Modelling the Factors Associated With Quality of Life in Females With Osteoporosis: a Cross-sectional Study

doi:10.21203/rs.3.rs-1442905/v1

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Modelling the Factors Associated With Quality of Life in Females With Osteoporosis: a Cross-sectional Study

https://doi.org/10.21203/rs.3.rs-1442905/v1

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Background: Studying the important factors contributing to different Health-related quality of life (HRQoL) subscales is essential for implementing preventive measures to increase the HRQoL among osteoporotic patients. We here evaluated the variables affecting the mental and physical QoL in a sample population of Iranian osteoporotic women.

Methods: In this cross-sectional study, the participants included 111 women with osteoporosis in 2013. Physical and mental of QoL were measured by the ECOS-16 questionnaire. Other variables included T-score, age, body mass index, educational level, marital status, duration of the disease, history of bone fracture in the past year, the number of pregnancies, and weekly walking hours. Final regression coefficients were obtained based on the total effects of estimations (decompositions of effects into direct, indirect and total effects) by SEM analysis.

Results: The mean scores of physical and mental domains of QoL were 54.12±21.22 and 54.42 ±25.11 respectively. Finally, the mean of T-score was -3.21± 0.92. Based on the regression coefficients calculated in the SEM model, the number of pregnancies(-1.18), and weekly walking hours(2.19) were the main determinants of physical aspect of QoL. Furthermore, age and weekly walking hours significantly influenced the mental aspect of QoL.

Conclusions: The present study indicated that weekly walking hours, the number of pregnancies, and disease duration affected physical QoL while weekly walking hours and age were predictors of mental QoL. These results can provide a guide for healthcare decision-makers to improve the life style and HRQoL of patients with osteoporosis.

Quality of life

Osteoporosis

Structural Equation Model

Iran

The aging of populations around the world has been more quickly than ever before. The bone mineral density (BMD) declines with age, especially in postmenopausal women (Cummings and Melton 2002, Khanna, Gupta et al. 2005). According to the world health organization (WHO), the prevalence of osteoporosis is about 30% among postmenopausal women (Bhatia, Mishra et al. 2018). Generally, losing bone begins at a younger age and progresses at a faster rate in women compared to men (Alswat 2017). In fact, osteoporosis is four times more prevalent in women than men (Alswat 2017). There are currently about 200 million women with osteoporosis around the world. Although osteoporosis is currently more common in developed North American and European nations, its prevalence has increased in developing countries as well (Lane 2006).

Osteoporosis disposes patients to bone fractures imposing remarkable medical, social, and economic burden and jeopardizing the patients’ quality of life (QoL) (Toyokawa, Khanna, Gupta et al. 2005, Bhatia, Mishra et al. 2018, Cui, Xu et al. 2019). The health-related quality of life (HRQoL) is a subgroup of QoL assessing physical and emotional features. Indeed, the HRQoL is the objective assessment of subjective feelings. In epidemiologic studies, HRQoL is used to estimate the burden and morbidity of diseases, as well as to optimize health care applications and improve the cost-effectiveness of therapeutic interventions (Lips and van Schoor 2005, Madureira, Ciconelli et al. 2012). The specific issues in osteoporosis can be deeply explored by disease-specific rather than general HRQoL questionnaires. The general questionnaires do not evaluate disease specific issues such as fear of falling, bone fractures, disproportioned clothing, and general patients’ concerns about the future which may lead to a skewed or imperfect picture of the HRQoL in osteoporotic women (Group 1997). Some studies have estimated that HRQoL of osteoporotic women was lower than that of normal population (de Oliveira Ferreira, Arthuso et al. 2009, Guillemin, Martinez et al. 2013). Different factors contributing to the HRQoL of osteoporotic women include demographic features, life style related factors, history of bone fractures, osteoporosis severity, as well as reproductive and physical functions (de Oliveira Ferreira, Arthuso et al. 2009, Guillemin, Martinez et al. 2013, Liu, Zeng et al. 2013).

Studying the important factors contributing to different HRQoL subscales is essential for implementing preventive measures to increase the HRQoL among osteoporotic patients. Therefore, we here evaluated the variables affecting the mental and physical QoL in a sample population of Iranian osteoporotic women. We here used the ECOS-16 osteoporosis specific questionnaire (Moradzadeh R, Moghimi N et al. 2018) and employed the structural equation modeling (SEM) analysis.

Study participants

In this cross-sectional study, the participants included 111 women with osteoporosis diagnosed by a rheumatologist in a rheumatology clinic in Sanandaj, Iran. The participants were recruited by convenience sampling in 2013. For reliable correlation and regression analyses and in according to the Cohen (Cohen 1988) suggestion, the sample size was decided as 110 to achieve the power of 0.80, the medium effect size of 0.15, and an alpha level of .05 (Huang, Liao et al. 2015).

