Psychiatry - Research Publications
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ItemThe association between major depressive disorder, use of antidepressants and bone mineral density (BMD) in men(JMNI, 2015-06)OBJECTIVE: Both depression and use of antidepressants have been negatively associated with bone mineral density (BMD) but mainly in studies among postmenopausal women. Therefore, the aim of this study was to investigate these relationships in men. METHODS: Between 2006 and 2011, 928 men (aged 24-98 years) from the Geelong Osteoporosis Study completed a comprehensive questionnaire, clinical measurements and had BMD assessments at the forearm, spine, total hip and total body. Major depressive disorder (MDD) was identified using a structured clinical interview (SCID-I/NP). The cross-sectional associations between BMD and both MDD and antidepressant use were analyzed using multivariable linear regression. RESULTS: Of the study population, 84 (9.1%) men had a single MDD episode, 50 (5.4%) had recurrent episodes and 65 (7.0%) were using antidepressants at the time of assessment. Following adjustments, recurrent MDD was associated with lower BMD at the forearm and total body (-6.5%, P=0.033 and -2.5%, P=0.033, respectively compared to men with no history of MDD), while single MDD episodes were associated with higher BMD at the total hip (+3.4%, P=0.030). Antidepressant use was associated with lower BMD only in lower-weight men (<75-110 kg depending on bone site). CONCLUSIONS: Both depression and use of antidepressants should be taken into account as possible risk factors for osteoporosis in men.
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ItemThe Role of Health Literacy in the Treatment of Osteoporosis(WILEY, 2016-10)
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ItemGender-specific risk factors for low bone mineral density in patients taking antipsychotics for psychosis(WILEY, 2018-01)OBJECTIVE: This study examined clinical and gender-specific risk factors for low bone mineral density (BMD) in adult patients with psychotic disorders. METHODS: The study included 285 community-dwelling patients with psychotic disorders. Dual-energy X-ray absorptiometry was used to measure BMD. Clinical characteristics associated with low BMD were identified with logistic regression analysis in total population and each gender. RESULTS: Fifty-eight (20.4%) subjects had low BMD. Low BMD was more common in men and in patients with low body mass indices (BMIs), as well as in those with shorter treatment durations, those on Medicaid, and patients using serotonergic antidepressants. Logistic regression analysis revealed that low BMD was negatively associated with BMI and treatment duration and positively with gender (male) and serotonergic antidepressants use in the overall population. In men, low BMD was associated with treatment duration and BMI; in women, low BMD was associated with BMI, prolactin level, vitamin D, and serotonergic antidepressant use. CONCLUSION: Managing the risk factors associated with low BMD among patients with psychotic disorder should be done gender-specifically. Psychotropic agents should be prescribed mindful of their effects on bone, as use of these medications is a modifiable risk factor for osteoporosis in women with psychotic disorders.
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ItemGastro oesophageal reflux disease (GORD)-related symptoms and its association with mood and anxiety disorders and psychological symptomology: a population-based study in women(BMC, 2013-07-24)BACKGROUND: Psychopathology seems to play a role in reflux pathogenesis and vice versa, yet few population-based studies have systematically investigated the association between gastro-oesophageal reflux disease (GORD) and psychopathology. We thus aimed to investigate the relationship between GORD-related symptoms and psychological symptomatology, as well as clinically diagnosed mood and anxiety disorders in a randomly selected, population-based sample of adult women. METHODS: This study examined data collected from 1084 women aged 20-93 yr participating in the Geelong Osteoporosis Study. Mood and anxiety disorders were identified using the Structured Clinical Interview for DSM-IV-TR Research Version, Non-patient edition (SCID-I/NP), and psychological symptomatology was assessed using the General Health Questionnaire (GHQ-12). GORD-related symptoms were self-reported and confirmed by medication use where possible and lifestyle factors were documented. RESULTS: Current psychological symptomatology and mood disorder were associated with increased odds of concurrent GORD-related symptoms (adjusted OR 2.1, 95% CI 1.3-3.5, and OR 3.0, 95% CI 1.7-5.6, respectively). Current anxiety disorder also tended to be associated with increased odds of current GORD-related symptoms (p = 0.1). Lifetime mood disorder was associated with a 1.6-fold increased odds of lifetime GORD-related symptoms (adjusted OR 1.6, 95% CI 1.1-2.4) and lifetime anxiety disorder was associated with a 4-fold increased odds of lifetime GORD-related symptoms in obese but not non-obese participants (obese, age-adjusted OR 4.0, 95% CI 1.8-9.0). CONCLUSIONS: These results indicate that psychological symptomatology, mood and anxiety disorders are positively associated with GORD-related symptoms. Acknowledging this common comorbidity may facilitate recognition and treatment, and opens new questions as to the pathways and mechanisms of the association.
