Abstract
Objective
To determine the risk factors of osteoporosis and osteopenia of the spine in postmenopausal women.
Method
An analytical cross-sectional study was performed on postmenopausal women. The T-score of the lumbar spine (L2–L4) was measured by densitometry and compared between osteoporotic, osteopenia, and normal women.
Results
One thousand three hundred fify-nine postmenopausal women were evaluated. The prevalence of osteopenia and osteoporosis was 58.2% and 12.8% respectively. Age, BMI, parity, total breastfeeding years, dairy use, calcium-D supplements, and regular exercise were significantly different in women with osteoporosis, osteopenia, and normal women. Ethnicity, diabetes, and previous fracture history were only other among women with osteoporosis (not osteopenia) and normal women. For osteopenia of the spine, age [AOR 1.08 (1.05–1.11; p < .001)] was the risk factor, and BMI = >30 [AOR 0.36 (0.28–0.58; p < .001)] and BMI 25–<30 [AOR 0.55 (0.34–0.88; p = .012)] were protective factors. Hyperthyroidism (AOR 23.43, p = .010), Kurdish ethnicity (AOR 2.96, p = .009), not having regular exercise (AOR 2.22, p = .012), previous fracture history (AOR 2.15, p = .041)], and age (AOR 1.14, p < .001)], were risk factors for osteoporosis, while BMI ≥30 [AOR 0.09, p < .001], BMI 25–<30 [AOR 0.28, p = .001], and diabetes [AOR 0.41, p = .038] were protective factors for osteoporosis of the spine.
Conclusion
Hyperthyroidism, low BMI <25, parity ≥ 6, Kurdish ethnicity, not having regular exercise, history of previous fracture, and age, were risk factors for osteoporosis of the spine respectively, while low BMI and age were risk factors for osteopenia.
Introduction
Osteoporosis is one of the most common age-associated and metabolic bone diseases, which causes low bone mass, bone tissue destruction, bone fractures, disability, mortality, and medical costs [Citation1–3]. It usually does not have any symptoms until fractures occur; therefore, a few people are diagnosed and treated at the right time [Citation4]. Osteoporosis is four times more common in women than men [Citation5], and globally every 30 min one person suffers from a bone fracture due to osteoporosis [Citation6]. Worldwide, osteoporosis is a major public health problem, especially in low- and middle-income countries [Citation6]. Women, particularly older ones, are the most vulnerable to osteoporosis because of low estrogen levels after menopause, which consequently accelerates bone loss [Citation3,Citation7,Citation8]. According to an estimation by International Osteoporosis Foundation (IOF), 1 in 3 women over the age of 50 will suffer osteoporotic fractures [Citation9,Citation10]. The prevalence of osteoporosis in women is reported to be around 15.8% in Canada, and 17% to 20% in the United States in different parts [Citation11,Citation12]. The Iranian Multicenter Osteoporosis Study (IMOS) showed that 18.7% of women over the age of 50 had osteoporosis in the lumbar region. IMOS also reported that the maximum bone mineral density (BMD) of Iranian women’s lumbar spine occurred at the age of 29–30 [Citation13–16]. With an increasing life expectancy, the number of women with osteoporosis will be increased in the future, which will cause further financial burdens in addition to morbidity and mortality. Therefore, understanding and preventing the risk factors in Iranian postmenopausal women is a major concern. The aim of the present study was to determine the risk factors of osteoporosis and osteopenia of the spine in postmenopausal women in Tehran, Iran.
Material and method
An analytical cross-sectional study was performed at Akbarabadi Training Hospital in Tehran, Iran between 2015 and 2017. During this time, 14,630 women visited the hospital’s clinic for routine checkups, from whom, all women who were above 45 years of age were invited to participate in the study, and 1359 consented to participate in the study. The inclusion criteria were postmenopausal women who were older than 45 years. Exclusion criteria were smoking and alcohol consumption, if women had oophorectomy before the age of 45, if the women had any bone problems including arthritis, bone metabolism dysfunction, bone metastases, parathyroid diseases, and history of using medications such as estrogen therapy. Menopause was defined as the permanent cessation of menstruation for at least one year after the age of 45, without, any other responsible factors such as hysterectomy.
