1. Abstract Purpose: Osteoporosis is a systemic skeletal disease and strongly associated with reduced quality of life (QoL). The aimof the study was to explore BMD that might serve as index of health-related QoL (HRQoL), or the relationship between bone mineral density (BMD) and HRQoL in postmenopausal Han Chi-nese women prior to diagnosis of osteoporosis. Methods: QUALEFFO-41 and an optimism questionnaire (LOT-r) were used to survey the enrolled patients. The relation- ships between HRQoL and FN BMD were analyzed using separatehierarchical multiple regression analysis. Results: In the hierarchical multiple regression analysis, for those without fracture: at Step 1, age, BMI and optimism account-ed for 58.6% of the variance in HRQoL total scores (Fch (3, 153 )=70.75, p < 0.05). At Step 2, the addition of FN BMD explained 5.8% of the variance over and above the age, BMI, and optimism (Fch (4, 153) = 67.30, p < 0.05). FN BMD accounted for significant variance in HRQoL total scores (p = 0.000). In those with fracture: the number of fractures was added to the analysis as a variance. A lower FN BMD was not associated with a compromised HRQoL total score (p = 0.555). Younger age, increased BMI, and decreased optimism negatively correlated with HRQoL
Keywords: Postmenopausal osteoporosis; Health-related quality of life; Bone mineral density; Fracture
2. Introduction Osteoporosis is a systemic skeletal disease characterized by reduced bone mass and micro-architectural abnormality, with a con-sequent increase in bone fragility and high susceptibility to frac- ture, particularly in the vertebral body, distal forearm, and proxi- mal femur of postmenopausal women [1]. It is estimated that the prevalence of osteoporosis rises from one-third in people aged 50-60 years to more than 50% in people aged over 80 years. By 2050, the global number of people with osteoporosis will reach 6 million (including both males and females), three quarters of them will reside in developing countries [2,3]. With the average life span extended to 70 years, most women will spend about one-third of their lifetimes beyond the menopausal age. Besides, the proportion of postmenopausal women is rising since the aging population is expanding rapidly. Thus, the health of menopausal women will become a prime concern worldwide [4]. During the menopausal transition period, women will experience a number of bothersome symptoms. In addition to hot flushes, headaches, sweating, fatigue, sexual dysfunction, and reduced estrogen, osteoporosis is the most prevalent disease in menopausal women, and is strongly associated with low quality of life(QoL [4]. The prevalence of osteoporosis and related fractures is higher in postmenopausal women than in men of comparable age since estrogen plays a key role in maintaining bone health. The National Osteoporosis Foundation (NOF) estimates that there are 9.1 million women with osteoporosis and an additional 26 million with reduced bone mass. This far exceeds the estimated number of same age men with osteoporosis and reduced bone mass (2.8 million and 14.4 million, respectively) [5]. In a meta-analysis evaluating the data on the epidemiology of Chinese people over 40-year age, the author found that the total prevalence of osteoporosis at an age above 40 years in China was 13.2%, and it is significantly higher among females than males: 14.2% vs. 11.8% respectively (P < 0.05). The prevalence of osteoporosis increases in both men and women with age, it increases more significantly in females over 50.
3. Methods Subjects The protocol of this study was approved by the Medical Ethics Committee of Xi’an Jiaotong University. All participants have completed written informed consent forms. All subjects enrolled in this cross-sectional study were randomly selected from clinic lists in the Second Affiliated Hospital of Xi’an Jiaotong University between January 2015 and December 2019. Patients were included in the data analysis if they were female, postmenopausal, over 45 years of age, had not undergone a previous dual energy X-ray absorptiometry (DXA) examination, and did not have a prior diagnosis of osteoporosis. Patients were excluded if they were receiving treatment for osteoporosis; had conditions or medications known to affect BMD such as hyperparathyroidism, renal disease or malabsorption; had suffered a stroke or a myocardial infarction in the previous year; or had a history of cancer [21]. Measurement of bone mineral density and anthropometric baseline data DXA (Lunar Expert 1313, Lunar Corp., USA) was used to assess BMD at the femur neck. BMD was expressed in g/cm2 and as peak bone mass percentage in normal subjects (T-score) depending on the software used in the device. The patients were classified into 3 groups on the basis of the BMD results of the femur neck according to World Health Organization criteria: normal (T score < -1.0 SD), osteopenia (T score -1.0 to -2.5 SD), and osteoporosis.
