gonzalez-Macias J (2011) Metabolic syndrome, fractures and gender. Maturitas 68:217–223 11. Kim HY, Choe JW, Kim HK, Bae SJ, Kim BJ, Lee SH et al (2010) Negative association between metabolic syndrome and bone mineral density in Koreans, especially in men. Calcif Tissue Int 86:350–358 12. Hwang DK, Choi HJ (2010) The relationship between low bone mass and metabolic syndrome in Korean women. Osteoporos Int 21:425–431 13. Park KK, Kim SJ, Moon ES (2010) Association between bone mineral density and metabolic syndrome in postmenopausal Korean women. Gynecol Obstet Invest 69:145–152 14. Carr MC (2003) The emergence of the metabolic syndrome with menopause. J Clin Endocrinol Metab 88:2404–2411 15. Kim HM, Park J, Ryu SY, Kim J (2007) The effect of menopause on the metabolic syndrome among Korean women: the Korean National Health and Nutrition Examination Survey, 2001. Diabetes Care 30:701–706 16. Cho GJ, Lee JH, Park HT, Shin JH, Hong SC, Kim T et al (2008) Postmenopausal status according to years since menopause as an independent risk factor for the metabolic syndrome. Menopause 15:524–529 17. Dorum A, Tonstad S, Liavaag AH, Michelsen TM, Hildrum B, Dahl AA (2008) Bilateral oophorectomy before 50 years of age is significantly associated with the metabolic syndrome and Framingham risk score: a controlled, population-based study (HUNT2). Gynecol Oncol 109:377–383 18. Suzuki T (2011) Exercise for prevention of osteoporosis and other lifestyle-related diseases. Clin Calcium 21:722–729 19. Isleten B, Durmaz B, Durmaz B, Onay H, Ozkinay F, Durmaz A et al (2013) The association of RANK gene C421T and C575T polymorphisms with bone mineral density in postmenopausal Turkish women. Arch Gynecol Obstet 288(4):917–923 20. Cleland SJ, Petrie JR, Small M, Elliott HL, Connell JM (2000) Insulin action is associated with endothelial function in hypertension and type 2 diabetes. Hypertension 35:507–511 21. Diamant M, Lamb HJ, van de Ree MA, Endert EL, Groeneveld Y, Bots ML et al (2005) The association between abdominal visceral fat and carotid stiffness is mediated by circulating inflammatory markers in uncomplicated type 2 diabetes. J Clin Endocrinol Metab 90:1495–1501 22. Kha HT, Basseri B, Shouhed D, Richardson J, Tetradis S, Hahn TJ et al (2004) Oxysterols regulate differentiation of mesenchymal stem cells: pro-bone and anti-fat. J Bone Miner Res 19:830–840
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GYNECOLOGIC ENDOCRINOLOGY AND REPRODUCTIVE MEDICINE
The relationship between bone mineral density and metabolic syndrome in peri- and post-menopausal Thai women Suchada Indhavivadhana1 • Panwad Rattanasrithong1
Received: 23 January 2015 / Accepted: 20 March 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract Purposes To compare the bone mineral density (BMD) measured in the lumbar spine and femoral neck in peri- and post-menopausal Thai women with and without metabolic syndrome, and to determine which contributory factors associated with metabolic syndrome influence BMD. Methods 427 peri- or post-menopausal Thai women were screened against the modified National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) for Asian populations’ criteria for metabolic syndrome. The BMD of those with and without metabolic syndrome was compared, and potential relationships between the factors associated with metabolic syndrome and BMD were sought. Results There was no difference in lumbar spine or femoral neck BMD between the groups (p = 0.605 and 0.415, respectively), but women with central obesity (waist circumference C80 cm, p = 0.004 and [88 cm, p = 0.002), low serum high-density lipoprotein cholesterol (HDL-C) concentration (p = 0.011) and a greater number of contributory factors to metabolic syndrome (p = 0.007) had significantly higher BMD at the femoral neck. Conclusions A diagnosis of metabolic syndrome did not correlate with either lumbar spine or femoral neck BMD. However, higher femoral neck BMD was significantly associated with increased waist circumference, low serum
& Suchada Indhavivadhana [email protected] 1
Gynecologic Endocrinology Unit, Division of Reproductive Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Prannok Rd, Bangkok Noi, Bangkok 10700, Thailand
HDL-C concentration and the number of contributory factors to metabolic syndrome. Keywords Metabolic syndrome Bone mineral density Menopause
