976 resultados para Physical Illness
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People with developmental disabilities are becoming an important part of the general practice population. Although they have a similar range of medical conditions to the general population, there are some important differences in prevalence, risk factors, presentation and management of particular conditions. We use gastro-oesophageal reflux to illustrate how developmental disability may affect the presentation, assessment and management of a common condition.
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Abstract and Summary of Thesis: Background: Individuals with Major Mental Illness (such as schizophrenia and bipolar disorder) experience increased rates of physical health comorbidity compared to the general population. They also experience inequalities in access to certain aspects of healthcare. This ultimately leads to premature mortality. Studies detailing patterns of physical health comorbidity are limited by their definitions of comorbidity, single disease approach to comorbidity and by the study of heterogeneous groups. To date the investigation of possible sources of healthcare inequalities experienced by individuals with Major Mental Illness (MMI) is relatively limited. Moreover studies detailing the extent of premature mortality experienced by individuals with MMI vary both in terms of the measure of premature mortality reported and age of the cohort investigated, limiting their generalisability to the wider population. Therefore local and national data can be used to describe patterns of physical health comorbidity, investigate possible reasons for health inequalities and describe mortality rates. These findings will extend existing work in this area. Aims and Objectives: To review the relevant literature regarding: patterns of physical health comorbidity, evidence for inequalities in physical healthcare and evidence for premature mortality for individuals with MMI. To examine the rates of physical health comorbidity in a large primary care database and to assess for evidence for inequalities in access to healthcare using both routine primary care prescribing data and incentivised national Quality and Outcome Framework (QOF) data. Finally to examine the rates of premature mortality in a local context with a particular focus on cause of death across the lifespan and effect of International Classification of Disease Version 10 (ICD 10) diagnosis and socioeconomic status on rates and cause of death. Methods: A narrative review of the literature surrounding patterns of physical health comorbidity, the evidence for inequalities in physical healthcare and premature mortality in MMI was undertaken. Rates of physical health comorbidity and multimorbidity in schizophrenia and bipolar disorder were examined using a large primary care dataset (Scottish Programme for Improving Clinical Effectiveness in Primary Care (SPICE)). Possible inequalities in access to healthcare were investigated by comparing patterns of prescribing in individuals with MMI and comorbid physical health conditions with prescribing rates in individuals with physical health conditions without MMI using SPICE data. Potential inequalities in access to health promotion advice (in the form of smoking cessation) and prescribing of Nicotine Replacement Therapy (NRT) were also investigated using SPICE data. Possible inequalities in access to incentivised primary healthcare were investigated using National Quality and Outcome Framework (QOF) data. Finally a pre-existing case register (Glasgow Psychosis Clinical Information System (PsyCIS)) was linked to Scottish Mortality data (available from the Scottish Government Website) to investigate rates and primary cause of death in individuals with MMI. Rate and primary cause of death were compared to the local population and impact of age, socioeconomic status and ICD 10 diagnosis (schizophrenia vs. bipolar disorder) were investigated. Results: Analysis of the SPICE data found that sixteen out of the thirty two common physical comorbidities assessed, occurred significantly more frequently in individuals with