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Copy number variants (CNVs) of 15q11.2 yielded conflicting reports on their association with schizophrenia (SZ), indicating the need for replication studies. Because there are no 15q11.2 CNV studies on Indian patients, we began by testing 307 SZ patients and 359 age- and sex-matched controls from South India. Using an improved multiplex ligation probe amplification, six deletions were found in patients and three in controls (p = 0.31), whereas one duplication was found in patients and three in controls (p = 0.63). Analysis of families of two patients and two controls with deletions indicated that the mutations were de novo. In conclusion, there seems to be no significant difference in the frequencies of 15q11.2 CNVs among the controls and patients studied here. Future studies involving a larger number of controls and patients are expected to provide better clarity on the relationship between 15q11.2 CNVs and SZ patients from India.
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Cromosomas Humanos Par 15/genética , Variaciones en el Número de Copia de ADN , Esquizofrenia/genética , Eliminación de Secuencia , Estudios de Casos y Controles , Humanos , IndiaRESUMEN
BACKGROUND: Obstructive sleep apnea (OSA) and depression may coexist in the same patient. This article aims to review the link between OSA and comorbid depression and critically evaluate the results of studies that assessed the correlation between OSA and depression, the impact of OSA treatment on comorbid depression, and the impact of comorbid depression on continuous positive airway pressure (CPAP) adherence. METHODS: An integrative review was conducted on English language studies and reports that assessed the relationship between OSA and depression. Studies were identified by searching PubMed, Web of Science and Google Scholar databases, and reference lists of included studies. RESULTS: Generally, cross-sectional studies show a higher prevalence of depression among OSA patients with both community and sleep disorder clinic samples. Nevertheless, the relationship between OSA and depression is complicated by the fact that the disorders have overlapping symptoms. Longitudinal studies demonstrate an increased risk of developing depression among people with OSA, as well as an association between OSA severity and the likelihood of developing depression. On the other hand, studies assessing the impact of CPAP therapy on depression among OSA patients report conflicting results. Therefore, it is essential to consider how the disorders affect one another and to understand the clinical consequences of treating each disorder in isolation. CONCLUSION: Depression is prevalent among patients with OSA both in the community and in sleep disorder clinics. Clinicians in general should be aware of this significant association and should aim to treat both disorders.
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Trastorno Depresivo/diagnóstico , Trastorno Depresivo/epidemiología , Apnea Obstructiva del Sueño/diagnóstico , Apnea Obstructiva del Sueño/epidemiología , Comorbilidad , Presión de las Vías Aéreas Positiva Contínua/psicología , Estudios Transversales , Trastorno Depresivo/psicología , Trastorno Depresivo/terapia , Humanos , Estudios Longitudinales , Cooperación del Paciente/psicología , Factores de Riesgo , Apnea Obstructiva del Sueño/psicología , Apnea Obstructiva del Sueño/terapia , Estadística como AsuntoRESUMEN
Copy number variants (CNVs) are among the main genetic factors identified in schizophrenia (SZ) through genome-scale studies conducted mostly in Caucasian populations. However, to date, there have been no genome-scale CNV reports on patients from India. To address this shortcoming, we generated, for the first time, genome-scale CNV data for 168 SZ patients and 168 controls from South India. In total, 63 different CNVs were identified in 56 patients and 46 controls with a significantly higher proportion of medium-sized deletions (100 kb-1 Mb) after multiple testing (FDR = 2.7E-4) in patients. Of these, 13 CNVs were previously reported; however, when searched against GWAS, transcriptome, exome, and DNA methylation studies, another 17 CNVs with candidate genes were identified. Of the total 30 CNVs, 28 were present in 38 patients and 12 in 27 controls, indicating a significantly higher representation in the former (p = 1.87E-5). Only 4q35.1-q35.2 duplications were significant (p = 0.020) and observed in 11 controls and 2 patients. Among the others that are not significant, a few examples of patient-specific and previously reported CNVs include deletions of 11q14.1 (DLG2), 22q11.21, and 14q21.1 (LRFN5). 16p13.3 deletion (RBFOX1), 3p14.2 duplication (CADPS), and 7p11.2 duplication (CCT6A) were some of the novel CNVs containing candidate genes. However, these observations need to be replicated in a larger sample size. In conclusion, this report constitutes an important foundation for future CNV studies in a relatively unexplored population. In addition, the data indicate that there are advantages in using an integrated approach for better identification of candidate CNVs for SZ and other mental health disorders.