Introduction Osteoporosis is characterized by low bone mass, microarchitectural deterioration of bone tissue leading to enhanced bone fragility, and a consequent increase in fracture risk. The prevalence of osteoporotic fracture increases with age. Osteoporosis affects women more than men, as postmenopausal estrogen deficiency is the main contributor to a rapid decline in bone density. As global populations age, osteoporosis is likely to become even greater a clinical problem [1, 2]. Prevention and early intervention in highrisk cases with rapid bone loss are likely the best management strategies. The bone mineral density (BMD) of the spine, hip and femur is measured using dual-energy X-ray absorptiometry-type bone densitometry (DXA). The T score and Z score are calculated with reference to the normal values for an age- and sex-matched population, and the diagnosis of osteoporosis is made according to the World Health Organization (WHO) criteria [3]. Metabolic syndrome comprises a combination of central obesity, dyslipidemia, impaired glucose tolerance and hypertension. Several expert groups have attempted to develop a definition for metabolic syndrome: the most widely accepted are those of the WHO, the European Group for the Study of Insulin Resistance (EGIR), the National Heart, Lung and Blood Institute and American Heart Association criteria (NHLBI/AHA), and the National Cholesterol
123
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Education Program-Third Adult Treatment Panel (NCEP ATP III), with the latter being in widest use [4, 5]. Several studies have demonstrated associations between metabolic syndrome and BMD, but their results have been inconsistent, as shown in Table 1. Most studies enrolled women of a wide variety of ages and none has focused on women in the menopausal or peri-menopausal state. The relationship between BMD and metabolic syndrome in menopausal or peri-menopausal Thai women has not been examined. We sought to compare BMD in the lumbar spine and femoral neck in women in this population with and without metabolic syndrome, and to determine which aspects of metabolic syndrome influence BMD, with the aim of identifying those most at risk of osteoporosis and to inform diagnostic strategy.
Materials and methods The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and its protocol No. 337/2554(EC4) was approved by the Siriraj Institutional Review Board of Mahidol University, Bangkok, Thailand. We enrolled 427 peri- and post-menopausal Thai women undergoing BMD assessments at the Siriraj Menopause Clinic, Mahidol University Hospital, between 2004 and 2012. We recorded participants’ socio-demographic and clinical characteristics, history of comorbid disease (with a particular focus on diabetes mellitus, hypertension and cardiovascular diseases) and family history of comorbid disease, and undertook physical examination and blood tests. The detailed methods of physical examination (including measurement of height, body weight, blood pressure and waist circumference) and laboratory testing used to make the diagnosis of metabolic syndrome were described in our previous report [6]. The peri–postmenopausal women who had inadequate data for diagnosed metabolic syndrome and currently taking hormone therapy or osteoporosis treatment were excluded. Definition of menopausal status [7] Participants were categorized into one of three groups on the basis of their menopausal status (perimenopause, natural menopause or surgical menopause) using the same criteria as our previous report [6, 7]. Criteria for diagnosis of osteoporosis Bone mineral density was measured using DXA (Lunar Prodigy DF?15974), calibrated daily using the standard phantom provided by the manufacturer. The equipment
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was operated by experienced technicians in the Division of Endocrinology and Metabolism, Department of Medicine, Siriraj Hospital. The mean of second to fourth lumbar vertebral (lumbar spine BMD) and femoral neck BMD was recorded. Those with a BMD T score at or below -2.5 were diagnosed with osteoporosis based on the WHO criteria [3]. Criteria for diagnosis of metabolic syndrome We used the NCEP ATP III criteria modified for use in an Asian population to diagnose metabolic syndrome [5]. These require the presence of three of the five following factors: (i) abdominal obesity defined as Asian waist circumference (WC) C80 cm; (ii) elevated blood pressure defined as systolic BP C130 mmHg or diastolic BP C85 mmHg, or previously treated hypertension; (iii) elevated fasting plasma glucose C110 mg/dL, or previously diagnosed type 2 diabetes mellitus; (iv) reduced serum high-density lipoprotein cholesterol (HDL-C) concentration (\50 mg/dL); and (v) elevated serum triglyceride concentration (C150 mg/dL). Statistical analysis Data were analyzed using SPSS software (version 18). Data are presented as mean ± standard deviation (SD) or number (with proportion as a percentage) as appropriate. We undertook univariate analysis to determine whether metabolic syndrome significantly influenced lumbar spine or femoral neck BMD, analysis of variance (ANOVA) for continuous data and the Chi-square test for categorical data. Pearson’s rank-order correlation was used to determine the correlation coefficient (r) between the contributors to metabolic syndrome and BMD. A p value \0.05 was considered statistically significant.