schizophrenia. In individuals with bipolar disorder fourteen occurred more frequently. The most prevalent chronic physical health conditions in individuals with schizophrenia and bipolar disorder were: viral hepatitis (Odds Ratios (OR) 3.99 95% Confidence Interval (CI) 2.82-5.64 and OR 5.90 95% CI 3.16-11.03 respectively), constipation (OR 3.24 95% CI 3.01-3.49 and OR 2.84 95% CI 2.47-3.26 respectively) and Parkinson’s disease (OR 3.07 95% CI 2.43-3.89 and OR 2.52 95% CI 1.60-3.97 respectively). Both groups had significantly increased rates of multimorbidity compared to controls: in the schizophrenia group OR for two comorbidities was 1.37 95% CI 1.29-1.45 and in the bipolar disorder group OR was 1.34 95% CI 1.20-1.49. In the studies investigating inequalities in access to healthcare there was evidence of: under-recording of cardiovascular-related conditions for example in individuals with schizophrenia: OR for Atrial Fibrillation (AF) was 0.62 95% CI 0.52 - 0.73, for hypertension 0.71 95% CI 0.67 - 0.76, for Coronary Heart Disease (CHD) 0.76 95% CI 0.69 - 0.83 and for peripheral vascular disease (PVD) 0.83 95% CI 0.72 - 0.97. Similarly in individuals with bipolar disorder OR for AF was 0.56 95% CI 0.41-0.78, for hypertension 0.69 95% CI 0.62 - 0.77 and for CHD 0.77 95% CI 0.66 - 0.91. There was also evidence of less intensive prescribing for individuals with schizophrenia and bipolar disorder who had comorbid hypertension and CHD compared to individuals with hypertension and CHD who did not have schizophrenia or bipolar disorder. Rate of prescribing of statins for individuals with schizophrenia and CHD occurred significantly less frequently than in individuals with CHD without MMI (OR 0.67 95% CI 0.56-0.80). Rates of prescribing of 2 or more anti-hypertensives were lower in individuals with CHD and schizophrenia and CHD and bipolar disorder compared to individuals with CHD without MMI (OR 0.66 95% CI 0.56-0.78 and OR 0.55 95% CI 0.46-0.67, respectively). Smoking was more common in individuals with MMI compared to individuals without MMI (OR 2.53 95% CI 2.44-2.63) and was particularly increased in men (OR 2.83 95% CI 2.68-2.98). Rates of ex-smoking and non-smoking were lower in individuals with MMI (OR 0.79 95% CI 0.75-0.83 and OR 0.50 95% CI 0.48-0.52 respectively). However recorded rates of smoking cessation advice in smokers with MMI were significantly lower than the recorded rates of smoking cessation advice in smokers with diabetes (88.7% vs. 98.0%, p<0.001), smokers with CHD (88.9% vs. 98.7%, p<0.001) and smokers with hypertension (88.3% vs. 98.5%, p<0.001) without MMI. The odds ratio of NRT prescription was also significantly lower in smokers with MMI without diabetes compared to smokers with diabetes without MMI (OR 0.75 95% CI 0.69-0.81). Similar findings were found for smokers with MMI without CHD compared to smokers with CHD without MMI (OR 0.34 95% CI 0.31-0.38) and smokers with MMI without hypertension compared to smokers with hypertension without MMI (OR 0.71 95% CI 0.66-0.76). At a national level, payment and population achievement rates for the recording of body mass index (BMI) in MMI was significantly lower than the payment and population achievement rates for BMI recording in diabetes throughout the whole of the UK combined: payment rate 92.7% (Inter Quartile Range (IQR) 89.3-95.8 vs. 95.5% IQR 93.3-97.2, p<0.001 and population achievement rate 84.0% IQR 76.3-90.0 vs. 92.5% IQR 89.7-94.9, p<0.001 and for each country individually: for example in Scotland payment rate was 94.0% IQR 91.4-97.2 vs. 96.3% IQR 94.3-97.8, p<0.001. Exception rate was significantly higher for the recording of BMI in MMI than the exception rate for BMI recording in diabetes for the UK combined: 7.4% IQR 3.3-15.9 vs. 2.3% IQR 0.9-4.7, p<0.001 and for each country individually. For example in Scotland exception rate in MMI was 11.8% IQR 5.4-19.3 compared to 3.5% IQR 1.9-6.1 in diabetes. Similar findings were found for Blood Pressure (BP) recording: across the whole of the UK payment and population achievement rates for BP recording in MMI were also significantly reduced compared to payment and population achievement rates