QoLAssessment The Questionnaire of the European Foundation for Osteoporosis (QUALEFFO) is a well-known instrument to assess functionality and QoL in this population. Different versions of the tool exist: the first one had 48 items but was shortened to 41 items (QUALEFFO-41) [22]. The Quality of Life Questionnaire of the European Foundation for Osteoporosis 41 (QUALEFFO-41) was developed for the purpose of evaluating patients with osteoporotic vertebral fractures. It is a self-administered, disease-specific tool and contains 41 items divided into several subscales: pain (5 items), physical function (17 items), social function (7 items), general health perception (3 items), and mental function (9 items). Most of the items have five response options (scores range from 0 to 4 points). Exceptions are items 27, 28, and 29 with four responses (score ranges from 0 to 3 points) and items 23, 24, 25, and 26 with 3 response options (scores range from 0 to 2 points) [23]. Domain scores were calculated by summing the answer scores and submitting the sum to a linear transformation to a 100 scale, where 0 represents the best and 100 the worst QoL [24]. Optimistic Assessment Optimism was assessed by the Chinese version of the Life Orientation Test-Revised (LOT-R) [25,26]. The LOT-R consists of 10 questions with a 6-item measure and 4 filler items assessing individual differences in generalized optimism versus pessimism. The total score ranges from 0 to 24 with high scores indicating higher levels of optimism. For indicative purposes, we analyzed optimism using cutoff values as follows: 0–13 indicates low optimism, 14–18 moderate optimism and 19–24 high optimism. Subscales of optimism and pessimism are useful both when compared against one another and combined for practical use in a clinical setting [27]. Statistical Analysis Differences in patient characteristics between the six groups were assessed using one-way analysis of variance (ANOVA). Excluding the effects of confounding factors such as age, BMI, number of fractures, and optimism, relationships between HRQoL and FN BMD were analyzed using separate hierarchical multiple regression analysis. P< 0.05 was considered to indicate a statistically significant difference. Data analysis was performed using SPSS Version 15.0 (IBM, Chicago, USA).
4. Results Participants 217 postmenopausal women were divided into those who had with or without a history of fracture,and were also stratified according to World Health Organization criteria: normal (T score < -1.0 SD), osteopenia (T score -1.0 to -2.5 SD), and osteoporosis (T score < -2.5 SD),genernating six groups (Table 1). The results of oneway ANOVA showed that there were significant differences in all variables among the six groups. In contrast with osteopenia and normal FN BMD, patients with osteoporosis were older, had lower BMI, and lower optimism. There were significant differences in the number of fractures among the three FN BMD groups. Patients with osteoporosis had a higher number of fractures compared with those with osteopenia and normal FN BMD.
QUALEFFO-41 Scores Table 2 shows the subdomain scores of QUALEFFO-41 in postmenopausal women undergoing BMD assessments (DXA) of patients in the six groups. The most significant negatively correlated factors or subdomains in this study were mental function (51.72±24.66), pain (51.61±27.49), and general health perception (50.61±21.44). When we compared the QUALEFFO-41 scores after stratifying the groups according to fracture status and FN BMD T scores. A significant difference was found for all domains at p < 0.001 (Table 3).
The Relationship between HRQoL and FN BMD Hierarchical multiple regression analysis was performed to evaluate the variance in HRQoL scores for those without a history of fracture could be explained by FN BMD after controlling for confounding variables (Table 4). In those without fracture, age, BMI, and optimism were entered in Step 1, followed by FN BMD. At Step 1, age, BMI and optimism accounted for 58.6% of the variance in HRQoL total scores (Fch (3, 153) = 70.75, p < 0.05). At Step 2, the addition of FN BMD added extra 5.8% of the variance over and above age, BMI, and optimism (Fch (4, 153) = 67.30, p < 0.05). FN BMD accounted for a significant variance in HRQoL total scores (p = 0.000). In those with fracture, the number of fractures were added to the statistical model, and the relationship between FN BMD and HRQoL total score did not reach statistical significance (p = 0.555). Younger age, higher BMI, and lower optimism negatively affected the levels of HRQoL in those with or without fracture (a lower score indicates a better HRQoL).