Results Of the 427 women enrolled, 51 (11.9 %) had metabolic syndrome and 23 (5.4 %) had osteoporosis. None of the participants had received hormone treatment. The demographic and clinical characteristics of all subjects according to the presence or absence of metabolic syndrome are shown in Table 2. The mean age of all subjects was 52.6 ± 5.4 years, but the metabolic syndrome group was significantly older (54.7 ± 5.4 years compared with 52.3 ± 5.4 years, respectively; p = 0.004). There were no statistically significant differences in menopausal status, regions of residence, education, parity, lifestyle (for example, exercise, smoking and alcohol drinking habits), the use of calcium supplements and type of diet, or family
Non 706
NCEP ATP III WC C88
MS 60.2 ± 7.4
Non 59.2 ± 6.6
FBS C100
WC [85 Korea
Korea
Korea
Spain
America
America
Country
Similar (adjusted)
Higher
Lower
–
Higher
Similar (adjusted)
Higher
–
Result in lumbar BMD
Similar (adjusted)
Higher
–
Similar Lower
Higher
Similar (adjusted)
Higher
Similar (adjusted BMI)
Higher
Result in femoral neck BMD
HDL was negatively associated with BMD
Central obesity and hypertriglyceride had lower BMD
Triglyceride was negatively associated with BMD
HT and central obesity had higher BMD
Increased numbers of components had lower BMD
FBS was positively associated with BMD
Increased numbers of components and diabetes had higher BMD
Result in MS parameters
BMD bone mineral density, MS metabolic syndrome, WC waist circumference, FBS fasting blood sugar, HT hypertension, NCEP APT III National Cholesterol Education Program Adult Treatment Panel III, NHLBI/AHA National Heart Lung and Blood Institutes/American Heart Association, IDF International Diabetes Federation, ADA American Diabetes Association
Non 325
MS 74
Non 1964
Asia–Pacific and ADA 2003
MS 56.3 ± 9.7
Non 45.3 ± 11.1
Non 917 MS 511
NCEP ATP III
Non 56.6 ± 6.7
FBS C100
MS 191
WC C80
MS 60.7 ± 6.0
21–94
MS 231 Non 877
NHLBI/AHA IDF
MS 60.3 ± 6.4 Non 56.2 ± 6.6
FBS C100
Data are number, or range, or mean ± standard deviation, or percent
Park et al. [13]
Hwang and Choi [12]
Kim et al. [11]
Hernandez et al. [10] WC [88
FBS C110
Non 74.0 ± 0.5
Non 61.8 ± 9.6
Non 549
WC [88
MS 75.9 ± 0.9
MS 307
MS 122
NCEP ATP III
38–97
NCEP ATP III
Female 56 %
FBS C110
Non 44.2 ± 8.7
MS 66.7 ± 9.6
Non 6424
WC [88
MS 56.7 ± 16.7
von Muhlen et al. [9]
MS 1773
NCEP ATP III
[20
Kinjo et al. [8]
Sample size of women
Diagnostic criteria for MS
Age (year)
References
Table 1 Summary of cross-sectional studies surveying women with metabolic syndrome, its components and BMD
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Arch Gynecol Obstet Table 2 Characteristics of peri-/post-menopausal Thai
Characteristics
pa
Metabolic syndrome Non-MS
MS
N
N
Mean ± SD or n (%)
Mean ± SD or n (%)
Age, year
376
52.34 ± 5.36
51
54.66 ± 5.35
0.004
Age at menopause, yearb
283
48.67 ± 4.24
42
48.73 ± 4.9
0.930
Duration since menopause, yearb
283
4.87 ± 4.01
42
6.79 ± 6.05
0.008
Regions of resident, Bangkok
