The burden of mental disorders across the states of India: the Global Burden of Disease Study 1990–2017

Abstract

Background
Mental disorders are among the leading causes of non-fatal disease burden in India, but a systematic understanding of their prevalence, disease burden, and risk factors is not readily available for each state of India. In this report, we describe the prevalence and disease burden of each mental disorder for the states of India, from 1990 to 2017.
Methods
We used all accessible data from multiple sources to estimate the prevalence of mental disorders, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) caused by these disorders for all the states of India from 1990 to 2017, as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We assessed the heterogeneity and time trends of mental disorders across the states of India. We grouped states on the basis of their Socio-demographic Index (SDI), which is a composite measure of per-capita income, mean education, and fertility rate in women younger than 25 years. We also assessed the association of major mental disorders with suicide deaths. We calculated 95% uncertainty intervals (UIs) for the point estimates.
Findings
In 2017, 197·3 million (95% UI 178·4–216·4) people had mental disorders in India, including 45·7 million (42·4–49·8) with depressive disorders and 44·9 million (41·2–48·9) with anxiety disorders. We found a significant, but modest, correlation between the prevalence of depressive disorders and suicide death rate at the state level for females (r2=0·33, p=0·0009) and males (r2=0·19, p=0·015). The contribution of mental disorders to the total DALYs in India increased from 2·5% (2·0–3·1) in 1990 to 4·7% (3·7–5·6) in 2017. In 2017, depressive disorders contributed the most to the total mental disorders DALYs (33·8%, 29·5–38·5), followed by anxiety disorders (19·0%, 15·9–22·4), idiopathic developmental intellectual disability (IDID; 10·8%, 6·3–15·9), schizophrenia (9·8%, 7·7–12·4), bipolar disorder (6·9%, 4·9–9·6), conduct disorder (5·9%, 4·0–8·1), autism spectrum disorders (3·2%, 2·7–3·8), eating disorders (2·2%, 1·7–2·8), and attention-deficit hyperactivity disorder (ADHD; 0·3%, 0·2–0·5); other mental disorders comprised 8·0% (6·1–10·1) of DALYs. Almost all (>99·9%) of these DALYs were made up of YLDs. The DALY rate point estimates of mental disorders with onset predominantly in childhood and adolescence (IDID, conduct disorder, autism spectrum disorders, and ADHD) were higher in low SDI states than in middle SDI and high SDI states in 2017, whereas the trend was reversed for mental disorders that manifest predominantly during adulthood. Although the prevalence of mental disorders with onset in childhood and adolescence decreased in India from 1990 to 2017, with a stronger decrease in high SDI and middle SDI states than in low SDI states, the prevalence of mental disorders that manifest predominantly during adulthood increased during this period.
Interpretation
One in seven Indians were affected by mental disorders of varying severity in 2017. The proportional contribution of mental disorders to the total disease burden in India has almost doubled since 1990. Substantial variations exist between states in the burden from different mental disorders and in their trends over time. These state-specific trends of each mental disorder reported here could guide appropriate policies and health system response to more effectively address the burden of mental disorders in India.