Osteoporosis was diagnosed based on BMD with T-score < -2.5. The questionnaires were completed either self-administratively (for educated patients) or by face to face interviews (for illiterate patients). The interviews were conducted by a nurse educated in osteoporosis and blinded to the study aims. The interviews were conducted in a private room to make the respondents feel comfortable.

The variables

The two main outcome variables in this study included physical and mental functions of QoL. These variables were measured by the ECOS-16 questionnaire which has been cross-cultural adapted in Persian language in a previous study in Sanandaj by Moradzadeh et al.(Moradzadeh R, Moghimi N et al. 2018). Each item was scored between 1 to 5 with higher scores indicating a better QoL. In this study, the obtained scores were multiplied by 100. The 16 items of the ECOS-16 questionnaire were categorized into two main domains of physical (pain and physical subscales) and mental (fear of illness and psychological function) QoL. Other variables included T-score, age, body mass index (BMI), educational level, marital status, duration of the disease, history of bone fracture in the past year, the number of pregnancies, and weekly walking hours.

The ethical issues in medical research were completely observed, and the study was approved by the ethic committee. All the participants completed an informed consent. Furthermore, all the completed questionnaires were kept confidential by the researcher.

Statistical analysis

Statistical analyses were carried out in Stata 12.0 software. Following the descriptive analysis, statistically significant associations between physical and mental QoL dimensions with each of variables were assessed by independent samples student t-test. The analysis of variance (ANOVA) and bonferroni's test were used for multiple comparisons. The p-value < 0.05 was considered as statistical significance threshold. The small missing values (e.g. 10 and 2 data points in BMI and Educational level respectively) were imputed using EM algorithm method. Using an iterative approach, the means, covariance matrixes, and the correlations between the quantitative variables were investigated. The missing values were also estimated by the EM method. Nevertheless, the covariance-based statistics calculated by EM method using the imputed values may underestimate their respective values.

The SEM analysis was used as the path model. The linear regression models in SEM fit into a single-level data. However, the SEM is not merely a linear regression but also a way of thinking, writing, and estimating parameters. The final regression coefficients were obtained based on the total effects of estimates (i.e. decompositions of effects into direct, indirect and total effects). The goodness of fit model was evaluated by Chi Square test and degrees of freedom (df), the root mean square error of approximation (RMSEA), probability RMSEA < = 0.05, and CFI and TLI indices.

Demographic characteristics

The demographic characteristics of study participants have been presented in Table 1. The most of the participants were married and illiterate. Seventeen percent of the included patients had history of bone fractures in the past year. The mean age of the studied sample population was 58.93 ± 10.13 years old. Furthermore, the average BMI was 28.29 kg/m2. The mean number of pregnancies was 5.37. The means of weekly walking hours and disease duration were 1.43 hours and 6.11 years respectively.

Considering different subscales of QoL, the mean scores of pain, physical function, psychological function and fear of illness were 49.14 ± 24.39, 59.10 ± 22.18, 69.76 ± 22.67 and 39.08 ± 37.39 respectively. Furthermore, the mean scores of physical and mental domains of QoL were 54.12 ± 21.22 and 54.42 ± 25.11 respectively. Finally, the mean of T-score was − 3.21 ± 0.92.

As shown in Table 1, the mean scores of physical and mental domains of QoL were significantly different among age groups and educational levels. However, there was no significant differences in QoL dimensions based on marital status and history of bone fracture during the past year. There was a statistically significant moderate correlation between physical and mental aspects of QoL (r = 0.58, p-value = 0.001). There were also significant correlations between the mean scores of physical and mental QoL and the number of pregnancies and weekly walking hours but not BMI and disease duration (Table 2).

SEM analysis

The path diagram achieved by SEM analysis has been displayed in Fig. 1. The associations between the independent variables (i.e. age, BMI, educational level, marital status, duration of disease, history of bone fracture in the past year, the number of pregnancies, and weekly walking hours) and dependent variables (i.e. physical and mental QoL aspects) were determined to develop a fit model. In addition, the history of bone fracture in the past year was considered as the mediator between disease duration and physical and mental QoL dimensions.

The goodness of fit indices indicated suitable fitness model on our data. Chi Square test and related degree of freedom were obtained 11.66 and 11 respectively (P-value = 0.39). The RMSEA and probability RMSEA < = 0.05 were calculated as 0.023 and 0.62 respectively. In addition, the CFI and TLI indices were obtained as 0.99 and 0.98 respectively.