263
70.5
33
66
0.514
Education, lower education level
24
20.2
1
7.7
0.461
Occupation, no
77
21.6
19
37.3
0.013 0.379
Parity Nulliparous
131
35.0
15
28.6
243
65.0
37
71.2
90
23.9
9
17.6
Natural menopause
232
61.7
33
64.7
Surgical menopause
54
14.4
9
Parous Menstrual status Perimenopause
BMI, kg/M2
0.560
376
23.39 ± 3.46
\23.0
190
50.5
23.0–29.9
174
46.3 3.2
51
17.6 26.53 ± 3.27
0.000
5
9.8
0.000
39
76.5
C30.0
12
WC, cm
376
76.02 ± 7.02
51
7
84.84 ± 6.37
13.7
C80.0
118
31.4
46
90.2
0.000
[88.0
30
8.0
14
27.5
0.000
19
5.1
9
17.6
0.003
0.000
Blood pressure, mmHg C130/85 Exercise, yes Cardiovascular exercise
80
81.6
5
71.4
0.616
Regular exercise
81
84.4
6
75.0
0.614
Smoking, yes
2
0.5
2
3.9
0.072
Alcohol drinking, yes
11
2.9
2
3.9
0.660
Calcium, use
48
12.8
3
6.0
0.166
High fiber diet
81
77.9
9
81.8
1.000
High protein diet
30
28.8
5
45.5
0.306
High carbohydrate diet
22
21.2
5
45.5
Diet
Medical disease No
80.8
21
46.7
4
1.1
1
2.2
Hypertension
25
6.7
10
22.2
Dyslipidemia
37
9.9
4
8.9
6
1.6
9
20
231
62.3
31
62.0
42
11.3
7
14.0
Diabetes mellitus
At least two diseases Family History of metabolic disease No Diabetes mellitus
0.614 0.000
303
0.885
Hypertension
24
6.5
4
8.0
Dyslipidemia
37
10.0
3
6.0
At least two diseases
37
10.0
5
10.0
MS metabolic syndrome, BMI body mass index, WC waist circumference
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a
Data are analyzed using one-way ANOVA for continuous data, or Chi-square test for categorical data
b
Age at menopause and duration since menopause are calculated by excluding perimenopause cases
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history of comorbid metabolic disease between the groups. The duration of menopause was significantly longer in women with metabolic syndrome, who were also more likely to be unemployed and have higher body mass index (BMI), WC and blood pressure. Table 3 shows the risk factors for BMD. Lumbar spine BMD had a moderately significantly inverse relationship with age (r = - 0.335, p = 0.000) and duration of menopause (r = - 0.308, p = 0.000). Femoral neck BMD had mildly significantly inverse correlation with age (r = - 0.287, p = 0.000), time since menopause (r = - 0.231, p = 0.000) and serum triglyceride concentration (r = - 0.152, p = 0.000). Both BMI and WC correlated significantly with lumbar spine and femoral neck BMD. The association between metabolic syndrome, its components and BMD is shown in Table 4. Lumbar spine and femoral neck BMD were not significantly different in women with and without metabolic syndrome, even after adjustment for factors known to be associated with BMD (data not shown). None of the components of metabolic syndrome influenced lumbar spine BMD; however, women with central obesity (WC C80 cm, p = 0.004 and WC [88 cm, p = 0.002) and low serum HDL-C concentration (p = 0.011) had a significantly higher femoral neck BMD. Only femoral neck BMD was significantly influenced by the number of components of metabolic syndrome (p = 0.007).
