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  • Predictors of mental health in post-menopausal women: Results from the Australian healthy aging of women study

    Author(s)
    Seib, Charrlotte
    Anderson, Debra
    Lee, Kathryn
    Humphreys, Janice
    Griffith University Author(s)
    Anderson, Debra J.
    Seib, Charrlotte
    Year published
    2013
    Metadata
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    Abstract
    Objective To examine the extent to which socio-demographics, modifiable lifestyle, and physical health status influence the mental health of post-menopausal Australian women. Methods Cross-sectional data on health status, chronic disease and modifiable lifestyle factors were collected from a random cross-section of 340 women aged 60–70 years, residing in Queensland, Australia. Structural equation modeling (SEM) was used to measure the effect of a range of socio-demographic characteristics, modifiable lifestyle factors, and health markers (self-reported physical health, history of chronic illness) on the latent construct of ...
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    Objective To examine the extent to which socio-demographics, modifiable lifestyle, and physical health status influence the mental health of post-menopausal Australian women. Methods Cross-sectional data on health status, chronic disease and modifiable lifestyle factors were collected from a random cross-section of 340 women aged 60–70 years, residing in Queensland, Australia. Structural equation modeling (SEM) was used to measure the effect of a range of socio-demographic characteristics, modifiable lifestyle factors, and health markers (self-reported physical health, history of chronic illness) on the latent construct of mental health status. Mental health was evaluated using the Medical Outcomes Study Short Form 12 (SF-12®) and Center for Epidemiologic Studies Depression Scale (CES-D). Results The model was a good fit for the data (χ2 = 4.582, df = 3, p = 0.205) suggesting that mental health is negatively correlated with sleep disturbance (β = −0.612, p < 0.001), and a history of depression (β = −0.141, p = 0.024).While mental health was associated with poor sleep, it was not correlated with most lifestyle factors (BMI, alcohol consumption, or cigarette smoking) or socio-demographics like age, income or employment category and they were removed from the final model. Conclusion Research suggests that it is important to engage in a range of health promoting behaviors to preserve good health. We found that predictors of current mental health status included sleep disturbance, and past mental health problems, while socio-demographics and modifiable lifestyle had little impact. It may be however, that these factors influenced other variables associated with the mental health of post-menopausal women, and these relationships warrant further investigation.
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    Journal Title
    Maturitas
    Volume
    76
    Issue
    4
    DOI
    https://doi.org/10.1016/j.maturitas.2013.09.003
    Subject
    Clinical Sciences not elsewhere classified
    Clinical Sciences
    Paediatrics and Reproductive Medicine
    Publication URI
    http://hdl.handle.net/10072/172290
    Collection
    • Journal articles

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