for the recording of BP in chronic kidney disease (CKD): payment rate: 94.1% IQR 90.9-97.1 vs.97.8% IQR 96.3-98.9 and p<0.001 and population achievement rate 87.0% IQR 81.3-91.7 vs. 97.1% IQR 95.5-98.4, p<0.001. Exception rates again were significantly higher for the recording of BP in MMI compared to CKD (6.4% IQR 3.0-13.1 vs. 0.3% IQR 0.0-1.0, p<0.001). There was also evidence of differences in rates of recording of BMI and BP in MMI across the UK. BMI and BP recording in MMI were significantly lower in Scotland compared to England (BMI:-1.5% 99% CI -2.7 to -0.3%, p<0.001 and BP: -1.8% 99% CI -2.7 to -0.9%, p<0.001). While rates of BMI and BP recording in diabetes and CKD were similar in Scotland compared to England (BMI: -0.5 99% CI -1.0 to 0.05, p=0.004 and BP: 0.02 99% CI -0.2 to 0.3, p=0.797). Data from the PsyCIS cohort showed an increase in Standardised Mortality Ratios (SMR) across the lifespan for individuals with MMI compared to the local Glasgow and wider Scottish populations (Glasgow SMR 1.8 95% CI 1.6-2.0 and Scotland SMR 2.7 95% CI 2.4-3.1). Increasing socioeconomic deprivation was associated with an increased overall rate of death in MMI (350.3 deaths/10,000 population/5 years in the least deprived quintile compared to 794.6 deaths/10,000 population/5 years in the most deprived quintile). No significant difference in rate of death for individuals with schizophrenia compared with bipolar disorder was reported (6.3% vs. 4.9%, p=0.086), but primary cause of death varied: with higher rates of suicide in individuals with bipolar disorder (22.4% vs. 11.7%, p=0.04). Discussion: Local and national datasets can be used for epidemiological study to inform local practice and complement existing national and international studies. While the strengths of this thesis include the large data sets used and therefore their likely representativeness to the wider population, some limitations largely associated with using secondary data sources are acknowledged. While this thesis has confirmed evidence of increased physical health comorbidity and multimorbidity in individuals with MMI, it is likely that these findings represent a significant under reporting and likely under recognition of physical health comorbidity in this population. This is likely due to a combination of patient, health professional and healthcare system factors and requires further investigation. Moreover, evidence of inequality in access to healthcare in terms of: physical health promotion (namely smoking cessation advice), recording of physical health indices (BMI and BP), prescribing of medications for the treatment of physical illness and prescribing of NRT has been found at a national level. While significant premature mortality in individuals with MMI within a Scottish setting has been confirmed, more work is required to further detail and investigate the impact of socioeconomic deprivation on cause and rate of death in this population. It is clear that further education and training is required for all healthcare staff to improve the recognition, diagnosis and treatment of physical health problems in this population with the aim of addressing the significant premature mortality that is seen. Conclusions: Future work lies in the challenge of designing strategies to reduce health inequalities and narrow the gap in premature mortality reported in individuals with MMI. Models of care that allow a much more integrated approach to diagnosing, monitoring and treating both the physical and mental health of individuals with MMI, particularly in areas of social and economic deprivation may be helpful. Strategies to engage this “hard to reach” population also need to be developed. While greater integration of psychiatric services with primary care and with specialist medical services is clearly vital the evidence on how best to achieve this is limited. While the National Health Service (NHS) is currently undergoing major reform, attention needs to be paid to designing better ways to improve the current disconnect between primary and secondary care. This should then help to improve physical, psychological and social outcomes for individuals with MMI.