Full text

www.thelancet.com/psychiatry Published online December 23, 2019 https://doi.org/10.1016/S2215-0366(19)30475-4
1
Articles
Lancet Psychiatry 2019
Published Online
December 23, 2019
https://doi.org/10.1016/
S2215-0366(19)30475-4
See Online/Comment
https://doi.org/10.1016/
S2215-0366(19)30524-3
*Collaborators listed at the end
of the Article
Correspondence to:
Prof Lalit Dandona, Indian
Council of Medical Research,
Ansari Nagar, New Delhi 110029,
India
lalit.dandona@icmr.gov.in
The burden of mental disorders across the states of India:
the Global Burden of Disease Study 1990–2017
India State-Level Disease Burden Initiative Mental Disorders Collaborators*
Summary
Background Mental disorders are among the leading causes of non-fatal disease burden in India, but a systematic
understanding of their prevalence, disease burden, and risk factors is not readily available for each state of India. In
this report, we describe the prevalence and disease burden of each mental disorder for the states of India, from 1990
to 2017.
Methods We used all accessible data from multiple sources to estimate the prevalence of mental disorders, years lived
with disability (YLDs), and disability-adjusted life-years (DALYs) caused by these disorders for all the states of India
from 1990 to 2017, as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We assessed the
heterogeneity and time trends of mental disorders across the states of India. We grouped states on the basis of their
Socio-demographic Index (SDI), which is a composite measure of per-capita income, mean education, and fertility
rate in women younger than 25 years. We also assessed the association of major mental disorders with suicide deaths.
We calculated 95% uncertainty intervals (UIs) for the point estimates.
Findings In 2017, 197·3 million (95% UI 178·4–216·4) people had mental disorders in India, including 45·7 million
(42·4–49·8) with depressive disorders and 44·9 million (41·2–48·9) with anxiety disorders. We found a significant, but
modest, correlation between the prevalence of depressive disorders and suicide death rate at the state level for females
(r²=0·33, p=0·0009) and males (r²=0·19, p=0·015). The contribution of mental disorders to the total DALYs in India
increased from 2·5% (2·0–3·1) in 1990 to 4·7% (3·7–5·6) in 2017. In 2017, depressive disorders contributed the most
to the total mental disorders DALYs (33·8%, 29·5–38·5), followed by anxiety disorders (19·0%, 15·9–22·4), idiopathic
developmental intellectual disability (IDID; 10·8%, 6·3–15·9), schizophrenia (9·8%, 7·7–12·4), bipolar disorder (6·9%,
4·9–9·6), conduct disorder (5·9%, 4·0–8·1), autism spectrum disorders (3·2%, 2·7–3·8), eating disorders (2·2%,
1·7–2·8), and attention-deficit hyperactivity disorder (ADHD; 0·3%, 0·2–0·5); other mental disorders comprised 8·0%
(6·1–10·1) of DALYs. Almost all (>99·9%) of these DALYs were made up of YLDs. The DALY rate point estimates of
mental disorders with onset predominantly in childhood and adolescence (IDID, conduct disorder, autism spectrum
disorders, and ADHD) were higher in low SDI states than in middle SDI and high SDI states in 2017, whereas the trend
was reversed for mental disorders that manifest predominantly during adulthood. Although the prevalence of mental
disorders with onset in childhood and adolescence decreased in India from 1990 to 2017, with a stronger decrease in
high SDI and middle SDI states than in low SDI states, the prevalence of mental disorders that manifest predominantly
during adulthood increased during this period.
Interpretation One in seven Indians were aected by mental disorders of varying severity in 2017. The proportional
contribution of mental disorders to the total disease burden in India has almost doubled since 1990. Substantial
variations exist between states in the burden from dierent mental disorders and in their trends over time. These
state-specific trends of each mental disorder reported here could guide appropriate policies and health system
response to more eectively address the burden of mental disorders in India.
Funding Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research,
Ministry of Health and Family Welfare, Government of India.
Copyright © 2019 World Health Organization; licensee Elsevier. This is an Open Access article published under the
CC BY 3.0 IGO license which permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly cited. In any use of this article, there should be no suggestion that WHO endorses any specific
organisation, products or services. The use of the WHO logo is not permitted. This notice should be preserved along
with the article’s original URL.
Introduction
Mental disorders were the second leading cause of
disease burden in terms of years lived with disability
(YLDs) and the sixth leading cause of disability-adjusted
life-years (DALYs) in the world in 2017, posing a serious
challenge to health systems, particularly in low-income
and middle-income countries.1 Mental health is being
recognised as one of the priority areas in health policies
around the world and has also been included in the
Sustainable Development Goals.2–4