Baseline data and demographic characteristics of the women including age, BMI, parity, ethnicity, total duration of breastfeeding, age at menarche, vitamin D and calcium supplement use, dairy use (Dairy consumption per day), and history of fracture (included all anatomical sites of the previous fracture according to the patient’s statement), exercise and weekly activities, use of any medications, and a history of any systemic disorders were recorded. Regular exercise was defined as an exercise for a duration of at least 30 min, 3 or 4 times a week [Citation17]. Using 2 cups equivalents of dairy products (including milk, yogurt, and cheese) per day or more was considered moderate to high and 1 cup equivalents of dairy products or less was considered low [Citation18]. All diabetic women received oral antidiabetic treatment for their diabetes. All women with hypothyroidism and hyperthyroidism were under treatment for their condition. For all women included in the study, bone densitometry was performed, using a NORLAND-XR600 dual-energy X-ray absorptiometry (DXA) device. The same equipment and the same person performed the DXA for all women. The coefficient of variation of the DXA equipment (CV) was 0.4% for the lumbar spine. Bone mass density and peak bone mass density were evaluated for the lumbar spine at L2–L4. T-score (comparison of the patient’s bone density with healthy, young individuals of the same sex) was calculated in the lumbar spine (L2–L4) for all participants. The DEXA scan report was considered based on the World Health Organization criteria for osteoporosis and Osteopenia. A negative T-score of –2.5 or less was defined as osteoporosis and a T-score between –1 and –2.5 was defined as osteopenia (low bone mass).
Convenience sampling was used to recruit for this study, hence the number or characteristics of the included women are not representative of the national population.
Data were analyzed using SPSS version 19. The normality of continuous variables was checked. Quantitative data distribution was checked through histogram, Skewness, and kurtosis. Continued data were compared with ANOVA and followed by the Scheffé test as post hoc multiple comparisons as needed. The categorical variables were compared with the chi-squared test. A binary logistic regression model was performed to detect predictors of osteopenia and osteoporosis. In the multivariate analysis using a logistic regression model with the entering method, independent predictors were assessed. The model included the variables related to osteopenia or osteoporosis in a univariate regression model with the PV = <0.1, and the adjusted odds ratios and corresponding confidence intervals were calculated. The significant level was set at α = 0.05.
Results
One thousand three-hundred fifty-nine postmenopausal women were evaluated. According to L2–L4 BMD T score, the prevalence of osteopenia and osteoporosis were 58.2% (95% CI: 55.6–60.8) and 12.8% (95% CI: 11.1–14.7) respectively. Demographic and clinical characteristics of the study women are shown in . and demonstrate the relationship between demographic, clinical, and some lifestyle factors with osteopenia or osteoporosis. Higher age, high parity (parity ≥ 6), lower BMI, low dairy use, no calcium-D supplements, no regular exercise, and Kurd ethnicity were found to be the risk factors for osteopenia and osteoporosis ( and ).
Table 1. Demographic and clinical characteristics of the study women.
Table 2. Risk factors for osteopenia or osteoporosis in postmenopausal women of the study.
Table 3. The relation of clinical factors with osteopenia or osteoporosis.
The mean menarche age was not different between the normal, osteopenic, and osteoporosis groups (). The highest rate of osteoporosis was seen in women with total breastfeeding years of 10 or more. Diabetic women were less prone to osteoporosis. The women with a history of fractures were more prone to becoming osteoporotic than women without a similar history ().
In the univariate logistic regression analysis ( and ), age, BMI, dairy use, calcium-D supplement intake, regular exercise, and parity were significant predictors of osteopenia (p < .05). A one-year increase in age was accompanied by an 8% increased chance of osteopenia. Considering the BMI of less than 25 as the reference group, the chance of osteopenia decreased by about 60% when BMI increased from 30 (OR = 0.39; 95% CI: 0.26–0.59, p = .009). The chance of osteopenia in the women with low dairy consumption was about 1.5 times higher than in the women with medium–high dairy consumption. Women who did not take calcium-D supplements were around 1.5 times more likely to develop osteopenia. Similarly, a lack of regular exercise increases the chance of osteopenia (OR = 1.41, 95% CI: 1.09–1.81). The women with a parity of ≥6 were 2.1 times more likely to develop osteopenia than women with a parity of 0 to 2. (95% CI: 1.39–3.16, p < .001). In multivariate regression analysis, age and BMI were the only significant predictors of osteopenia (p < .001) ( and ).