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Objective. To examine possible risk factors in post-stroke depression (PSD) other than site of lesion in the brain Data sources. 191 first-ever stroke patients were examined physically shortly after their stroke and examined psychiatrically and physically 4 months post-stroke. Setting. A geographically defined segment of the metropolitan area of Perth, Western Australia, from which all strokes over a course of 18 months were examined (the Perth Community Stroke Study). Measures. Psychiatric Assessment Schedule, Mini Mental State Examination, Barthel Index, Frenchay Activities Index, physical illness and sociodemographic data were collected. Post-stroke depression (PSD) included both major depression and minor depression (dysthymia without the 2-year time stipulation) according to DSM-III (American Psychiatric Association) criteria. Patients depressed at the time of the stroke were excluded. Patients. 191 first-ever stroke patients, 111M, 80F, 28% had PSD, 17% major and 11% minor depression. Results. Significant associations with PSD at 4 months were major functional impairment, living in a nursing home, being divorced and having a high pre-stroke alcohol intake (M only). There was no significant association with age, sex, social class, cognitive impairment or pre-stroke physical illness. Conclusion. Results favoured the hypothesis that depression in an unselected group of stroke patients is no more common, and of no more specific aetiology, than it is among elderly patients with other physical illness.
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Background: Although depression appears to decrease in late life, this could be due to misattribution of depressive symptoms to physical disorders that increase in late we. Methods: We investigated this issue by studying age differences in co-morbidity of DSM-IV major depressive episodes (MDE) with chronic physical conditions in the WHO World Mental Health (WMH) surveys, a series of community epidemiological surveys of respondents in 10 developed countries (n = 52,485) and 8 developing countries (n = 37,265). MDE and other mental disorders were assessed with the Composite International Diagnostic Interview (CIDI). Organic exclusion rules were not used to avoid inappropriate exclusion of cases with physical co-morbidity. Physical conditions were assessed with a standard chronic conditions checklist. Results: Twelve-month DSM-IV/CIDI MDE was significantly less prevalent among respondents ages 65+ than younger respondents in developed but not developing countries. Prevalence of co-morbid mental disorders generally either decreased or remained stable with age, while co-morbidity of MDE with mental disorders generally increased with age. Prevalence of physical conditions, in comparison, generally increased with age, while co-morbidity of MDE with physical conditions generally decreased with age. Depression treatment was lowest among the elderly in developed and developing countries. Conclusions: The weakening associations between MDE and physical conditions with increasing age argue against the suggestion that the low estimated prevalence of MDE among the elderly is due to increased confounding with physical disorders. Future study is needed to investigate processes that might lead to a decreasing impact of physical illness on depression among the elderly. Depression and Anxiety 27:351-364, 2010. (C) 2009 Wiley-Liss, Inc.
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The study aimed to elucidate electrophysiological and cortical mechanisms involved in anticipatory actions when healthy subjects had to catch balls in free drop. Specific alpha absolute power changes were measured in quantitative electroencephalography (qEEG). Our hypothesis is that during the preparation of motoraction (i.e.. 2 s before the ball drops) integration occurs among the left medial frontal, left primary somatomotor and left posterior parietal cortices, showing a differentiated activity involving expectation, planning and preparedness. We contend that in right-handers, the left hemisphere takes on a dominant role for the regulation of motor behavior. The sample was composed of 23 healthy right handed subjects (13 men and 10 women), with ages varying between 25 and 40 years old (32.5 +/- 7.5), absence of mental and physical illness. The experiment consisted of a task of catching balls with the right hard in free drop. The three-way ANOVA analysis demonstrated all interaction between moment and position in left-medial frontal cortex (F3 electrode), somatomotor cortex (C3 electrode) and posterior parietal cortex (P3 electrode: p < 0.05). Summarizing, the experimental task enabled the observation of integration among frontal, central and parietal regions. This integration appears to be more predominant in expectation, planning and motor preparation.