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Background: Existing psychiatric epidemiological studies from Tamil Nadu with methodological limitations and variations had under-reported the prevalence of mental morbidity. Robust data from a representative population-based epidemiological study are not readily available to guide mental health programs in Tamil Nadu. Aim: This study aimed to estimate the prevalence, correlates, and treatment gap of mental morbidity in the state of Tamil Nadu using data from National Mental Health Survey (NMHS) of India, 2015-2016. Materials and Methods: NMHS in Tamil Nadu was conducted in 60 clusters of 4 districts (Trichy, Tirunelveli, Thoothukudi, and Namakkal) using a door-to-door survey and multistage sampling proportionate to rural, urban nonmetro, and urban metro population. Mini-International Neuropsychiatric Interview (M.I.N.I version 6) and Fagerstrom nicotine dependence scale were administered on a representative adult (aged ≥18 years) sample to assess the mental morbidity. Prevalence and 95% confidence intervals (CIs) were estimated after weighing the sample for survey design. Results: A total of 3059 adults from 1069 households were interviewed. The overall weighted prevalence of lifetime and current mental morbidity was 19.3% (95% CI: 19.0%-19.6%) and 11.8% (95% CI: 11.6%-12.0%) respectively. Participants who were men (largely contributed by substance-use disorders), aged 40-49 years, from rural areas, and from lower income quintile had higher prevalence of mental morbidity. The treatment gap was 94.2% for any mental health problem. Common mental disorders (depression, anxiety, and substance-use) accounted for most of the morbidity. Conclusion: The burden and treatment gap for mental health morbidity is high in Tamil Nadu. The findings call for urgent policy level and systemic action to strengthen mental health program in Tamil Nadu.
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The ongoing wars in many regions-such as the conflict between Israel and Hamas-as well as the effects of war on communities, social services, and mental health are covered in this special editorial. This article emphasizes the need for international efforts to promote peace, offer humanitarian aid, and address the mental health challenges faced by individuals and communities affected by war and violence.
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Aim: To study the sociodemographic and clinical profile of subjects receiving disability certificates (DCs) issued for psychiatric disorders across multiple centres in India. Materials and Methods: Eleven centres, including ten government and one non-governmental organization spread across the country, participated in the study. Data on the sociodemographic and clinical profiles of patients who were issued DC in the calendar year 2019 were collected on a proforma designed for the study. Results: Overall, 2018 patients were issued DC for various psychiatric disorders across 11 centres in 2019. The number of certificates issued across different centres varied from 34 to 622. In terms of diagnostic profile, intellectual disability accounted for most of the certificates issued. In terms of psychiatric diagnosis, schizophrenia was the most common psychiatric diagnosis, followed by bipolar disorder, for which a DC was issued. When the diagnosis was considered, centre wise, intellectual disability (6 centres), mental illness (MI; 4 centres), and autism and specific learning disability (1 centre) accounted for the most DCs issued. Schizophrenia (9 centres), bipolar affective disorder (1 centre), and dementia (1 centre) were the most common MI for which DC was issued. Across centres, more than two-thirds of DC were issued to males. Conclusion: There is a wide variation in the number and clinical profile of DC issued across centres.
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Some research suggests that distress, secondary to isolation and fear following COVID-19 infection, can negatively affect the long-term more than the COVID-19 infection itself. This narrative review aims to provide a global view on the neuropsychiatric consequences of COVID-19 that can be ascribed to several factors, ranging from the direct effect of infection, to the body's responses against the infection, or to the psychological sequelae of social isolation, unemployment, and fear for one's health and livelihood. Current findings show that the more severe the respiratory infection, the more likely are central nervous system (CNS) complications regarding the infection itself. The immune reactions to the infection may result in symptoms similar to chronic fatigue as well as neurocognitive deficits, which last long after the infection is gone. An increase in symptoms of depression, anxiety, and trauma-related stress may also follow upon economic fears and isolation from friends and family. The consequences of the pandemic are not limited to adults; children learning remotely and away from classmates and routine activities may develop adjustment disorders, acute stress disorder, and a variety of manifestations of grief. A summary of case reports suggests that COVID-19-related stress, economic recession, and political unrest increase the risk of suicidal behaviors and acts of violence. However, it is unknown whether manifestations of mental disorders result from social causes or whether CNS complications may be responsible.