Table 4. The crude and adjusted odds ratio of different categories of age and BMI for osteopenia and osteoporosis.
Table 5. The crude and adjusted odds ratio of predicting factors of osteopenia and osteoporosis.
The significant predictors of osteoporosis in the univariate logistic regression analysis ( and ), were higher age, lower BMI, parity, total breastfeeding years of more than 10 years, Kurd ethnicity, low dairy use, lack of Calcium-D supplement intake, lack of regular exercise, previous fracture, and diabetes. Considering a parity of 0–2 as the reference group, women with a parity of 6 or more were approximately 3.7 times more likely to develop osteoporosis. Women with more than 10 years of breastfeeding were 2.4 times more likely to develop osteoporosis. Diabetes was a protective factor for osteoporosis in this study. Hyperthyroidism was a risk factor for osteoporosis, although this relationship was not significant at the defined level. Multivariate analysis using a logistic regression model included the variables related to osteoporosis in a univariate regression model with the PV = <0.1. Therefore, hyperthyroidism was included in the logistic regression model.
Multivariate regression analysis showed that age, BMI, Kurdish ethnicity, lack of regular exercise, parity, diabetes, hyperthyroidism, and previous fracture were significant independent predictors for osteoporosis of the spine (p < .05) ().
Discussion
In the present study, according to L2–L4 T score, the prevalence of osteopenia and osteoporosis of the spine in postmenopausal women were 58.2% and 12.8% respectively. Hyperthyroidism, low BMI (<25), high parity (≥6), Kurdish ethnicity, not having regular exercise, previous fracture, and aging, were significant independent predictors for osteoporosis in postmenopausal women respectively, however, low BMI (<25) and aging were the sole risk factors for osteopenia.
The results of a study conducted by Jamshidian et al. on Iranian women aged 40–60 years, showed that the prevalence of osteoporosis in the lumbar spine was 15.8% [Citation19]. However, a meta-analysis in 2013 reported the prevalence of osteoporosis based on lumbar T score in postmenopausal women was around 19% [Citation20]. Ethnicity, lifestyle, and diet have influence on the prevalence of osteoporosis in postmenopausal women [Citation10,Citation21–25]. According to the studies conducted worldwide, the prevalence of osteoporosis among different ethnicities is different [Citation10,Citation24–26]. Several studies done in the world have found a significant inverse relationship between age and BMD [Citation3,Citation6,Citation10,Citation26,Citation27]. One-third of a woman’s life is spent after menopause. Therefore, prevention of osteoporosis is important issue. Regarding the high prevalence of osteoporosis during postmenopausal period and its impact on women’s morbidity and mortality due to fractures and its high financial burden, it is important to identify its risk factors in different ethnicities to prevent the preventable risk factors by education and making changes in lifestyle.
The lower number of osteoporosis in the present study in comparison with the aforementioned studies might be due to more education about using calcium-D supplements and exercise.
The reasons for low prevalence of osteoporosis in this study compared to the ones conducted in Iran and the world may be the methods of measuring and diagnosing the disease, the sample size, and different methods of data collection.
In the present study, it was found that the one-year increase in age would lead to 14% increase in the risk of osteoporosis and 8% increase in the risk of osteopenia in postmenopausal women. Hence, as the age increased, the risk of osteoporosis in different parts of body increased as well. A probable decrease in the number of vitamin D receptors in kidneys, reduced calcium absorption efficiency, and reduced estrogen levels with age can be the reasons for low bone mass in older adults, which might increase the risk of osteoporosis [Citation25–27]. On the other hand, the results of this study showed that the women who were at the age of menopause were four times more likely to have osteoporosis than those who were not.