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The study aimed to elucidate electrophysiological and cortical mechanisms involved in anticipatory actions when healthy subjects had to catch balls in free drop; specifically through quantitative electroencephalography (qEEG) alpha absolute power changes. Our hypothesis is that during the preparation of motor action (i.e., 2 s before ball`s drop) occurred integration among left medial frontal, left primary somatomotor and left posterior parietal cortices, showing a differentiated activity involving expectation, planning and preparedness. This hypothesis supports a lateralization of motor function. Although we contend that in right-handers the left hemisphere takes on a dominant role for the regulation of motor behavior. The sample was composed of 23 healthy subjects (13 male and 10 female), right handed, with ages varying between 25 and 40 years old (32.5 +/- 7.5), absence of mental and physical illness, right handed, and do not make use of any psychoactive or psychotropic substance at the time of the study. The experiment consisted of a task of catching balls in free drop. The three-way ANOVA analysis demonstrated an interaction between moment and position in left medial frontal cortex (F3 electrode), somatomotor cortex (C3 electrode) and posterior parietal cortex (P3 electrode: p < 0.001). Summarizing, through experimental task employed, it was possible to observe integration among frontal, central and parietal regions. This integration appears to be more predominant in expectation, planning and motor preparation. In this way, it established an absolute predominance of this mechanism under the left hemisphere. (C) 2008 Elsevier Ireland Ltd. All rights reserved.
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Background:The aging process promotes a progressive increase in chronic-degenerative diseases. The effect of these diseases on the functional capacity has been well recognized. Another health parameter concerns “quality of life related to health”. Among the elderly population, cardiovascular diseases stand out due to the epidemiological and clinical impact. Usually, these diseases have been associated with others. This set of problems may compromise both independence and quality of life in elderly patients who seek cardiologic treatment. These health parameters have not been well contemplated by cardiologists.Objective:Evaluating, among the elderly population with cardiovascular disease, which are the most relevant clinical determinants regarding dependence and quality of life.Methods:This group was randomly and consecutively selected and four questionnaires were applied: HAQ, SF-36, PRIME-MD e Mini Mental State.Results:The study included 1,020 elderly patients, 63.3% women. The group had been between 60 and 97 years-old (mean: 75.56 ± 6.62 years-old). 61.4% were independent or mild dependence. The quality of life total score was high (HAQ: 88.66 ± 2.68). 87.8% of patients had a SF-36 total score > 66. In the multivariate analysis, the association between diagnoses and high degrees of dependence was significant only for previous stroke (p = 0.014), obesity (p < 0.001), lack of physical activity (p = 0.016), osteoarthritis (p < 0.001), cognitive impairment (p < 0.001), and major depression (p < 0.001). Analyzing the quality of life, major depression and physical illness for depression was significantly associated with all domains of the SF-36.Conclusion:Among an elderly outpatient cardiology population, dependence and quality of life clinical determinants are not cardiovascular comorbidities, especially the depression.
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OBJECTIVES: Beyond its well-documented association with depressive symptoms across the lifespan, at an individual level, quality of life may be determined by multiple factors: psychosocial characteristics, current physical health and long-term personality traits. METHOD: Quality of life was assessed in two distinct community-based age groups (89 young adults aged 36.2 ± 6.3 and 92 older adults aged 70.4 ± 5.5 years), each group equally including adults with and without acute depressive symptoms. Regression models were applied to explore the association between quality of life assessed with the World Health Organization Quality of Life - Bref (WHOQOL-Bref) and depression severity, education, social support, physical illness, as well as personality dimensions as defined by the Five-Factor Model. RESULTS: In young age, higher quality of life was uniquely associated with lower severity of depressive symptoms. In contrast, in old age, higher quality of life was related to both lower levels of depressive mood and of physical illness. In this age group, a positive association was also found between quality of life and higher levels of Openness to experience and Agreeableness personality dimensions. CONCLUSION: Our data indicated that, in contrast to young cohorts, where acute depression is the main determinant of poor quality of life, physical illness and personality dimensions represent additional independent predictors of this variable in old age. This observation points to the need for concomitant consideration of physical and psychological determinants of quality of life in old age.