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ItemPrevalence of mood and anxiety disorder in self reported irritable bowel syndrome (IBS). An epidemiological population based study of women(BMC, 2010-08-05)BACKGROUND: Irritable bowel syndrome (IBS) is commonly regarded as a functional disorder, and is hypothesized to be associated with anxiety and depression. This evidence mainly rests on population-based studies utilising self-report screening instruments for psychopathology. Other studies applying structured clinical interviews are generally based on small clinical samples, which are vulnerable to biases. The extant evidence base for an association between IBS and psychopathology is hence not conclusive. The aim of this study was therefore to re-examine the hypothesis using population-based data and psychiatric morbidity established with a structured clinical interview. METHODS: Data were derived from a population-based epidemiological study (n = 1077). Anxiety and mood disorders were established using the Structured Clinical Interview for DSM-IV-TR (SCID-I/NP) and the General Health Questionnaire (GHQ-12). Current and lifetime IBS was self-reported. Hypertension and diabetes were employed as comparison groups as they are expected to be unrelated to mental health. RESULTS: Current IBS (n = 69, 6.4%) was associated with an increased likelihood of current mood and/or anxiety disorders (OR = 2.62, 95%CI 1.49 - 4.60). Half the population reporting a lifetime IBS diagnosis also had a lifetime mood or anxiety disorder. Exploratory analyses demonstrated an increased prevalence of IBS across most common anxiety and mood disorders, the exception being bipolar disorder. The association with IBS and symptoms load (GHQ-12) followed a curved dose response pattern. In contrast, hypertension and diabetes were consistently unrelated to psychiatric morbidity. CONCLUSIONS: IBS is significantly associated with anxiety and mood disorders. This study provides indicative evidence for IBS as a disorder with a psychosomatic aspect.
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ItemStatin use and risk of depression: a Swedish national cohort study(BMC, 2014-12-04)BACKGROUND: Statin medications, used to prevent heart disease by reducing cholesterol, also reduce inflammation and protect against oxidative damage. As inflammation and oxidative stress occur in depression, there is interest in their potential to reduce depression risk. We investigated whether use of statin medications was associated with a change in the risk of developing depression in a very large Swedish national cohort (n = 4,607,990). METHODS: National register data for adults ≥40yr was analyzed to obtain information about depression diagnoses and prescriptions of statin medications between 2006 and 2008. Associations were tested using logistic regression. RESULTS: Use of any statin was shown to reduce the odds of depression by 8% compared to individuals not using statin medications (OR = 0.92, 95% CI, 0.89-0.96; p < 0.001). Simvastatin had a protective effect (OR = 0.93, 95% CI, 0.89-0.97; p = 0.001), whereas atorvastatin was associated with increased risk of depression (OR = 1.11, 95% CI, 1.01-1.22; p = 0.032). There was a stepwise decrease in odds ratio with increasing age (OR ≥ 40 years = 0.95, OR ≥ 50 years = 0.91, OR ≥ 60 years = 0.85, OR ≥ 70 years = 0.81). CONCLUSIONS: The use of any statin was associated with a reduction in risk of depression in individuals over the age of 40. Clarification of the strength of these protective effects, the clinical relevance of these effects and determination of which statins are most effective is needed.
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ItemPop, heavy metal and the blues: secondary analysis of persistent organic pollutants (POP), heavy metals and depressive symptoms in the NHANES National Epidemiological Survey(BMJ PUBLISHING GROUP, 2014)OBJECTIVES: Persistent environmental pollutants, including heavy metals and persistent organic pollutants (POPs), have a ubiquitous presence. Many of these pollutants affect neurobiological processes, either accidentally or by design. The aim of this study was to explore the associations between assayed measures of POPs and heavy metals and depressive symptoms. We hypothesised that higher levels of pollutants and metals would be associated with depressive symptoms. SETTING: National Health and Nutrition Examination Survey (NHANES). PARTICIPANTS: A total of 15 140 eligible people were included across the three examined waves of NHANES. PRIMARY AND SECONDARY OUTCOME MEASURES: Depressive symptoms were assessed using the nine-item version of the Patient Health Questionnaire (PHQ-9), using a cut-off point of 9/10 as likely depression cases. Organic pollutants and heavy metals, including cadmium, lead and mercury, as well as polyfluorinated compounds (PFCs), pesticides, phenols and phthalates, were measured in blood or urine. RESULTS: Higher cadmium was positively associated with depression (adjusted Prevalence Ratios (PR)=1.48, 95% CI 1.16 to 1.90). Higher levels of mercury were negatively associated with depression (adjusted PR=0.62, 95% CI 0.50 to 0.78), and mercury was associated with increased fish consumption (n=5500, r=0.366, p<0.001). In addition, several PFCs (perfluorooctanoic acid, perfluorohexane sulfonic acid, perfluorodecanoic acid and perfluorononanoic acid) were negatively associated with the prevalence of depression. CONCLUSIONS: Cadmium was associated with an increased likelihood of depression. Contrary to hypotheses, many of persistent environmental pollutants were not associated or negatively associated with depression. While the inverse association between mercury and depressive symptoms may be explained by a protective role for fish consumption, the negative associations with other pollutants remains unclear. This exploratory study suggests the need for further investigation of the role of various agents and classes of agents in the pathophysiology of depression.
