| Literature DB >> 30359382 |
Banandur S Pradeep1, Gopalkrishna Gururaj1, Mathew Varghese2, Vivek Benegal3, Girish N Rao1, Gautham M Sukumar1, Senthil Amudhan1, Banavaram Arvind1, Satish Girimaji4, Thennarasu K5, Marimuthu P5, Kommu John Vijayasagar4, Binukumar Bhaskarapillai5, Jagadisha Thirthalli2, Santosh Loganathan2, Naveen Kumar2, Paulomi Sudhir6, Veena A Sathyanarayana6, Kangkan Pathak7, Lokesh Kumar Singh8, Ritambhara Y Mehta9, Daya Ram10, Shibukumar T M11, Arun Kokane12, Lenin Singh R K13, Chavan B S14, Pradeep Sharma15, Ramasubramanian C16, Dalal P K17, Pradeep Kumar Saha18, Sonia Pereira Deuri19, Anjan Kumar Giri20, Abhay Bhaskar Kavishvar21, Vinod K Sinha10, Jayakrishnan Thavody22, Rajni Chatterji23, Brogen Singh Akoijam24, Subhash Das14, Amita Kashyap25, Sathish R V26, Selvi M27, Singh S K28, Vivek Agarwal29, Raghunath Misra30.
Abstract
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.Entities:
Mesh:
Year: 2018 PMID: 30359382 PMCID: PMC6201882 DOI: 10.1371/journal.pone.0205096
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Project management–organogram with roles and responsibilities of different teams.
Fig 2Overview of study designs.
Fig 3Steps in data collection and flow of interview.
Sampling framework for the National Mental Health Survey– 2016.
| South | West | North | Central | East | Northeast | TOTAL | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| KL | TN | GJ | RJ | PB | UP | CG | MP | JH | WB | AS | MN | ||
| Number of Districts | 14 | 32 | 26 | 33 | 20 | 71 | 18 | 50 | 24 | 19 | 27 | 9 | 343 |
| Number of Districts Selected | 3 | 4 | 3 | 4 | 4 | 4 | 3 | 4 | 4 | 4 | 3 | 3 | 43 |
| Number of Taluka in the selected Districts | 15 | 32 | 19 | 30 | 17 | 19 | 29 | 33 | 52 | 88 | 21 | 11 | 366 |
| Number of Taluka Selected | 6 | 7 | 7 | 7 | 7 | 7 | 6 | 7 | 7 | 7 | 6 | 6 | 80 |
| Total number of Clusters in the Selected Taluka | 265 | 1082 | 738 | 1200 | 1103 | 2544 | 1067 | 1239 | 967 | 966 | 1035 | 272 | 12,478 |
| Number of Clusters selected | 60 | 60 | 60 | 60 | 60 | 60 | 60 | 60 | 60 | 60 | 60 | 60 | 720 |
| Proportion of clusters selected (%) | 22.6 | 5.5 | 8.1 | 5.0 | 5.4 | 2.4 | 5.6 | 4.8 | 6.2 | 6.2 | 5.8 | 22.1 | 5.8 |
| Number of Households in the Selected Clusters | 192,569 | 76,322 | 360,678 | 49,184 | 76,161 | 68,033 | 50,603 | 62,462 | 58,281 | 89,017 | 34,594 | 51,971 | 1,169,875 |
| Number of Households Contacted | 1223 | 1083 | 953 | 602 | 723 | 880 | 738 | 1051 | 685 | 842 | 954 | 876 | 10610 |
| Proportion of Households Contacted | 0.6 | 1.4 | 0.3 | 1.2 | 0.9 | 1.3 | 1.5 | 1.7 | 1.2 | 0.9 | 2.8 | 1.7 | 0.9 |
| Number of Households interviewed | 926 | 1069 | 927 | 576 | 719 | 795 | 722 | 918 | 637 | 654 | 926 | 797 | 9666 |
| Proportion of Households interviewed (%) | 75.7 | 98.7 | 97.3 | 95.7 | 99.4 | 90.3 | 97.8 | 87.3 | 93 | 77.7 | 97.1 | 91 | 91.1 |
| Number of eligible Individuals in the selected households (≥18 years) | 3149 | 3462 | 3439 | 3233 | 3158 | 3788 | 3079 | 3240 | 3673 | 2818 | 3104 | 3389 | 39,532 |
| Number of Eligible Individuals interviewed | 2479 | 3059 | 3168 | 3108 | 2895 | 3508 | 2841 | 2621 | 3022 | 2646 | 2603 | 2852 | 34802 |
| Proportion of Eligible Individuals interviewed | 78.7 | 88.4 | 92.1 | 96.1 | 91.7 | 92.6 | 92.3 | 80.9 | 82.3 | 93.9 | 83.8 | 84.2 | 88.0 |
*KL = Kerala; TN = Tamilnadu; GJ = Gujarat; RJ = Rajasthan; PB = Punjab; UP = Uttar Pradesh; CG = Chattisgarh; MP = Madhya Pradesh; JH = Jharkhand; WB = West Bengal; AS = Assam; MN = Manipur
Socio demographic characteristics of study subjects selected for NMHS.