5. Discussion In this study population, the classification of postmenopausal women attending for BMD assessments (DXA) showed significant differences among the six groups with respect to all domains of the QUALEFFO-41. Compared with osteopenia and normal FN BMD, postmenopausal women with osteoporosis showed impairments in all domains of the specific QUALEFFO-41 instrument; scoring particularly low in the mental function (51.72 ± 24.66), pain (51.61 ± 27.49), and general health perception (50.61 ± 21.44) domains. These results are similar to those of other studies using the same questionnaire and also show a worse QoL in virtually all domains evaluated, with scores predominantly more related to the clinical aspects of the diseases [28,29]. The present study is one of few studies that has investigated the relationship between FN BMD and HRQoL in those with and without bone fracture before a diagnosis of osteoporosis after controlling confounding variables. In osteoporosis, low BMD is asymptomatic and patients with or without low-grade fractures may be unaware of their conditions. By contrast, a reduced BMD may sometimes cause a decrease in QoL owing to the fear of potential new fractures [29]. It is possible that increased pain present in patients with osteoporosis even before a true fracture occurs; which is reflected in the worse bodily pain scores. This pain could be due to micro-architectural failure of the bone, which might be associated with the low BMD [30]. It is interesting to note that Dennison et al. [31] found a relationship between HRQoL and FN BMD in men but not women after controlling for other variables, such as age, social class, BMI, and co-morbidities. This is the first study to control age, BMI, and optimism during the scoring for the QUALEFFO-41 in postmenopausal Han Chinese women undergoing FN BMD assessment prior to the diagnosis of osteoporosis. After controlling for these confounding variables, we found that HRQoL is associated with FN BMD in Han Chinese women with or without previous fractures before a diagnosis of osteoporosis. Moreover, the relationship between FN BMD and HRQoL was more evident in those without a previous fracture, suggesting that it is not always the clinical fracture itself or the impact of diagnosis of osteoporosis determining this relationship. In the present study, we found that younger age negatively affected HRQoL scores in those with or without fracture. The reasons for such influence in HRQoL by relatively younger age are still unclear. Such inverse correlation between age and HRQoL was consistent with previous studies [32-35]. They are consistent with existing literature, where in frailty patients, advancing age is associated with better HRQoL [36] and the reasons for this could be that older patients have reduced life quality expectations [37]. This may indicate that because older men start with lower baseline QOL scores, they have lower recovery expectations from their diseases, or that older patients have developed strong resilience to QOL fluctuations over time [38]. In our study, increasing BMI negatively affected HRQoL in those with or without fractures. Table 1 shows that the majority of postmenopausal patients were overweight or obese. Greater morbidity and adverse effects on HRQoL might be expected in obese individuals with fracture than in non-obese people because of a greater prevalence of comorbidities, higher risk of fracture, more post-operative complications, and slower rehabilitation [39-41]. Compston et al. reported obese women with fracture undergoing a prolonged period of hospitalization for treatment with a poor recovery of functional status and worse HRQL compared with that in non-obese women. Therefore, higher BMI might be related to higher osteoporosis risk.
References 1. Richard E. Osteoporosis. Medicine. 2013; 41(10): 586-591.
2. Cooper C, Cole Z A, Holroyd C R, Earl S C, Harvey NC, Dennison EM, et al. Secular trends in the incidence of hip and other osteoporotic fractures. Osteoporos Int. 2011; 22(5): 1277-1288.
3. Cauley JA. Public health impact of osteoporosis. J Gerontol A Biol Sci Med Sci. 2013; 68(10): 1243-1251.
4. Ji MX, Yu Q. Primary osteoporosis in postmenopausal women. Chronic Diseases and Translational Medicine. 2015; 1(1): 9-13.
5. Nguyen ND, Ahlborg HG, Center JR, Eisman JA, Nguyen TV. Residual lifetime risk of fractures in women and men. J Bone Miner Res. 2007; 22(6): 781-788.
6. Ya-jun Han, X jT, Tuoheti Yilihamu. Meta-analysis on the prevalence rate of osteoporosis in the middle-aged and elderly in China. Chin J Tissue Eng Res. 2014; 18(7): 1129-1134.
7. Orgainzation WH. Guidelines for preclinical evaluation and clinical trials in osteoporosis. Geneva. 1998.
8. Cummings SR, Melton LJ. Epidemiology and outcomes of osteoporotic fractures. Lancet. 2002; 359(9319): 1761-1767.
9. Foundation NO. Clinician’s guide to the prevention and treatment of osteoporosis. Washington DC: National Osteoporosis Foundation. 2013.
10. Downey PA, Perry SB, Anderson JM. Screening postmenopausal women for fall and fracture prevention. J Geriatr Phys Ther. 2013; 36(3): 138-145.
11. Lasaite L, Krasauskiene A. Psychological state, quality of life, and body composition in postmenopausal women with osteoporosis in Lithuania. Arch Osteoporos. 2009; 4(1-2): 85-90.
12. Andreoli A, Bazzocchi A, Celi M, Lauro D, Sorge R, Tarantino U, et al. Relationship between body composition, body mass index and bone mineral density in a large population of normal, osteopenic and osteoporotic women. Radiol Med. 2011; 116(7): 1115-1123.