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Making the links between Obesity & Well-being. A briefing paper developed for Care Services Improvement Partnership (CSIP) North West. The paper covers the epidemiology and evidence of links between health and obesity. Mental well-being is a key factor of obesity and weight management. Good mental health is a protective factor for good physical health and against physical illness and is essential for making healthy lifestyle choices and behaviour changes. Poor mental health can lead to unhealthy lifestyle choices and unhealthy weight management. Obesity and physical illness can also lead to poor mental health. People with mental health problems, especially severe, are also at increased risk of obesity and related poor health. In order to ensure that strategies and programmes effectively address the relevant mental well-being factors, a mental well-being impact assessment (MWIA) could be undertaken. This process is based on health impact assessment methodology and a set of evidence based mental well-being determinants and factors, grouped under the four themes of enhancing control, increasing resilience and community assets, facilitating participation and promoting inclusion. The process also involves identifying indicators to measure progress. Evaluation shows it is effective in engaging stakeholders in service development and evaluation and it increases understanding of mental well-being and its determinants.
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BACKGROUND: Depression is highly prevalent in patients with physical illness and is associated with a diminished quality of life and poorer medical outcomes. OBJECTIVE: The authors evaluated whether a multifaceted intervention conducted by a psychiatric consultation-liaison nurse could reduce the incidence of major depression in rheumatology inpatients and diabetes outpatients with a high level of case complexity. METHOD: Of 247 randomized patients, the authors identified 100 patients with a high level of case complexity at baseline and without major depression (65 rheumatology and 35 diabetes patients). Patients were randomized to usual care (N=53) or to a nurse-led intervention (N=47). Main outcomes were the incidence of major depression and severity of depressive symptoms during a 1-year follow-up, based on quarterly assessments with standardized psychiatric interviews. RESULTS: The incidence of major depression was 63% in usual-care patients and 36% in the intervention group. Effects of intervention on depressive symptoms were observed in outpatients with diabetes but not in rheumatology inpatients. CONCLUSION: These preliminary results based on subgroup analysis suggest that a multifaceted nurse-led intervention may prevent the occurrence of major depression in complex medically ill patients and reduce depressive symptoms in diabetes outpatients.
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Using Dutch data (N = 6630), this article examines how sibling relationships (including full biological, half- and adopted siblings) differed for persons who experienced a negative life event (divorce, physical illness, psychological problems, addiction, problems with the law, victimization of abuse or financial problems) and those who did not. Results showed that people who experienced serious negative life events in the past often had less active, less supportive and more strained sibling ties. The group that experienced a physical illness formed an exception, showing more supportive and active sibling ties, but also higher levels of conflict. Results suggest inequality between persons who have experienced negative life events and those who have not in terms of access to positive and supportive sibling relationships.
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BACKGROUND: The occurrence of depression in younger adults is related to the combination of long-standing factors such as personality traits (neuroticism) and more acute factors such as the subjective impact of stressful life events. Whether an increase in physical illnesses changes these associations in old age depression remains a matter of debate. METHODS: We compared 79 outpatients with major depression and 102 never-depressed controls; subjects included both young (mean age: 35 years) and older (mean age: 70 years) adults. Assessments included the Social Readjustment Rating Scale, NEO Personality Inventory and Cumulative Illness Rating Scale. Logistic regression models analyzed the association between depression and subjective impact of stressful life events while controlling for neuroticism and physical illness. RESULTS: Patients and controls experienced the same number of stressful life events in the past 12 months. However, in contrast to the controls, patients associated the events with a subjective negative emotional impact. Negative stress impact and levels of neuroticism, but not physical illness, significantly predicted depression in young age. In old age, negative stress impact was weakly associated with depression. In this age group, depressive illness was also determined by physical illness burden and neuroticism. CONCLUSIONS: Our data suggest that the subjective impact of life stressors, although rated as of the same magnitude, plays a less important role in accounting for depression in older age compared to young age. They also indicate an increasing weight of physical illness burden in the prediction of depression occurrence in old age.