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ItemInto the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample(PUBLIC LIBRARY SCIENCE, 2016-12-09)BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self-reported medical symptoms to identify and describe clusters of individuals with increased rates of depression from a large cross-sectional community based population epidemiological study. METHODS: A multi-staged methodology utilising ML and traditional statistical techniques was performed using the community based population National Health and Nutrition Examination Study (2009-2010) (N = 3,922). A Self-organised Mapping (SOM) ML algorithm, combined with hierarchical clustering, was performed to create participant clusters based on 68 medical symptoms. Binary logistic regression, controlling for sociodemographic confounders, was used to then identify the key clusters of participants with higher levels of depression (PHQ-9≥10, n = 377). Finally, a Multiple Additive Regression Tree boosted ML algorithm was run to identify the important medical symptoms for each key cluster within 17 broad categories: heart, liver, thyroid, respiratory, diabetes, arthritis, fractures and osteoporosis, skeletal pain, blood pressure, blood transfusion, cholesterol, vision, hearing, psoriasis, weight, bowels and urinary. RESULTS: Five clusters of participants, based on medical symptoms, were identified to have significantly increased rates of depression compared to the cluster with the lowest rate: odds ratios ranged from 2.24 (95% CI 1.56, 3.24) to 6.33 (95% CI 1.67, 24.02). The ML boosted regression algorithm identified three key medical condition categories as being significantly more common in these clusters: bowel, pain and urinary symptoms. Bowel-related symptoms was found to dominate the relative importance of symptoms within the five key clusters. CONCLUSION: This methodology shows promise for the identification of conditions in general populations and supports the current focus on the potential importance of bowel symptoms and the gut in mental health research.
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ItemFusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression(PUBLIC LIBRARY SCIENCE, 2016-02-05)BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. METHODS: The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. RESULTS: After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). CONCLUSION: The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.
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ItemRole of personality disorder in randomised controlled trials of pharmacological interventions for adults with mood disorders: a protocol for a systematic review and meta-analysis(BMJ PUBLISHING GROUP, 2019-06)INTRODUCTION: Remission rates for mood disorders, including depressive and bipolar disorders, remain relatively low despite available treatments, and many patients fail to respond adequately to these interventions. Evidence suggests that personality disorder may play a role in poor outcomes. Although personality disorders are common in patients with mood disorders, it remains unknown whether personality disorder affects treatment outcomes in mood disorders. We aim to review currently available evidence regarding the role of personality disorder on pharmacological interventions in randomised controlled trials for adults with mood disorders. METHODS AND ANALYSIS: A systematic search of Cochrane Central Register of Controlled Clinical Trials (CENTRAL) via cochranelibrary.com, PubMed via PubMed, EMBASE via embase.com, PsycINFO via Ebsco and CINAHL Complete via Ebsco databases will be conducted to identify randomised controlled trials that have investigated pharmacological interventions in participants aged 18 years or older for mood disorders (ie, depressive disorders and bipolar spectrum disorders) and have also included assessment of personality disorder. One reviewer will screen studies against the predetermined eligibility criteria, and a second reviewer will confirm eligible studies. Data will be extracted by two independent reviewers. Methodological quality and risk of bias will be assessed using the Cochrane Risk of Bias tool. A systematic review, and if sufficient evidence is identified, a meta-analysis will be completed. Meta-analysis will be conducted using the standardised mean difference approach and reported with 95% CIs. A random effects model will be employed and statistical heterogeneity will be evaluated using the I2 statistic. Prespecified subgroup analyses will be completed. ETHICS AND DISSEMINATION: As this systematic review will use published data, ethics permission will not be required. The outcomes of this systematic review will be published in a relevant scientific journal and presented at a research conference. TRIAL REGISTRATION NUMBER: CRD42018089279.