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Quality of life of childbearing age women and its associated factors: an application of seemingly unrelated regression (SUR) models

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Abstract

Purpose

This article is a report of using seemingly unrelated regression (SUR) models to examine the determinants of different dimensions of quality of life (QoL) among childbearing age women. There are a limited number of studies on QoL and its associated factors among women in developing countries such as Iran. Therefore, more attention should be focused on identifying these issues.

Methods

We administered the Persian’s abbreviated version of the World Health Organization Quality of Life (WHOQOL-BREF) questionnaire to 1,067 married women aged between 15 and 49 years. The women were chosen via a multistage research design from the rural region of Shiraz, the center of Fars Province in Iran in 2008. Clinical and socio-demographic characteristics as well as their reproductive health-related characteristics were investigated. To identify associated factors of QoL dimensions, ordinary least squares (OLS) regression and SUR were used and their findings were compared.

Results

The WHOQOL-BREF showed acceptable consistency (Cronbach’s alpha range: 0.62–0.75 across domains). Lower age, absence of long-term illness, economic status satisfaction, higher level of education, lower number of pregnancies, and higher body mass index were important associated factors of different dimensions of the QoL among these women. The estimated parameters for these factors were in close agreement in both OLS and SUR estimation methods. However, the SUR estimator provided the higher precision of the estimates than the OLS estimator, as the parameters obtained by SUR are characterized by lower standard errors. Women’s age, income satisfaction, and level of education were common for all domains.

Conclusions

This study presents a novel approach to simultaneously predict QoL domains using the SUR estimators and the results are relevant for implementing objective QoL. SUR estimators performed consistently better than the OLS estimators, since SUR takes the correlation between error terms into account. Thus, the SUR method could be a useful methodology for predicting QoL domains.

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Abbreviations

BMI:

Body mass index

OLS:

Ordinary least squares

QoL:

Quality of life

SAS:

Statistical analysis system

SE:

Standard error

SPSS:

Statistical package for social sciences

SUR:

Seemingly unrelated regression

VIF:

Variance inflation factor

WHOQOL-BREF:

World Health Organization Quality of Life questionnaire

References

  1. WHOQOL group. (1993). Study protocol for the World health organization project to develop a quality of life assessment instrument (WHOQOL). Quality of Life Research, 2, 153–159.

    Article  Google Scholar 

  2. Vaz, A. F., Pinto-Neto, A. M., Conde, M. C., Costa-Paiva, L., Morais, S. S., & Esteves, S. B. (2007). Quality of life of women with gynaecologic cancer: Associated factors. Archives of Gynecology and Obstetrics, 276, 583–589.

    Article  PubMed  Google Scholar 

  3. D’Souza, M. S., Somayaji, G., & Nairy, K. S. (2011). Determinants of reproductive health and related quality of life among Indian women in mining communities. Journal of Advanced Nursing, 1963–1975.

  4. Lee, M. K., Son, B. H., Hwang, S. Y., Han, W., Yang, J. H., Lee, S., et al. (2007). Factors affecting health-related quality of life in women with recurrent breast cancer in Korea. Quality of Life Research, 16, 559–569.

    Article  PubMed  Google Scholar 

  5. Wool, C., Cerutti, R., Marquis, P., et al. (2000). Psychometric validation of two Italian quality of life questionnaires in menopausal women. Maturitas, 35, 129–142.

    Article  PubMed  CAS  Google Scholar 

  6. Satoh, T., & Ohashi, K. (2005). Quality of life assessment in community-dwelling, middle-aged, healthy women in Japan. Climacteric, 8, 146–153.

    Article  PubMed  CAS  Google Scholar 

  7. Forger, F., Ostensen, M., Schumacher, A., & Villiger, P. M. (2005). Impact of pregnancy on health related quality of life evaluated prospectively in pregnant women with rheumatic diseases by the SF-36 health survey. Annals of the Rheumatic Diseases, 64, 1494–1499.

    Article  PubMed  CAS  Google Scholar 

  8. Hsiung, P. C., Fang, C. T., Chang, Y. Y., Chen, M. Y., & Wang, J. D. (2005). Comparison of WHOQOL-BREF and SF-36 in patient with HIV infection. Quality of Life Research, 14, 141–150.

    Article  PubMed  Google Scholar 

  9. Skevington, S. M., Lotfy, M., & O’Connell, K. A. (2004). The World Health Organization’s WHOQOL-BREF quality of life assessment: Psychometric properties and results of the international field trial. A report from the WHOQOl group. Quality of Life Research, 13, 299–310.

    Article  PubMed  CAS  Google Scholar 

  10. Wang, W. C., Yao, G., Tsai, Y. J., Wang, J. D., & Hsieh, C. L. (2006). Validating, improving reliability and estimating correlation of the four subscales in the WHOQOL-BREF using multidimensional rasch analysis. Quality of Life Research, 15(4), 607–620.

    Article  PubMed  Google Scholar 

  11. Zellner, A. (1962). An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association, 57, 348–368.

    Article  Google Scholar 

  12. Chung, M., Hsu, N., Wang, Y., Lai, K. L., & Kao, S. (2007). Exploration into the variance in self-reported health-related quality of life between the chronically-ill elderly and their family caregivers. Journal of Nursing Research, 15(3), 175–181.

    Article  PubMed  Google Scholar 

  13. Vermuelen, K. M., Bij, W. V., Erasmus, M. E., & Tenvergert, E. M. (2007). Long term health-related quality of life after lung transplantation: Different predictors for different dimensions. The Journal of Heart and Lung Transplantation, 26(2), 188–193.

