Prevalence of Depression in a Large Urban South Indian Population — The Chennai Urban Rural Epidemiology Study (Cures – 70)

BACKGROUND: In India there are very few population based data on prevalence of depression. The aim of the study was to determine the prevalence of depression in an urban south Indian population. METHODS AND FINDINGS: Subjects were recruited from the Chennai Urban Rural Epidemiology Study (CURES), involving 26,001 subjects randomly recruited from 46 of the 155 corporation wards of Chennai (formerly Madras) city in South India. 25,455 subjects participated in this study (response rate 97.9%). Depression was assessed using a self-reported and previously validated instrument, the Patient Health Questionnaire (PHQ) - 12. Age adjustment was made according to the 2001 census of India. The overall prevalence of depression was 15.1% (age-adjusted, 15.9%) and was higher in females (females 16.3% vs. males 13.9%, p<0.0001). The odds ratio (OR) for depression in female subjects was 1.20 [Confidence Intervals (CI): 1.12-1.28, p<0.001] compared to male subjects. Depressed mood was the most common symptom (30.8%), followed by tiredness (30.0%) while more severe symptoms such as suicidal thoughts (12.4%) and speech and motor retardation (12.4%) were less common. There was an increasing trend in the prevalence of depression with age among both female (p<0.001) and male subjects (p<0.001). The prevalence of depression was higher in the low income group (19.3%) compared to the higher income group (5.9%, p<0.001). Prevalence of depression was also higher among divorced (26.5%) and widowed (20%) compared to currently married subjects (15.4%, p<0.001). CONCLUSIONS: This is the largest population-based study from India to report on prevalence of depression and shows that among urban south Indians, the prevalence of depression was 15.1%. Age, female gender and lower socio-economic status are some of the factors associated with depression in this population

Understanding the explanatory model of the patient on their medically unexplained symptoms and its implication on treatment development research: a Sri Lanka Study

<p>Abstract</p> <p>Background</p> <p>Patients with medically unexplained symptoms (MUS) are often distressed, disabled and dissatisfied with the care they receive. Illness beliefs held by patients have a major influence on the decision to consult, persistence of symptoms and the degree of disability. Illness perception models consist of frameworks to organise information from multiple sources into distinct but interrelated dimensions: identity (the illness label), cause, consequences, emotional representations perceived control and timeline.</p> <p>Our aim was to elicit the illness perceptions of patients with MUS in Sri Lankan primary care to modify and improve a CBT intervention.</p> <p>Method</p> <p>An intervention study was conducted in a hospital primary care clinic in Colombo, Sri Lanka using CBT for MUS. As a part of the baseline assessment, qualitative data was collected using; the Short Explanatory Model Interview (SEMI), from 68 patients (16–65 years) with MUS. We categorised the qualitative data in to key components of the illness perception model, to refine CBT intervention for a subsequent larger trial study.</p> <p>Results</p> <p>The cohort was chronically ill and 87% of the patients were ill for more than six months (range six months to 20 years) with 5 or more symptoms and 6 or more visits over preceding six months. A majority were unable to offer an explanation on identity (59%) or the cause (56%), but in the consequence domain 95% expressed significant illness worries; 37% believed their symptoms indicated moderately serious illness and 58% very serious illness. Reflecting emotional representation, 33% reported fear of death, 20% fear of paralysis, 13% fear of developing cancer and the rest unspecified incurable illness. Consequence and emotional domains were significant determinants of distress and consultations. Their repeated visits were to seek help to alleviate symptoms. Only a minority expected investigations (8.8 %) or diagnosis (8.8%). However, the doctors who had previously treated them allegedly concentrated more on identity than cause. The above information was used to develop simple techniques incorporating analogies to alter their perceptions</p> <p>Conclusion</p> <p>The illness perception model is useful in understanding the continued distress of patients with persistent symptoms without an underlying organic cause. Hence it can make a significant contribution when developing and evaluating culturally sensitive patient friendly interventions.</p

Preclinical carotid atherosclerosis in patients with latent autoimmune diabetes in adults (LADA), type 2 diabetes and classical type 1 diabetes

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This project was funded by Grants Nos. PI12/00183 and PI15/00625, both included in Plan Nacional de I + D + I, and co-financed by Instituto de Salud Carlos III, Subdireccion General de Evaluacion, Ministry of Economy and Competitiveness, and Fondo Europeo de Desarrollo Regional (FEDER). CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM) is an initiative from Instituto de Salud Carlos III, Spain

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer