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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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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ItemHow cigarette smoking may increase the risk of anxiety symptoms and anxiety disorders: a critical review of biological pathways(WILEY, 2013-05)Multiple studies have demonstrated an association between cigarette smoking and increased anxiety symptoms or disorders, with early life exposures potentially predisposing to enhanced anxiety responses in later life. Explanatory models support a potential role for neurotransmitter systems, inflammation, oxidative and nitrosative stress, mitochondrial dysfunction, neurotrophins and neurogenesis, and epigenetic effects, in anxiety pathogenesis. All of these pathways are affected by exposure to cigarette smoke components, including nicotine and free radicals. This review critically examines and summarizes the literature exploring the role of these systems in increased anxiety and how exposure to cigarette smoke may contribute to this pathology at a biological level. Further, this review explores the effects of cigarette smoke on normal neurodevelopment and anxiety control, suggesting how exposure in early life (prenatal, infancy, and adolescence) may predispose to higher anxiety in later life. A large heterogenous literature was reviewed that detailed the association between cigarette smoking and anxiety symptoms and disorders with structural brain changes, inflammation, and cell-mediated immune markers, markers of oxidative and nitrosative stress, mitochondrial function, neurotransmitter systems, neurotrophins and neurogenesis. Some preliminary data were found for potential epigenetic effects. The literature provides some support for a potential interaction between cigarette smoking, anxiety symptoms and disorders, and the above pathways; however, limitations exist particularly in delineating causative effects. The literature also provides insight into potential effects of cigarette smoke, in particular nicotine, on neurodevelopment. The potential treatment implications of these findings are discussed in regards to future therapeutic targets for anxiety. The aforementioned pathways may help mediate increased anxiety seen in people who smoke. Further research into the specific actions of nicotine and other cigarette components on these pathways, and how these pathways interact, may provide insights that lead to new treatment for anxiety and a greater understanding of anxiety pathogenesis.
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ItemA brief review of exercise, bipolar disorder, and mechanistic pathways(FRONTIERS MEDIA SA, 2015-03-04)Despite evidence that exercise has been found to be effective in the treatment of depression, it is unclear whether these data can be extrapolated to bipolar disorder. Available evidence for bipolar disorder is scant, with no existing randomized controlled trials having tested the impact of exercise on depressive, manic or hypomanic symptomatology. Although exercise is often recommended in bipolar disorder, this is based on extrapolation from the unipolar literature, theory and clinical expertise and not empirical evidence. In addition, there are currently no available empirical data on program variables, with practical implications on frequency, intensity and type of exercise derived from unipolar depression studies. The aim of the current paper is to explore the relationship between exercise and bipolar disorder and potential mechanistic pathways. Given the high rate of medical co-morbidities experienced by people with bipolar disorder, it is possible that exercise is a potentially useful and important intervention with regard to general health benefits; however, further research is required to elucidate the impact of exercise on mood symptomology.
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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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ItemThe impact of maternal smoking during pregnancy on depressive and anxiety behaviors in children: the Norwegian Mother and Child Cohort Study(BMC, 2015-02-03)BACKGROUND: Maternal smoking during pregnancy (MSDP) is associated with multiple adverse childhood outcomes including externalizing behaviors. However, the association between MSDP and internalizing (anxiety and depressive) behaviors in offspring has received less investigation. We aimed to assess the association between MSDP and childhood internalizing (anxiety and depressive) behaviors in a very large, well-characterized cohort study. METHODS: We assessed the association between MSDP and internalizing behaviors in offspring utilizing information drawn from 90,040 mother-child pairs enrolled in the Norwegian Mother and Child Cohort Study. Mothers reported smoking information, including status and frequency of smoking, twice during pregnancy. Mothers also reported their child's internalizing behaviors at 18 months, 36 months, and 5 years. Associations between MSDP and childhood internalizing behaviors, including dose-response and timing of smoking in pregnancy, were assessed at each time point. RESULTS: MSDP was associated with increased internalizing behaviors when offspring were aged 18 months (B = 0.11, P <0.001) and 36 months (B = 0.06, P <0.01), adjusting for numerous potential confounders. Higher rates of smoking (e.g., >20 cigarettes per day) were associated with higher levels of internalizing behaviors. Maternal smoking during early pregnancy appeared to be the critical period for exposure. CONCLUSIONS: We found evidence supporting a potential role for MSDP in increasing internalizing (anxiety and depressive) behaviors in offspring. We also found evidence supportive of a possible causal relationship, including dose-dependency and support for a predominant role of early pregnancy exposure. Further investigation utilizing genetically informed designs are warranted to assess this association.