    Article  PubMed  Google Scholar 

  14. Kuehner, C., & Buerger, C. (2005). Determinants of subjective quality of life in depressed patients: The role of self-esteem, response styles, and social support. Journal of Affective Disorders, 86, 205–213.

    Article  PubMed  Google Scholar 

  15. Yu, H. M., Ren, X. W., Chen, Q., Zhao, T. Y., Zhu, T. J., & Guo, Z. X. (2008). Quality of life of coal dust workers without pneumoconiosis in mainland China. Journal of Occupation Health, 50(6), 505–511.

    Article  Google Scholar 

  16. The WHOQOL group. (1998). Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychological Medicine, 28, 551–558.

    Article  Google Scholar 

  17. Nedjat, S., Montazeri, A., Holakouie, K., Mohammad, K., & Majdzadeh, R. (2008). Psychometric properties of the Iranian interview-administered version of the world health organization’s quality of life questionnaire (WHOQOL-BREF): A population-based study. BMC Health Services Research, 8(61), 1–7.

    Google Scholar 

  18. The WHOQOL group. (1998). The World Health Organization Quality of Life assessment (WHOQOL): Development and general psychometric properties. Social Science and Medicine, 46, 1569–1585.

    Article  Google Scholar 

  19. Judge, G. G., Hill, R. C., Griffiths, W. E., Lutkepohl, H., & Lee, T. C. (1988). Introduction to the theory and practice of econometrics (2nd ed.). New York: Wiley.

    Google Scholar 

  20. Yahya, W. B., Adebayo, S. B., Jolayemi, E. T., Oyejola, B. A., & Sanni, O. O. M. (2008). Effects of non-orthogonality on the efficiency of seemingly unrelated regression (SUR) models. InterStat Journal, 1–29.

  21. Timm, N. H. (2002). Applied multivariate analysis. New York: Springer.

    Google Scholar 

  22. Neter, J., Wasserman, W., & Kutner, M. H. (1983). Applied linear statistical models. Homewood: Richard D.Irwin Inc.

    Google Scholar 

  23. Lai, K. L., Tzeng, R. J., Wang, B. L., Lee, H. S., Amidon, L. R., & Kao, S. (2005). Health-related quality of life and health utility for the institutional elderly in Taiwan. Quality of Life Research, 14, 1169–1180.

    Article  PubMed  Google Scholar 

  24. Chan, G. W., Ungvari, G. S., Shek, D. T., & Leung Dagger, J. J. (2003). Hospital and community-based care for patients with chronic schizofrenia in Hong Kong quality of life and its correlates. Social Psychiatry and Psychiatric Epidemiology, 38, 196–203.

    Article  PubMed  Google Scholar 

  25. Chen, Y. C., Chie, W. C., Kuo, S. C., Lin, Y. H., Lin, S. J., & Chen, P. C. (2007). The association between infant feeding pattern and mother’s quality of life in Taiwan. Quality of Life Research, 16, 1281–1288.

    Article  PubMed  Google Scholar 

  26. Meiyanti, Kalumpiu., & Mulia, I. J. (2009). Anemia decreases quality of life of the elderly in Jakarta. Universa Medicina, 28, 152–160.

    Google Scholar 

  27. Khosravi, A., Ramezani, M. A., Toghianifar, N., Rabiei, K., Jahandideh, M., & Yousofi, A. (2010). Association between hypertension and quality of life in a sample of Iranian adults. Acta Cardiologica, 65(4), 425–430.

    PubMed  Google Scholar 

  28. Theodrou, M., Kaitelidou, D., Galanis, P., Middleton, N., Theodorou, P., Stafyla, P., et al. (2011). Quality of life measurement in patients with hypertension in Cyprus. The Hellenic Journal of Cardiology, 52, 407–415.

    Google Scholar 

  29. Beasley, T. M. (2008). Seemingly unrelated regression (SUR) models as a solution to path analytic models with correlated errors. Multiple Linear Regression Viewpoints, 34(1), 1–7.

    Google Scholar 

  30. Lesaffre, E., Rizopoulos, D., & Tsonaka, R. (2007). The logistic transform for bounded outcome scores. Biostatistics, 8, 72–85.

    Article  PubMed  Google Scholar 

  31. Bottai, M., Cai, B., & McKeown, E. R. (2010). Tutorials in biostatistics: Logistic quantile regression for bounded outcomes. Statistics in Medicine, 29, 309–317.

    PubMed  Google Scholar 

  32. Desai, M., & Begg, M. D. (2008). A comparison of regression approaches for analyzing clustered data. American Journal of Public Health, 98(8), 1425–1429.

    Article  PubMed  Google Scholar 

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Acknowledgments

This article is extracted from a Ph.D dissertation by Sareh Keshavarzi in Biostatistics, Shiraz University of Medical Sciences, Shiraz, Iran. The study was financially supported through the grants from Shiraz University of Medical Sciences.

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Authors and Affiliations

  1. Department of Biostatistics, Shiraz University of Medical Sciences, Shiraz, Iran

    Sareh Keshavarzi, Seyyed Mohammad Taghi Ayatollahi & Najaf Zare

  2. Faculty of Nursing and Midwifery, Shiraz University of Medical Science, Shiraz, Iran

    Farkhondeh Sharif

Authors
  1. Sareh Keshavarzi
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  2. Seyyed Mohammad Taghi Ayatollahi
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  3. Najaf Zare
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  4. Farkhondeh Sharif
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Correspondence to Seyyed Mohammad Taghi Ayatollahi.

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Keshavarzi, S., Ayatollahi, S.M.T., Zare, N. et al. Quality of life of childbearing age women and its associated factors: an application of seemingly unrelated regression (SUR) models. Qual Life Res 22, 1255–1263 (2013). https://doi.org/10.1007/s11136-012-0250-3

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