The regression coefficients calculated based on the SEM model have been shown in Table 3. The number of pregnancies (-1.18), and weekly walking hours (2.19) were the main determinants of physical aspect of QoL. In this regard, more pregnancies were associated with decreased physical QoL. On the other hand, higher weekly walking hours predicted higher physical QoL. The duration of disease was negatively associated with physical QoL; however, this was not statistically significant (p = 0.096). Furthermore, age and weekly walking hours significantly influenced the mental aspect of QoL. Higher age (i.e. individuals older than 65 years old) resulted in poorer mental QoL while longer weekly walking hours predicted better mental QoL. No statistically significant relationships were found between other variables and QoL dimensions except for the history of bone fracture in the past year and BMI that were inversely correlated with physical QoL. In addition, history of bone fracture in the past year, longer disease duration, and being single decreased mental QoL. Finally, higher educational level was associated with an increase in the mental QoL score.

Osteoporosis is a public health issue worldwide. The patients with osteoporosis have limited physical and mental functions. The pain, insomnia, fatigue, and reduced mobility caused by osteoporosis can lead to social isolation and depression and consequently poor HRQoL in these patients (Bianchi, Orsini et al. 2005, Garip, Eser et al. 2015, Al-Sari, Tobias et al. 2016, Drozd, Mazur et al. 2016).

Our findings highlighted that weekly walking hours, disease duration, and the number of pregnancies were important determinants of physical QoL. On the other hand, age and weekly walking hours influenced mental QoL in our patients. In other studies, patients’ awareness of reduced BMD has been highlighted as a factor intensifying anxiety, as well as fear of falling and bone fractures in osteoporotic patients which in turn results in reduced independence and poorer HRQoL (Wilson, Sharp et al. 2012). Align with this, the HRQoL scores in all the four domains were low in osteoporotic women in our study indicating the lower fear of illness in these patients.

In present study, mental QoL reduced with increasing age which is in parallel with previous studies. The physical functioning of older women has also been limited due to the fear of falling and possible fractures (Al-Sari, Tobias et al. 2016, Bączyk, Samborski et al. 2016).

Weekly walking hours has been associated with longer life span, lower risk of diseases and more desirable HRQoL in osteoporotic patients (http://www.who.int/dietphysicalactivity/factsheet_olderadults/en). In line with other studies (Moriyama, Oneda et al. 2008, Bączyk, Samborski et al. 2016), we also found that weekly walking hours had a positive impact on both physical and mental QoL of osteoporotic women.

The number of pregnancies negatively affected the physical QoL of osteoporotic women in our study which is consistent with a previous report noting that women with more pregnancies had lower HRQoL (Singh and Kaur 2015). Women’s health is substantially decreased during and after pregnancy. In fact, maternal BMD decreases by about 3 percent during each pregnancy (Michaëlsson, Baron et al. 2001). After delivery, other activities and problems including breastfeeding, child-rearing, limited physical activity due to obesity, postpartum stress, low back pain, pelvic pain, and other issues in parous woman exaggerate the reduced maternal health leading to poorer HRQoL (Singh and Kaur 2015).

A negative association has been reported between BMI and HRQoL in some studies. Actually, interventions for weight loss improved HRQoL over time (Heo, Allison et al. 2003, Fontaine, Barofsky et al. 2004, Papaioannou, Kennedy et al. 2006). In the present study, BMI negatively correlated with physical and mental QoL; however, the correlations were not statistically significant.

Women with higher education have probably more knowledge and better understanding of their disease which make them to adhere to their medical regimen more effectively. Furthermore, educated women are expected to have higher coping capabilities with the condition (Abourazzak, Allali et al. 2009). Accordingly, higher education has been noted as a mitigating factor toward HRQoL in multiple studies (Badia, Díez-Pérez et al. 2004, Bączyk, Samborski et al. 2016, Morfeld, Vennedey et al. 2017).

In our study, higher BMI, history of fractures in the past year and being single were associated with lower scores of physical and mental QoL. Nevertheless, these associations were statistically insignificant which might be due to the high variance in QoL sub-categories.

One of the limitations in our study included self-reported data collection. Although self-reporting is a routine approach in medical research (Moradzadeh, Mansournia et al. 2018), there may be potential risk of misclassification bias on the findings (Moradzadeh R, Golmohammadi P et al. 2018) which can be decreased by applying bias analysis methods (Moradzadeh, Mansournia et al. 2018, Moradzadeh, Mansournia et al. 2019). On the other hand, selection bias is another committed bias. The included patients were recruited from a rheumatology clinic; however, some patients might refer to other specialists such as internists, or orthopedist. So, we didn’t have access to some patients that might lead to selection bias. Furthermore, there were a number of other variables that we could not assess them, and it is suggested to include these in future studies. Also, the impact of the mediators and interactions between the variables should be considered deeper.

