Literature DB >> 24907046

Predictors of prescribed medication use for depression, anxiety, stress, and sleep problems in mid-aged Australian women.

Margot J Schofield1, Asaduzzaman Khan.   

Abstract

OBJECTIVE: The study examined prevalence of self-reported use of medication recommended or prescribed by a doctor for depression, anxiety, stress, and sleep problems; and modelled baseline factors that predicted use over 3 years for each condition.
METHODS: Analyses were undertaken on the 2001 and 2004 surveys of mid-aged women in the Australian Longitudinal Study on Women's Health. Dependent variables were self-reported use in past 4 weeks of medications recommended or prescribed by a doctor for depression, anxiety, stress, or sleep problems in 2001 and 2004. Generalized Estimating Equations (GEE) were used to predict medication use for each condition over 3 years.
RESULTS: Prevalence of prescribed medication use (2001, 2004) for each condition was depression (7.2, 8.9 %), anxiety (7.4, 9.0 %), stress (4.8, 5.7 %), and sleep problems (8.7, 9.5 %). Multivariable analyses revealed that odds of medication use across 3 years in all four conditions were higher for women with poorer mental and physical health, using hormone replacement therapy (HRT), or having seen a counsellor; and increased over time for depression, anxiety, and stress models. Medication use for depression was also higher for overweight/obese women, ex-smokers, and unmarried. Medication use for anxiety was higher for unmarried and non-working/low occupational women. Medication use for stress was higher for non-working women. Additional predictors of medication for sleep were surgical menopause, and area of residence.
CONCLUSIONS: Self-reported use of prescribed medication for four mental health conditions is increased over time after controlling for mental and physical health and other variables. Research needs to explore decision-making processes influencing differential rates of psychoactive medication use and their relationship with health outcomes.

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Year:  2014        PMID: 24907046     DOI: 10.1007/s00127-014-0896-y

Source DB:  PubMed          Journal:  Soc Psychiatry Psychiatr Epidemiol        ISSN: 0933-7954            Impact factor:   4.328


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