Discussion Among the physiologic changes that occur during transition into menopause, those in reproductive endocrine function might particularly influence the risk of metabolic Table 3 Factors associating with bone mineral density in peri-/post-menopausal Thai
derangement. The incidences of increased WC, hypertension, impaired insulin sensitivity and dyslipidemia are reportedly increased in menopausal women [14, 15]. Consequently, the prevalence of metabolic syndrome increases with age, BMI and menopausal status [16, 17]. Furthermore, the risk of underlying comorbidities such as diabetes mellitus, hypertension and cardiovascular disease is increased [14]. We found that age, duration since menopause, central obesity and comorbidities were important factors. Level of education, exercise, smoking and alcohol intake did not appear to be risk factors for metabolic syndrome in our cohort. We also found that the incidence of osteoporosis was greater in more elderly women and those in the menopausal state. This broadly reflects the current understanding of osteoporosis, a disease of low bone mass and micro-architectural bone defects that increase the risk of bone fracture for which the risk factors include age, weight, low estrogen states, exercise, diet and genetic influences [1, 18, 19]. It is clear that the relationship between metabolic syndrome, its contributory factors and BMD is not yet fully understood. Kinjo and colleagues [8] reported in the Third National Health and Nutrition Examination Survey study that women with metabolic syndrome had higher lumbar BMD, which was consistent with findings in the femoral neck reported by Park and colleagues [13]. We found no statistically significant differences in BMD at either site in Thai women with or without metabolic syndrome. Notably, the menopausal women who participated in previous studies [8, 13] were of a broader age range, and generally had greater WC and BMI than our population. We did, however, find correlations between lumbar spine and femoral neck BMD and BMI, WC and since menopause. Interestingly, other investigators have reported similar
Factors
Lumbar spine BMD
Femoral neck BMD
r
p
r
p
Age (year)
-0.335
0.000
-0.287
0.000
Duration since last menstrual perioda (year)
-0.308
0.000
-0.231
0.000
0.151
0.002
0.293
0.000
-0.067
0.169
-0.028
0.568
Waist circumference (cm)
0.102
0.035
0.229
0.000
Systolic blood pressure (mmHg)
0.028
0.561
0.016
0.745
Diastolic blood pressure (mmHg)
0.080
0.098
0.050
0.307
Fasting blood glucose (mg/dL)
-0.049
0.314
-0.052
0.287
Triglyceride (mg/dL)
-0.048
0.321
-0.152
0.000
0.014
0.770
0.058
0.236
Body mass index (kg/M2) Parity Components of metabolic syndrome
HDL-C (mg/dL)
BMD bone mineral density, HDL-C high-density lipoprotein cholesterol Data were analyzed using Pearson’s rank correlation a
Age at menopause and duration since menopause are calculated by excluding perimenopause cases
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Arch Gynecol Obstet Table 4 Components of metabolic syndrome using modified NCEP ATP III criteria and bone mineral density in peri-/post-menopausal Thai women Factors
Lumbar spine BMD N
Metabolic syndrome
p
Mean ± SD
Femoral neck BMD N
Mean ± SD
51
1.069 ± 0.144
50
0.859 ± 0.123
375
1.057 ± 0.154
376
1.845 ± 0.116
\80 cm
262
1.053 ± 0.148
263
0.833 ± 0.119
C80 cm
164
1.068 ± 0.160
0.337
163
0.867 ± 0.119
0.004
[88 cm
44
1.090 ± 0.488
0.148
44
0.899 ± 0.111
0.002
367
1.054 ± 0.150
59
1.088 ± 0.164
Non-metabolic syndrome
0.605
p
0.415
Components of MS Waist circumference
Blood pressure \130/85 mmHg C130/85 mmHg or HT treatment
0.116
367
0.844 ± 0.119
59
0.862 ± 0.104
0.268
Fasting blood glucose \100 mg/dL
325
1.059 ± 0.151
326
0.849 ± 0.118
C100 mg/dL or DM treatment
98
1.059 ± 0.156
0.987
97
0.842 ± 0.107
0.614
C110 mg/dL or DM treatment
44
1.065 ± 0.173
0.816
43
0.841 ± 0.114
0.736
\150 mg/dL
343
1.060 ± 0.152
344
0.843 ± 0.115
C150 mg/dL
83
1.053 ± 0.155
0.698
82
0.859 ± 0.126
0.283
Triglyceride
HDL-C \50 mg/dL
76
1.089 ± 0.169
0.060
76
0.878 ± 0.127
0.011
\50 mg/dL or DLP treatment
118
1.075 ± 0.165
0.182
118
0.861 ± 0.124
0.120
C50 mg/dL
348
1.052 ± 0.149
348
0.840 ± 0.114
0
176
1.045 ± 0.133
177
0.821 ± 0.112
1
114
1.054 ± 0.161
114
0.865 ± 0.114
2
87
1.082 ± 0.180
87
0.860 ± 0.126
Number of MS criteria
0.491
0.007
3
29
1.067 ± 0.132
28
0.882 ± 0.100
4
17
1.092 ± 0.172