In conclusion, the present study indicated a model on the determinants of physical and mental QoL in women with osteoporosis. This model emphasized that weekly walking hours, the number of pregnancies, and disease duration affected physical QoL while weekly walking hours and age were predictors of mental QoL. These results can provide a guide for healthcare decision-makers to improve the life style and HRQoL of patients with osteoporosis.

Ethics approval and consent to participate

The study was approved by the Ethic committee of Arak University of Medical Sciences, Arak, Iran (ethic code: IR.ARAKMU.REC.1394.382) and written informed consent was obtained from all participants. The study was conducted according to the guidelines of the Declaration of Helsinki.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests

Funding

Not applicable.

Authors' contributions

RM, MZ, and MT contributed in the conception and design of the study, acquisition of data, analysis and interpretation of data, drafting the article and final approval of the version to be submitted.

Acknowledgements

Not applicable.

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Table 1: The differences among characteristics versus quality of life (N=111)

Variable Name			Physical quality of life			Mental quality of life
		N(%) Mean ± SD	Mean	SD	P-value	Mean	SD	P-value
Marital status
	married	96(86.49)	54.11	20.46	0.99	55.18	25.41	0.43
	Single/Discovered/widowed	15(13.51)	54.17	26.44	0.99	49.58	23.35	0.43
Education level
	illiterate	58(52.25)	46.29	19.92	0.0001^*	47.31	25.59	0.0017^**
	Elementary/middle school	29(26.13)	60.86	20.00		57.22	22.81
	High school and more	24(21.62)	64.90	18.70		68.23	20.56
history of bone fracture in the past year
	No	92(82.88)	55.03	20.84	0.32	55.74	25.17	0.22
	Yes	19(17.12)	49.74	23.05	0.32	48.03	24.46	0.22
Age
	< = 60	63(56.76)	58.37	20.26	0.015	61.46	24.06	0.001
	>60	48(43.24)	48.54	21.36	0.015	45.18	23.64	0.001

* Bonferroni's P-value of Physical QoL between illiterate and Elementary / middle school, illiterate and high school and more, Elementary / middle school and high school and more were 0.005, 0.001 and 1.00, respectively.

** Bonferroni's P-value of mental quality of life between illiterate and Elementary / middle school, illiterate and high school and more, Elementary / middle school and high school and more were 0.212, 0.001 and 0.293, respectively.

Table 2: Correlations among subject characteristics, and physical and mental quality of life, (N=111)

Variables	Mean ± SD	Physical quality of life	Mental quality of life
Variables	Mean ± SD	r^* (P-value)	r* (P-value)
BMI	28.29 ± 4.91	-0.15 (0.13)	-0.12 (0.23)
Number of pregnancies	5.37 ± 3.41	-0.30 (0.001)	-0.29 (0.002)
Weekly walking hours	1.43 ± 2.43	0.28 (0.003)	0.26 (0.006)
Duration of the disease	6.11 ± 6.09	-0.17 (0.071)	-0.17 (0.075)

*r: Spearman Correlation Coefficient

Table 3: Total effects of the variables on the sub scales of quality of life based on the SEM analysis.

Subscales of quality of life	Variables	coefficient	P-value	95% Confidence Intervals
Physical quality of life	History of bone fracture in the past year	-2.93	0.55	(-12.53, 6.67)
	BMI	-0.25	0.46	(-0.90, 0.40)
	Number of pregnancies	-1.18	0.022	(-2.19, -0.17)
	Weekly walking hours	2.19	0.004	(0.70, 3.68)
	Duration of the disease	-0.51	0.096	(-1.11, 0.09)
Mental quality of life	History of bone fracture in the past year	-4.79	0.400	(-15.94, 6.36)
	Age	-9.15	0.026	(-17.20, -1.11)
	Weekly walking hours	2.26	0.015	(0.44, 4.07)
	Marital status	-5.02	0.39	(-16.34, 6.30)
	Education level	3.90	0.139	(-1.27, 9.08)
	Duration of the disease	-0.47	0.198	(-1.17, 0.24)

Goodness of fit indices: Chi Square = 11.66, DF = 11 (P-value = 0.39), RMSEA = 0.023, Probability RMSEA <= 0.05 = 0.62, CFI = 0.99, TLI = 0.98

No competing interests reported.

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Modelling the Factors Associated With Quality of Life in Females With Osteoporosis: a Cross-sectional Study

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