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Social distancing, also referred to as physical distancing, means creating a safe distance of at least two meters (six feet) between yourself and others. This is a term popularized during the COVID-19 pandemic, as it is one of the most important measures to prevent the spread of this virus. However, the term 'social distancing' can be misleading, as it may imply that individuals should stop socializing. However, socializing in a safe context (i.e. over the phone, video-chat, etc.) is especially important during this time of crisis. Therefore, in this narrative review, we suggest the term 'distant socializing' as more apt expression, to promote physical distancing measures while also highlighting the importance of maintaining social bonds. Further, articles discussing the practice, implementation, measurement, and mental health effects of physical distancing are reviewed. Physical distancing is associated with psychiatric symptoms (such as anxiety and depression), suicidal ideation, and domestic violence. Further, unemployment and job insecurity have significantly increased during COVID-19, which may exacerbate these negative mental health effects. Governments, medical institutions, and public health bodies should therefore consider increasing mental health resources both during and after the pandemic, with a specific focus on frontline workers, COVID-19 survivors, and marginalized communities.
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COVID-19 , Pandemias , Humanos , Distanciamiento Físico , Salud Pública , SARS-CoV-2RESUMEN
BACKGROUND: Recognizing the need for good quality, scientific and reliable information for strengthening mental health policies and programmes, the National Mental Health Survey (NMHS) of India was implemented by National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, in the year 2015-2016. AIM: To estimate the prevalence, socio-demographic correlates and treatment gap of mental morbidity in a representative population of India. METHODS: NMHS was conducted across 12 Indian states where trained field investigators completed 34,802 interviews using tablet-assisted personal interviews. Eligible study subjects (18+ years) in households were selected by a multi-stage, stratified, random cluster sampling technique. Mental morbidity was assessed using MINI 6. Three-tier data monitoring system was adopted for quality assurance. Weighted and specific prevalence estimates were derived (current and lifetime) for different mental disorders. Mental morbidity was defined as those disorders as per the International Statistical Classification of Diseases, Tenth Revision Diagnostic Criteria for Research (ICD-10 DCR). Multivariate logistic regression was conducted to examine risk for mental morbidity by different socio-demographic factors. Survey was approved by central and state-level institutional ethical committees. RESULTS: The weighted lifetime prevalence of 'any mental morbidity' was estimated at 13.67% (95% confidence interval (CI) = 13.61, 13.73) and current prevalence was 10.56% (95% CI = 10.51, 10.61). Mental and behavioural problems due to psychoactive substance use (F10-F19; 22.44%), mood disorders (F30-F39; 5.61%) and neurotic and stress-related disorders (F40-F48; 3.70%) were the most commonly prevalent mental morbidity in India. The overall prevalence was estimated to be higher among males, middle-aged individuals, in urban-metros, among less educated and in households with lower income. Treatment gap for overall mental morbidity was 84.5%. CONCLUSION: NMHS is the largest reported survey of mental morbidity in India. Survey estimated that nearly 150 million individuals suffer from one or the other mental morbidity in India. This information is to be used for planning, delivery and evaluating mental health programming in the country.