| Un-Weighted | Weighted | Un-Weighted | Weighted | Un-Weighted | Weighted | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Variables | Categories in Variable | Males | Males | Females | Females | Total | Total | ||||||
| n | % | n | % | n | % | N | % | n | % | n | % | ||
| Age group | 18 to 29 | 5537 | 33.39% | 215464 | 34.96% | 6311 | 34.64% | 241762 | 36.75% | 11848 | 34.04% | 457226 | 35.89% |
| 30 to 39 | 3377 | 20.36% | 128809 | 20.90% | 3685 | 20.23% | 135483 | 20.60% | 7062 | 20.29% | 264292 | 20.74% | |
| 40 to 49 | 2731 | 16.47% | 101651 | 16.50% | 3123 | 17.14% | 110309 | 16.77% | 5854 | 16.82% | 211960 | 16.64% | |
| 50 to 59 | 2088 | 12.59% | 73847 | 11.98% | 2360 | 12.95% | 81418 | 12.38% | 4448 | 12.78% | 155265 | 12.19% | |
| 60 and above | 2852 | 17.20% | 96479 | 15.66% | 2738 | 15.03% | 88867 | 13.51% | 5590 | 16.06% | 185346 | 14.55% | |
| Place of Residence | Rural | 11384 | 68.64% | 404997 | 65.72% | 12573 | 69.02% | 437909 | 66.57% | 23957 | 68.84% | 842906 | 66.16% |
| Urban non-metro | 3162 | 19.07% | 92483 | 15.01% | 3439 | 18.88% | 98215 | 14.93% | 6601 | 18.97% | 190698 | 14.97% | |
| Urban metro | 2039 | 12.29% | 118770 | 19.27% | 2205 | 12.10% | 121715 | 18.50% | 4244 | 12.19% | 240485 | 18.88% | |
| Education | Illiterate | 2450 | 14.77% | 93486 | 15.17% | 5959 | 32.71% | 231236 | 35.15% | 8409 | 24.16% | 324722 | 25.49% |
| Primary | 3112 | 18.76% | 131919 | 21.41% | 3048 | 16.73% | 121598 | 18.48% | 6160 | 17.70% | 253517 | 19.90% | |
| Secondary | 3075 | 18.54% | 112258 | 18.22% | 2647 | 14.53% | 93734 | 14.25% | 5722 | 16.44% | 205992 | 16.17% | |
| High School | 3498 | 21.09% | 114686 | 18.61% | 2995 | 16.44% | 89925 | 13.67% | 6493 | 18.66% | 204611 | 16.06% | |
| Pre-University | 1916 | 11.55% | 70107 | 11.38% | 1598 | 8.77% | 53622 | 8.15% | 3514 | 10.10% | 123729 | 9.71% | |
| Vocational | 250 | 1.51% | 10444 | 1.69% | 109 | 0.60% | 3668 | 0.56% | 359 | 1.03% | 14112 | 1.11% | |
| Graduate | 1600 | 9.65% | 59363 | 9.63% | 1313 | 7.21% | 46137 | 7.01% | 2913 | 8.37% | 105500 | 8.28% | |
| Post Graduate | 450 | 2.71% | 16954 | 2.75% | 411 | 2.26% | 14493 | 2.20% | 861 | 2.47% | 31447 | 2.47% | |
| Professional | 188 | 1.13% | 5317 | 0.86% | 82 | 0.45% | 1839 | 0.28% | 270 | 0.78% | 7156 | 0.56% | |
| Not known | 46 | 0.28% | 1716 | 0.28% | 55 | 0.30% | 1587 | 0.24% | 101 | 0.29% | 3303 | 0.26% | |
| Occupation | Cultivator | 2882 | 17.38% | 109289 | 17.73% | 376 | 2.06% | 15255 | 2.32% | 3258 | 9.36% | 124544 | 9.78% |
| Agricultural Labourer | 2104 | 12.69% | 79805 | 12.95% | 927 | 5.09% | 36665 | 5.57% | 3031 | 8.71% | 116470 | 9.14% | |
| Employer | 327 | 1.97% | 11493 | 1.86% | 48 | 0.26% | 1525 | 0.23% | 375 | 1.08% | 13018 | 1.02% | |
| Employee &other worker | 6872 | 41.44% | 245970 | 39.91% | 3264 | 17.92% | 77442 | 11.77% | 10136 | 29.12% | 323412 | 25.38% | |
| Student | 1559 | 9.40% | 60389 | 9.80% | 1277 | 7.01% | 49092 | 7.46% | 2836 | 8.15% | 109481 | 8.59% | |
| Household duties | 227 | 1.37% | 8108 | 1.32% | 10227 | 56.14% | 395091 | 60.06% | 10454 | 30.04% | 403199 | 31.65% | |
| Dependent | 1210 | 7.30% | 48183 | 7.82% | 1548 | 8.50% | 65148 | 9.90% | 2758 | 7.92% | 113331 | 8.90% | |
| Pensioner | 649 | 3.91% | 21475 | 3.48% | 361 | 1.98% | 10818 | 1.64% | 1010 | 2.90% | 32293 | 2.53% | |
| Others | 755 | 4.55% | 31538 | 5.12% | 189 | 1.04% | 6803 | 1.03% | 944 | 2.71% | 38341 | 3.01% | |
| Marital status | Never Married | 3903 | 23.53% | 150698 | 24.45% | 2614 | 14.35% | 98334 | 14.95% | 6517 | 18.73% | 249032 | 19.55% |
| Married | 12235 | 73.77% | 451105 | 73.20% | 13745 | 75.45% | 497750 | 75.66% | 25980 | 74.65% | 948855 | 74.47% | |
| Widowed/Divorced/ Separated | 361 | 2.18% | 11888 | 1.93% | 1783 | 9.79% | 59029 | 8.97% | 2144 | 6.16% | 70917 | 5.57% | |
| Others | 86 | 0.52% | 2559 | 0.42% | 75 | 0.41% | 2726 | 0.41% | 161 | 0.46% | 5285 | 0.41% | |
| Total | 16585 | 47.66% | 616250 | 48.37% | 18217 | 52.34% | 657839 | 51.63% | 34802 | 100.00% | 1274089 | 100.00% | |