The results of the studies by Huda et al. and Finkelstein et al. showed that menopause was a risk factor for osteoporosis [Citation21,Citation28]. The reason could be attributed to estrogen loss in women at menopause. In addition, in this study, one unit increase in the BMI could decrease the chance of osteoporosis in the lumbar spine 20%. Increased BMI is associated with endocrine changes, which can have positive effects on bones [Citation29,Citation30]. On the other hand, weight loss is associated with early menopause, which is in turn associated with low bone mass [Citation31]. This was proved in the present study. A study conducted by Omidvar et al. indicated that high age, low BMI, low vitamin D level, low calcium intake, and low heparin level were the risk factors for osteoporosis [Citation32]. The results of this study also showed that, any increase in the number of gravidity could double the chance of trochanter osteoporosis in women. The results of the study by Huda et al. showed that early menstruation, low parity, high BMI, and long gestational age were associated with high BMD and that was consistent with the results of the present study [Citation21]. The lower prevalence of osteoporosis in diabetic women in the present study contrasts with the other studies, however, it might be due to better monitoring and on-time interventions for using calcium-D supplements and exercise. A limitation of the present study is reporting DXA only in the T score of the L2–L4 lumbar spine; therefore, it cannot generalize to all cases of osteoporosis and osteopenia.
Regarding osteoporosis and its risk factors, many studies have been conducted and analyzed in the world so far and the relationship between osteoporosis in women and demographic and other factors has been measured, but the results have been shown to be contradictory. Generally, a specific factor cannot be considered as a risk factor for osteoporosis, since all the risk factors for this disease may interact with each other.
Strengths and limitations of the study
A limitation of the present study is reporting DXA only in the T score of the L2–L4 lumbar spine; therefore, it cannot generalize to all cases of osteoporosis and osteopenia.
Conclusion
This study showed that hyperthyroidism, low BMI <25, parity ≥ 6, Kurdish ethnicity, not having regular exercise, history of previous fracture, and age, were risk factors for osteoporosis of the spine respectively. Hence, the results of this study could help to reduce the burden of the disease and its high costs by screening young women for early detection of osteoporosis risk factors. On the other hand, the results of this study might provide proper information for young women to prevent the risk factors of osteoporosis and the occurrence of the disease.
Disclosure statement
None.
Additional information
Funding
References
- Center JR. Fracture burden: what two and a half decades of Dubbo Osteoporosis Epidemiology Study data reveal about clinical outcomes of osteoporosis. Curr Osteoporos Rep. 2017;15(2):1–6.
- Pasco JA, Mohebbi M, Holloway KL, et al. Musculoskeletal decline and mortality: prospective data from the Geelong Osteoporosis Study. J Cachexia Sarcopenia Muscle. 2017;8(3):482–489.
- Iki M, Fujita Y, Tamaki J, et al. Incident fracture associated with increased risk of mortality even after adjusting for frailty status in elderly Japanese men: the Fujiwara-Kyo osteoporosis risk in men (FORMEN) cohort study. Osteoporos Int. 2017;28(3):871–880.
- Sing C, Cheung C. Early anti-osteoporosis treatment and risk of mortality after hip fracture: a population based study. Paper presented at: WCO-IOF-ESCEO Florence 2107, 2017 March 23–26, Florence, Italy.
- Bonjour J-P, Chevalley T, Ferrari S, et al. The importance and relevance of peak bone mass in the prevalence of osteoporosis. Salud Publica de Mexico. 2009;51:s5–s17.
- Berger C, Goltzman D, Langsetmo L, et al. Peak bone mass from longitudinal data: implications for the prevalence, pathophysiology, and diagnosis of osteoporosis. J Bone Miner Res. 2010;25(9):1948–1957.
- Dontas I, Yiannakopoulos C. Risk factors and prevention of osteoporosis-related fractures. J Musculoskelet Neuronal Interact. 2007;7(3):268–272.
- Maalouf G, Gannagé-Yared M, Ezzedine J, et al. Middle east and North Africa consensus on osteoporosis. J Musculoskelet Neuronal Interact. 2007;7(2):131.
- Keramat A, Patwardhan B, Larijani B, et al. The assessment of osteoporosis risk factors in Iranian women compared with Indian women. BMC Musculoskelet Disord. 2008;9(1):28.
- Salari P, Rezaie A, Larijani B, et al. A systematic review of the impact of n – 3 fatty acids in bone health and osteoporosis. Med Sci Monit. 2008;14(3):RA37–RA44.
- Hollowell JG, Staehling NW, Flanders WD, et al. Serum TSH, T4, and thyroid antibodies in the United States population (1988 to 1994): national health and nutrition examination survey (NHANES III). J Clin Endocrinol Metab. 2002;87(2):489–499.
- Dawson-Hughes B, Tosteson A, Melton L, et al. Implications of absolute fracture risk assessment for osteoporosis practice guidelines in the USA. Osteoporos Int. 2008;19(4):449–458.