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Encuestas Epidemiológicas , Salud Mental , Adulto , Femenino , Humanos , India/epidemiología , Modelos Logísticos , Masculino , Trastornos Mentales/epidemiología , Trastornos Mentales/terapia , Persona de Mediana Edad , Análisis Multivariante , Prevalencia , Factores Socioeconómicos , Adulto JovenRESUMEN
BACKGROUND: India accounts for 18% of the global population and 26·6% of global suicide deaths. However, robust population-based, nationally representative data on suicidality are not readily available to plan and implement suicide prevention programmes in India. We aimed to investigate the prevalence and sociodemographic differentials of suicidality using data from the National Mental Health Survey (NMHS) of India, 2015-16. METHODS: Trained field data collectors from the NMHS obtained information on suicidality (during the past month) from a community sample of adults aged 18 years and older using the suicidality module of the Mini-International Neuropsychiatric Interview (version 6.0). Suicidality was categorised as low, moderate, high, and overall (representing any suicidality), and examined for sociodemographic differentials using normalised sampling weights. For each of the 12 surveyed states, we calculated the age-standardised suicidality prevalence for men and women, men-to-women ratio of weighted suicidality prevalence, ratio of suicidality to suicide deaths, and ratio of suicide attempts to suicide deaths. We used logistic regression analysis to examine the association between sociodemographic factors and overall suicidality and severity. FINDINGS: Among 34â748 participants with complete interviews, 5·1% (95% CI 4·7-5·6) had some level of suicidality, and 0·3% (0·2-0·4) had at least one suicide attempt in the past month. The prevalence of overall suicidality was higher in women (6·0% [5·4-6·6]) than in men (4·1% [3·7-4·6]). The prevalence of overall suicidality was highest in those aged 40-49 years among women and in those aged 60 years or older among men. Compared with their counterparts, individuals with lower educational attainment, individuals residing in urban metropolitan cities, individuals who were widowed, separated, or divorced, and unemployed individuals had a higher prevalence of overall suicidality. The men-to-women ratio of overall suicidality prevalence for India was 0·68 (range 0·55-0·85). For every death by suicide in India, there were more than 200 people with suicidality and more than 15 suicide attempts. We found variations for various severities of suicidality. We found an increased risk for overall suicidality in women versus men (odds ratio [OR] 1·54 [95% CI 1·31-1·81]; p<0·0001) and in individuals residing in urban metropolitan cities versus those residing in rural areas (1·75 [1·30-2·35]; p=0·0002). Individuals belonging to the lowest income quintile (reference group with OR <1·00 and p<0·05 for other income quintiles), those with depressive disorders (28·78 [20·04-41·33]; p<0.0001) and those with alcohol use disorders (6·52 [3·83-11·10]; p<0.0001) had an increased risk for high suicidality, compared with their corresponding counterparts. INTERPRETATION: A national suicide prevention strategy that is comprehensive, using multisectoral approaches, is required to address the prevailing sociodemographic and other risk factors for reducing suicidality and suicide deaths in India. This study also has implications for other low-income and middle-income countries in south Asia, where sociodemographic factors play a crucial role for suicide prevention. FUNDING: Ministry of Health and Family Welfare, Government of India.
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Alcoholismo/epidemiología , Trastorno Depresivo/epidemiología , Intento de Suicidio/estadística & datos numéricos , Adulto , Anciano , Femenino , Encuestas Epidemiológicas , Humanos , India/epidemiología , Masculino , Persona de Mediana Edad , Prevalencia , Factores SocioeconómicosRESUMEN
INTRODUCTION: The employment status of mentally ill patients is a reflection of their productivity, control of illness besides providing therapeutic benefits and integration into mainstream society. Owing to the associated stigma, self-reporting of mental illness (SRMI) often is rare. Census exercise of India in 2011 provides an insight of SRMI and employment status of such people. This study was undertaken to consider the role of gender, age group, and place on the employment status of SRMI. METHODOLOGY: Frequency of SRMI, age group, gender, and employment status was gathered from Indian 2011 census sources. Descriptive statistics and logistic regression were employed. P ≤ 0.05 was taken as significant. RESULTS: Majority (68.6%) of the SRMI people resides in rural areas, in the economically productive age group of 15-59 years (75.88%) and often males (57.51%). Of the SRMI as reported in the data, 78.62% were not employed while 2.4% of them were currently employed. The employability frequency distributions of SMRIs were statistically different in terms of area, age group, and gender with significance. DISCUSSION: Although the mental illness data of 2011 census was rejected by mental health professionals citing discrepancy and underestimating of the prevalence of mental illness, it provides a robust estimate of the employability, self-reporting tendency of mental illness. The association of the factors provides a unique insight into SRMIs in India. CONCLUSION: Understanding the interplay of factors may yield robust estimates and clues for policy framers to formulate employment-related policies for employment opportunities for mentally ill patients.
