The National Mental Health Survey of India (2016): Prevalence, socio-demographic correlates and treatment gap of mental morbidity

2020 ◽  
Vol 66 (4) ◽  
pp. 361-372 ◽  
Author(s):  
Melur Sukumar Gautham ◽  
Gopalkrishna Gururaj ◽  
Mathew Varghese ◽  
Vivek Benegal ◽  
Girish N Rao ◽  
...  

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.

Author(s):  
Abdulaziz S. Alangari ◽  
Sarah S. Knox ◽  
Kim E. Innes ◽  
Alfgeir L. Kristjansson ◽  
Sijin Wen ◽  
...  

Author(s):  
Zeina N. Mneimneh ◽  
Steven G. Heeringa ◽  
Yu‐Chieh Lin ◽  
Yasmin A. Altwaijri ◽  
Raphael Nishimura

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Manuela Silva ◽  
Ana Antunes ◽  
Sofia Azeredo-Lopes ◽  
Graça Cardoso ◽  
Miguel Xavier ◽  
...  

Author(s):  
Abdullah S. Al‐Subaie ◽  
AbdulHameed Al‐Habeeb ◽  
Yasmin A. Altwaijri

2005 ◽  
Vol 40 (2) ◽  
pp. 87-98 ◽  
Author(s):  
Terry J. Lewin ◽  
Tim Slade ◽  
Gavin Andrews ◽  
Vaughan J. Carr ◽  
Charles W. Hornabrook

2018 ◽  
Vol 64 (6) ◽  
pp. 589-596 ◽  
Author(s):  
BS Chavan ◽  
Subhash Das ◽  
Rohit Garg ◽  
Sonia Puri ◽  
Aravind BA Banavaram

Background: Mental illness results in a plethora of distressing issues, has tremendous socio-economic impact and causes socio-occupational dysfunction in the individual as well as the caregivers. There is a felt need to explore the disability caused by mental illness and the associated socio-economic impact at the population level in a developing nation like India. Aims: To elucidate the disability and socio-economic impact associated with mental illness at the individual and household levels for the state of Punjab in India. Method: This was a multisite cross-sectional study carried out during 2015–2016 (as a part of the National Mental Health Survey of India) in three districts and one urban metro area of Punjab. The sample was selected using multi-stage, stratified, random cluster sampling technique, with random selection based on Probability Proportionate to Size (PPS) at different stages. A validated set of questions was used to assess the socio-economic impact of mental illness and the Sheehan Disability Scale was used to document self-perceived disability among individuals with mental morbidity. Median (IQR) and proportions were used to summarize quantitative and qualitative data, respectively Results: Subjects with any mental morbidity reported disability of varying severities across different domains of life; family life was affected the most (70.1%). One in every six persons reported that their mental illness interfered with their daily activities to a large extent. Economic burden was high and a typical family would spend about INR 1500/month (US$23) towards the treatment of its member with mental morbidity. Family members had to forego their work for at least 7 days in 3 months to take care of their relative with mental illness. Conclusion: Mental illness causes disability in the individual and has tremendous socio-economic impact on the family, incapacitating a family’s productivity to a large extent and thus affecting the society.


Addiction ◽  
2007 ◽  
Vol 102 (8) ◽  
pp. 1261-1268 ◽  
Author(s):  
Corina Benjet ◽  
Guilherme Borges ◽  
Maria Elena Medina-Mora ◽  
Clara Fleiz ◽  
Jeronimo Blanco ◽  
...  

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