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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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ItemSample selection and reasons for non-participation in the PRedictors and Outcomes of incident FRACtures (PROFRAC) study(PAGEPRESS PUBL, 2019)Background. Fragility fractures, associated with osteoporosis, are an escalating public health problem. We aim to describe sample selection, recruitment methods and reasons for non-participation in The PRedictors and Outcomes of incident FRACtures (PROFRAC) study. Design and Methods. Barwon Statistical Division residents aged 20+ years, with a radiologically-confirmed fracture between June 1st 2012 and May 31st 2013, were eligible. Individuals identified as fracture cases were invited by mail to complete a questionnaire. Reasons for non-participation were documented. Logistic regression techniques were used to determine odds ratios for participation and non-participation reasons. Results. A total of 1,458 of 2,155 (67.7%) adults with fracture (48.7% men) participated. Individuals were excluded due to inability to give informed consent, death, no knowledge of fracture, or inability to be contacted. The odds of participation decreased with age (OR 0.99, 95%CI 0.99-0.99, P=0.011) and increased among specific fracture groups [clavicle/scapula (OR 2.50, 1.30-4.68, P=0.006), forearm/humerus (OR 2.00, 1.22-3.27, P=0.006), wrist (OR 2.08, 1.31-3.32, P=0.002), hip (OR 2.12, 1.20-3.75, P=0.009), ankle (OR 1.85, 1.20-2.87, P=0.001), compared to face/skull fractures]. The odds of reporting disinterest, time constraints or personal reasons as the reason for non-participation decreased with age, whereas the odds of reporting frailty, language-related issues or illness as the reason for non-participation increased with of age [disinterest (OR 0.98, 0.97-0.98, P<0.001), time constraints (OR 0.97, 0.96-0.98, P<0.001), personal reasons (OR 0.98, 0.97-0.99, P=0.007), frailty (OR 1.12, 1.09-1.15, P<0.001), language-related issues (OR 1.02, 1.01-1.04, P<0.001), illness (OR 1.03, 1.02-1.05, P<0.001)]. Conclusions. Understanding drivers of research participation can inform study design to achieve optimal participation in health research.
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ItemMapping Cancer incidence across Western Victoria: the association with age, accessibility, and socioeconomic status among men and women(BMC, 2019-09-06)BACKGROUND: Cancer is a leading burden of disease in Australia and worldwide, with incidence rates varying with age, sex and geographic location. As part of the Ageing, Chronic Disease and Injury study, we aimed to map the incidence rates of primary cancer diagnoses across western Victoria and investigate the association of age, accessibility/remoteness index of Australia (ARIA) and area-level socioeconomic status (SES) with cancer incidence. METHODS: Data on cancer incidence in the study region were extracted from the Victorian Cancer Registry (VCR) for men and women aged 40+ years during 2010-2013, inclusive. The age-adjusted incidence rates (per 10,000 population/year), as well as specific incidence for breast, prostate, lung, bowel and melanoma cancers, were calculated for the entire region and for the 21 Local Government Areas (LGA) that make up the whole region. The association of aggregated age, ARIA and SES with cancer incidence rates across LGAs was determined using Poisson regression. RESULTS: Overall, 15,120 cancer cases were identified; 8218 (54%) men and 6902 women. For men, the age-standardised rate of cancer incidence for the whole region was 182.1 per 10,000 population/year (95% CI 177.7-186.5) and for women, 162.2 (95% CI: 157.9-166.5). The incidence of cancer (overall) increased with increasing age for men and women. Geographical variations in cancer incidence were also observed across the LGAs, with differences identified between men and women. Residents of socioeconomically disadvantaged and less accessible areas had higher cancer incidence (p < 0.001). CONCLUSION: Cancer incidence rates varied by age, sex, across LGAs and with ARIA. These findings not only provide an evidence base for identifying gaps and assessing the need for services and resource allocation across this region, but also informs policy and assists health service planning and implementation of preventative intervention strategies to reduce the incidence of cancer across western Victoria. This study also provides a model for further research across other geographical locations with policy and clinical practice implications, both nationally and internationally.