13. Guyatt GH, Feeny DH, Patrick DL. Measuring health-related quality of life. Ann Intern Med. 1993; 118(8): 622-629.
14. Prevention and management of osteoporosis. World Health Organ Tech Rep Ser. 2003; 921: 1-164.
15. Scheier MF, Carver CS. Effects of Optimism on Psychological and Physical Well-Being - Theoretical Overview and Empirical Update. Cognitive Therapy and Research. 1992; 16(2): 201-228.
16. Scheier MF, CC. Self-regulatory processes and responses to health threats: effects of optimism on well-being. In: Suls J, Wallston KA, editors. Social Psychological Foundations of Health and Illness. Malden, MA, USA:Blackwell Publishing Ltd, p. 2003; 395-428.
17. Conversano C, Rotondo A, Lensi E, Della Vista O, Arpone F, Reda MA. Optimism and its impact on mental and physical well-being. Clin Pract Epidemiol Ment Health. 2010; 6: 25-29.
18. Wallace LS, Ballard JE, Holiday DB, Wells HE. Comparison between 60 matched pairs of postmenopausal black and white women: analysis of risk factors related to bone mineral density. Maturitas. 2005; 52(3-4): 356-363.
19.AC Looker, E S Orwoll, C C Johnston Jr, R LLindsay, H WWahner, W L Dunn, M S Calvo. Prevalence of low femoral bone density in older U.S. adults from NHANES III. J Bone Miner Res. 1997; 12(11): 1761-1768.
20. Looker AC, Melton LJ, Harris TB, Borrud LG, Shepherd JA. Prevalence and Trends in Low Femur Bone Density Among Older US Adults: NHANES 2005-2006 Compared with NHANES III. Journal of Bone and Mineral Research. 2010; 25(1): 64-71.
21. Wilson S, Sharp CA, Davie M. Health-related quality of life in women referred for bone density assessment: relationships with bone mineral density, fracture and co-morbidity. Quality of Life Research. 2015; 24(5): 1235-1243.
22. Caulin F, Lips P, Cooper C, Agnusdei D, Egger, P Johnell, et al. Quality of life as outcome in the treatment of osteoporosis: The development of a questionnaire for quality of life by the European Foundation for Osteoporosis (QUALEFFO). Quality of Life Research. 1997; 6(7-8): 58-58.
23. Azimi P, Shahzadi S, Azhari S, Montazeri A. An outcome measure of functionality and quality of life in Iranian women with osteoporotic vertebral fractures: a validation study of the QUALEFFO-41. Journal of Orthopaedic Science. 2014; 19(6): 860-867.
24. Lips P, Cooper C, Agnusdei D, Caulin F, Egger P, Johnell O, et al. Quality of life in patients with vertebral fractures: Validation of the quality of life questionnaire of the European Foundation for Osteoporosis (QUALEFFO). Osteoporosis International. 1999; 10(2): 150-160.
25. Scheier MF, Carver CS, Bridges MW. Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): a reevaluation of the Life Orientation Test. J Pers Soc Psychol. 1994; 67(6): 1063-1078.
26. Sultan S, Bureau B. Which optimism in health psychology? European Review of Applied Psychology-Revue Europeenne De Psychologie Appliquee. 1999; 49(1): 43-51.
27. Glaesmer H, Rief W, Martin A, Mewes R, Brahler E, Zenger M, Hinz A. Psychometric properties and population-based norms of the Life Orientation Test Revised (LOT-R). British Journal of Health Psychology. 2012; 17: 432-445.
28. Bianchi ML, Orsini M R, Saraifoger S, Ortolani S, Radaelli G, Betti S. Quality of life in post-menopausal osteoporosis. Health Qual Life Outcomes. 2005; 3: 78.
29. Romagnoli E, Carnevale V, Nofroni I, D’Erasmo E, Paglia F, De Geronimo, et al. Quality of life in ambulatory postmenopausal women: the impact of reduced bone mineral density and subclinical vertebral fractures. Osteoporos Int. 2004; 15(12): 975-980.
30. Cohen A, Liu XS, Stein EM, McMahon DJ, Rogers HF, Lemaster J, et al. Bone microarchitecture and stiffness in premenopausal women with idiopathic osteoporosis. J Clin Endocrinol Metab. 2009; 94(11): 4351-4360.
31. Dennison EM, Jameson KA, Syddall HE, Martin HJ, Cushnaghan J, et al. Bone health and deterioration in quality of life among participants from the Hertfordshire cohort study. Osteoporosis International. 2010; 21(11): 1817-1824.
Xijing He. The Role of Bone Mineral Density Assessment in Health-Related Quality of Life in Postmenopausal Han Chinese Women Prior to Clinic Diagnosis of Osteoporosis . Annals of Clinical and Medical Case Reports 2022