- Lindsay R, Silverman SL, Cooper C, et al. Risk of new vertebral fracture in the year following a fracture. JAMA. 2001;285(3):320–323.
- Larijani B, Moayyeri A, Keshtkar AA, et al. Peak bone mass of Iranian population: the Iranian multicenter osteoporosis study. J Clin Densitom. 2006;9(3):367–374.
- Rahnavard Z, Zolfaghari M, Hossein-Nezad A, et al. The incidence of osteoporotic hip fracture: Iranian multicenter osteoporosis study (IMOS). Res J Biol Sci. 2009;4(2):171–173.
- Meybodi HA, Heshmat R, Maasoumi Z, et al. Iranian osteoporosis research network: background, mission and its role in osteoporosis management. Iranian J Public Health. 2008;37(Suppl):1–6.
- American Heart Association Recommendations for Physical Activity in Adults and Kids. Physical Activity Guidelines for Americans (Second Edition). Available from: https://www.heart.org/en/healthy-living/fitness/fitness-basics/aha-recs-for-physical-activity-in-adults.
- Dietary Guidelines for Americans. Dietary Guidelines for Americans 2015-2020 (Eight Edition), Page 23—2015-2020. Available from: https://health.gov/sites/default/files/2019-09/2015- 2020 _Dietary_Guidelines.pdf.
- Jamshidian Tehrani M, Kalantari N, Azadbakht L, et al. The prevalence of osteoporosis among women aged 40-60 in Tehran. Iran J Endocrinol Metab. 2003;5:271–276.
- Hirota T, Nara M, Ohguri M, et al. Effect of diet and lifestyle on bone mass in Asian young women. Am J Clin Nutr. 1992;55(6):1168–1173.
- Huda W, Morin R. Patient doses in bone mineral densitometry. Br J Radiol. 1996;69(821):422–425.
- Smeets-Goevaers C, Lesusink G, Papapoulos S, et al. The prevalence of low bone mineral density in Dutch perimenopausal women: the Eindhoven perimenopausal osteoporosis study. Osteoporos Int. 1998;8(5):404–409.
- Ballard P, Purdie D, Langton C, et al. Prevalence of osteoporosis and related risk factors in UK women in the seventh decade: osteoporosis case finding by clinical referral criteria or predictive model? Osteoporos Int. 1998;8(6):535–539.
- Burger H, De Laet C, Van Daele P, et al. Risk factors for increased bone loss in an elderly population the Rotterdam study. Am J Epidemiol. 1998;147(9):871–879.
- Raehtz S, Bierhalter H, Schoenherr D, et al. Estrogen deficiency exacerbates type 1 diabetes-induced bone TNF-α expression and osteoporosis in female mice. Endocrinology. 2017;158(7):2086–2101.
- Riggs BL, Khosla S, Melton LJ. A unitary model for involutional osteoporosis: estrogen deficiency causes both type I and type II osteoporosis in postmenopausal women and contributes to bone loss in aging men. J Bone Miner Res. 1998;13(5):763–73.
- Southmayd E, Mallinson R, Williams N, et al. Unique effects of energy versus estrogen deficiency on multiple components of bone strength in exercising women. Osteoporos Int. 2017;28(4):1365–1376.
- Finkelstein JS, Brockwell SE, Mehta V, et al. Bone mineral density changes during the menopause transition in a multiethnic cohort of women. J Clin Endocrinol Metab. 2008;93(3):861–868.
- Ong T, Sahota O, Tan W, et al. A United Kingdom perspective on the relationship between body mass index (BMI) and bone health: a cross sectional analysis of data from the Nottingham fracture liaison service. Bone. 2014;59:207–210.
- Van der Voort D, Geusens P, Dinant G. Risk factors for osteoporosis related to their outcome: fractures. Osteoporos Int. 2001;12(8):630–638.
- Nguyen T, Sambrook P, Eisman J. Bone loss, physical activity, and weight change in elderly women: the Dubbo Osteoporosis Epidemiology Study. J Bone Miner Res. 1998;13(9):1458–1467.
- Omidvar N, Neyestani T-R, Hajifaraji M, et al. Calcium intake, major dietary sources and bone health indicators in Iranian primary school children. Iran J Pediatr. 2015;25(1):e177.