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This review introduces a conceptual framework for understanding stakeholder management (ShM) in the clinical and community-based research environment. In recent years, an evolution in practice has occurred in many applicants for public and non-governmental funding of public health research in hospital settings. Community health research projects are inherently complex, have sought to involve patients and other stakeholders in the center of the research process. Substantial evidence has now been provided that stakeholder involvement is essential for management effectiveness in clinical research. Feedback from stakeholders has critical value for research managers inasmuch as it alerts them to the social, environmental, and ethical implications of research activities. Additionally, those who are directly affected by program development and clinical research, the patients, their families, and others, almost universally have a strong motivation to be involved in the planning and execution of new program changes. The current overview introduces a conceptual framework for ShM in the clinical research environment and offers practical suggestions for fostering meaningful stakeholder engagement. The fifth edition of PMBOK(®) of the Project Management Institute, has served as basis for many of the suggested guidelines that are put forward in this article.
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BACKGROUND: Sleep-wake disturbances have frequently been reported in bipolar disorder and schizophrenia, and are considered to be caused by an underlying circadian rhythm disorder. The study presented here was designed to investigate the existence of Per3 polymorphism in bipolar disorder type I (BD-I) and schizophrenic patients in South India. METHODS: Blood samples were collected from 311 BD-I patients, 293 schizophrenia patients, and 346 age- and sex-matched normal controls. Per3 genotyping was performed on DNA by polymerase chain reaction using specific primers. RESULTS: An increased prevalence of five repeat homozygotes was seen in BD-I patients as compared with healthy controls (odds ratio =1.72 [95% confidence interval: 1.08-2.76, P=0.02]). In BD-I patients, the frequency of the five repeat allele was higher (allele frequency =0.41), and that of the four repeat allele lower (allele frequency =0.36) (χ (2)=4.634; P<0.03) than in the control group. No significant association was observed in the allele frequencies of four and five repeat alleles in schizophrenia patients when compared with controls. CONCLUSION: The occurrence of the five repeat allele of Per3 may be a risk factor for BD-I onset in this ethnic group.
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Recent scientific evidences have brought a paradigm shift in our approach towards the concepts of insomnia and its management. The differentiation between primary and secondary insomnia was proved more hypothetical than actual and based upon the current evidences insomnia subtypes described in earlier system have been lumped into one-insomnia disorder. Research in this field suggests that insomnia occurring during psychiatric or medical disorders has a bidirectional and interactive relationship with and coexisting medical and psychiatric illnesses. The new approach looks to coexist psychiatric or medical disorders as comorbid conditions and hence specifies two coexisting conditions. Therefore, the management and treatment plans should address both the conditions. A number of sleep disorders may present with insomnia like symptoms and these disorders should be treated efficiently in order to alleviate insomnia symptoms. In such cases, a thorough history from the patient and his/her bed-partner is warranted. Moreover, some patients may need polysomnography or other diagnostic tests like actigraphy to confirm the diagnosis of the underlying sleep disorder. DSM-5 classification system of sleepwake disorders has several advantages, e.g., it has seen insomnia across different dimensions to make it clinically more useful; it focuses on the assessment of severity and guides the mental health professional when to refer a patient of insomnia to a sleep specialist; lastly, it may encourage the psychiatrists to opt for sleep medicine as a career.
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Manual Diagnóstico y Estadístico de los Trastornos Mentales , Trastornos del Sueño-Vigilia/diagnóstico , Sueño , Diagnóstico Diferencial , Humanos , Polisomnografía , Trastornos del Sueño-Vigilia/clasificación , Trastornos del Sueño-Vigilia/etiologíaRESUMEN
The Ministry of Health and Family Welfare and its public health institutes are collaborating with Asia Australia Mental Health on an innovative community mental health development project designed to enhance initiatives under the District Mental Health Program and increase accessibility of essential community mental health services. The project is an exciting opportunity to create positive change in meeting the challenges of community mental health care in India. It recognizes that no one single model of care can be applied to all the community in the country and that locally appropriate models working in close partnership with local communities is required. Targeted and skill-based training programs are useful to build local leadership capacity in implementing quality and culturally appropriate community mental health services.