17
0.854 ± 0.129
5
3
1.093 ± 0.029
3
0.898 ± 0.066
Data are analyzed using unpaired t test for continuous data, and Chi-square test (or Fisher’s exact test) for categorical data
results to ours after adjustment for all covariates including age and BMI, making it reasonable to conclude that metabolic syndrome per se does not influence BMD. Many studies have reported that there is a relationship between osteoporosis and central adiposity, which in itself is recognized as causing insulin resistance and chronic inflammation underpinned by mediators such as interleukin-6, tumor necrosis factor-alpha and C-reactive protein [20, 21]. Inflammation and insulin resistance may promote bone reabsorption, reducing bone mass and BMD. It has also been proposed that obesity or high BMI might protect against excessive bone loss in aging by increasing mechanical loading [9, 13]. The complex interaction between these two pathophysiologic phenomena may account for the inconsistent findings of a number of studies [8, 9, 11, 13], including ours. Kim and colleagues’ finding that three of the
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components of metabolic syndrome were negatively associated with femoral neck BMD after multivariate adjustment may reflect the difficulty of separating cardiovascular diseases and metabolic syndrome when the two are so closely linked, and the complexity introduced using different diagnostic criteria for metabolic syndrome [11]. In our cohort, the individual components of metabolic syndrome had no significant influence on lumbar spine BMD, consistent with previous findings [13]. Nonetheless, we identified that femoral neck BMD in our population was influenced by central obesity, low serum HDL-C concentration and the number of components of metabolic syndrome. Women with central obesity, lower HDL-C concentration and additional numbers of metabolic syndrome components might have higher BMD similar to the previous result. It has been proposed that the mechanism
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underpinning the negative correlation between BMD and serum HDL-C concentration might be the relative lack of oxysterols available when serum HDL-C concentration is high, which in turn might reduce the osteogenic differentiation of mesenchymal stem cells [22]. Although our cross-sectional data were acquired retrospectively, the dataset was almost complete as a result of the comprehensive records made of all patients attending our clinic, and there were no missing data concerning metabolic components. Our study had several other limitations. First, serum calcium and phosphate concentrations were not measured, both of which may have influenced BMD. Second, we did not evaluate our subjects’ insulin resistance or inflammatory status, so we are unable to illuminate further the reported relationships between insulin resistance and inflammation [9, 20], or osteoporosis and inflammation [8, 9, 11, 13]. Finally, our subjects were selected solely from patients who visited our urban clinic, which may have resulted in selection bias that makes our findings less generalizable to the wider population of Thai women. In conclusion, we found that metabolic syndrome did not affect BMD in the lumbar spine or femoral neck in menopausal Thai women. However, some of the components of metabolic syndrome, including abdominal obesity, low serum HDL-C concentration and the number of contributory factors to metabolic syndrome were associated with a significantly increased femoral neck BMD. It may be beneficial to postpone BMD evaluation by DXA scan for determining osteoporosis, especially in the femoral neck, in menopausal women with these components of the metabolic syndrome. Acknowledgments The Siriraj Research Development Fund supported this study financially. The authors would like to thank all staff members in the Siriraj Menopause Clinic, and thanks also go to Miss Julaporn Pooliam and the Office for Research and Development for their kind assistance and valuable comments on research methodology. Conflict of interest Both authors are full-time staff members in the Faculty of Medicine, Siriraj Hospital, Mahidol University, which is a government non-profit university hospital; and neither has any conflict of interest to declare.
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