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.
Understanding the burden and pattern of mental disorders as well as mapping the existing resources for delivery of mental health services in India, has been a felt need over decades. Recognizing this necessity, the Ministry of Health and Family Welfare, Government of India, commissioned the National Mental Health Survey (NMHS) in the year 2014–15. The NMHS aimed to estimate the prevalence and burden of mental health disorders in India and identify current treatment gaps, existing patterns of health-care seeking, service utilization patterns, along with an understanding of the impact and disability due to these disorders. This paper describes the design, steps and the methodology adopted for phase 1 of the NMHS conducted in India. The NMHS phase 1 covered a representative population of 39,532 from 12 states across 6 regions of India, namely, the states of Punjab and Uttar Pradesh (North); Tamil Nadu and Kerala (South); Jharkhand and West Bengal (East); Rajasthan and Gujarat (West); Madhya Pradesh and Chhattisgarh (Central) and Assam and Manipur (North East). The NMHS of India (2015–16) is a unique representative survey which adopted a uniform and standardized methodology which sought to overcome limitations of previous surveys. It employed a multi-stage, stratified, random cluster sampling technique, with random selection of clusters based on Probability Proportionate to Size. It was expected that the findings from the NMHS 2015–16 would reveal the burden of mental disorders, the magnitude of the treatment gap, existing challenges and prevailing barriers in the mental-health delivery systems in the country at a single point in time. It is hoped that the results of NMHS will provide the evidence to strengthen and implement mental health policies and programs in the near future and provide the rationale to enhance investment in mental health care in India. It is also hoped that the NMHS will provide a framework for conducting similar population based surveys on mental health and other public health problems in low and middle-income countries.
ObjectivesThe National Mental Health Survey (NMHS) of India was undertaken with the objectives of (1) estimating the prevalence and patterns of various mental disorders in representative Indian population and (2) identifying the treatment gap, healthcare utilisation, disabilities and impact of mental disorders. This paper highlights findings pertaining to depressive disorders (DD) from the NMHS.DesignMultisite population-based cross-sectional study. Subjects were selected by multistage stratified random cluster sampling technique with random selection based on probability proportionate to size at each stage.SettingConducted across 12 states in India (representing varied cultural and geographical diversity), employing uniform, standardised and robust methodology.ParticipantsA total of 34 802 adults (>18 years) were interviewed.Main outcome measurePrevalence of depressive disorders (ICD-10 DCR) diagnosed using Mini International Neuropsychiatric Interview V.6.0.ResultsThe weighted prevalence of lifetime and current DD was 5.25% (95% CI: 5.21% to 5.29%, n=34 802) and 2.68% (95% CI: 2.65% to 2.71%, n=34 802), respectively. Prevalence was highest in the 40–59 age groups (3.6%, n=10 302), among females (3.0%, n=18 217) and those residing in cities with population >1 million (5.2%, n=4244). Age, gender, place of residence, education and household income were found to be significantly associated with current DD. Nearly two-thirds of individuals with DD reported disability of varying severity, and the treatment gap for depression in the study population was 79.1%. On an average, households spent INR1500/month (~US$ 23.0/month) towards care of persons affected with DD.ConclusionAround 23 million adults would need care for DD in India at any given time. Since productive population is affected most, DD entails considerable socioeconomic impact at individual and family levels. This is a clarion call for all the concerned stakeholders to scale up services under National Mental Health Programme in India along with integrating care for DD with other ongoing national health programmes.
Depression in old age is associated with genetic susceptibility, chronic disease and disability, pain, frustration with limitations in activities of daily living. The present hospital based cross sectional study was undertaken on 306 patients selected by systemic consecutive sampling from Geriatric O.P.D of Institute of Psychiatry, Kolkata to find out the prevalence of depression and associated factors among geriatric patients. 65.3% of the study population had depression (mild-36.2%, severe-29.1%) and the association of this depression with age (p<.001), gender (p<.001), residence (p=.027), marital status (p=.004), education (p<.001), occupation (p<.001), family type (p<.001) and economic dependency (p=.002), living condition (p<.001) was statistically significant. Social support group, local clubs and respective families should address the issue of depression among elderly. Family counselling for old age care, creation of a viable family and social environment will go a long way to improve the mental health of the elderly.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.