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Recognising the importance of mental disorders in
reducing the total disease burden, India launched its
first National Mental Health Policy in 2014 and a revised
Mental Healthcare Act in 2017, with the objectives of
providing equitable, aordable, and universal access to
mental health care.5,6 India has a federal set-up in
which health is primarily a responsibility of the states.2
The socio-cultural and demographic diversity across the
states of India requires that the policies and
interventions to contain the burden of mental disorders
be well suited to local contexts. Therefore, a better
understanding of the distribution and trends of mental
disorders for each state of India is crucial. Previous
studies exist that have described the disease burden of
mental disorders in India,7–16 but a systematic
understanding of the magnitude of this burden and the
trends for all the states of India is not readily available.
In this report, we present a detailed account of the
prevalence and disease burden of each mental disorder
and their associated risk factors for the states of India,
from 1990 to 2017, on the basis of modelling using all
accessible data sources. Our use of the word burden
within this study is in line with the technical language
of the Global Burden of Diseases, Injuries, and Risk
Factors Study (GBD), and is not intended to imply
negative judgement of individuals who experience
mental health problems.
Methods
Overview
The analysis and findings of mental disorders presented
in this Article were produced by the India State-Level
Disease Burden Initiative as part of GBD 2017. The work
of this Initiative has been approved by the Health Ministry
Screening Committee at the Indian Council of Medical
Research and the ethics committee of the Public Health
Foundation of India. A comprehensive description of the
metrics, data sources, and statistical modelling for mental
disorders in GBD 2017 has been reported elsewhere.3,17–20
In GBD 2017, mental disorders included depressive
disorders, anxiety disorders, schizophrenia, bipolar
disorder, idiopathic developmental intellectual disability
(IDID), conduct disorder, autism spectrum disorders,
eating disorders, attention-deficit hyperactivity disorder
(ADHD), and other mental disorders. Suicide is classified
under injuries in GBD. The India State-Level Disease
Burden Initiative has previously reported detailed trends
of suicide deaths for all states of India.21 The GBD 2017
methods relevant for this Article are summarised here
and described in detail in the appendix (pp 3–39).
Research in context
Evidence before this study
We searched PubMed for published papers on mental disorders
in India and Google for reports in the public domain, as well as
references in these papers and reports, on April 22, 2019,
using the search terms “anorexia nervosa”, “anxiety disorders”,
“attention-deficit disorder with hyperactivity”, “autism
spectrum disorders”, “bipolar disorder”, “bulimia nervosa”,
“burden”, “conduct disorder”, “DALYs”, “depressive disorders”,
“major depressive disorders”, “dysthymic disorder”, “eating
disorders”, ‘’epidemiology’’, “India”, “intellectual disability” ,
“mental disorders”, “mental health”, ‘’morbidity’’, “prevalence”,
“schizophrenia”, and “trends”, without language or publication
date restrictions. We found some studies on the prevalence of
mental disorders done in different parts of India, including the
National Mental Health Survey, but we found no systematic
compilation of the state-level variations of prevalence and
disability-adjusted life-years (DALYs) and their time trends,
which is needed to inform the mental health policy and
programmes across the country.
Added value of this study
To our knowledge, this study is the first to provide
comprehensive estimates of the prevalence and disease burden
due to all mental disorders for every state of India from
1990 to 2017, on the basis of all accessible data sources and
with use of the standardised Global Burden of Diseases, Injuries,
and Risk Factors Study framework. The findings highlight that
mental disorders affect one in seven people in India, and their
contribution to the total disease burden has almost doubled
between 1990 and 2017. This Article reports variations in the
prevalence of mental disorders between the states of India,
with the prevalence of mental disorders of predominantly
childhood and adolescent onset higher in the less developed
northern states than in the more developed southern states,
and the prevalence of mental disorders manifesting
predominantly during adulthood higher in the more developed
southern states than in the less developed northern states. This
report assessed the association of major mental disorders with
the suicide death rate at the state level, finding a significant,
but modest, correlation with depressive disorders. The findings
include a description of how the burden of individual mental
disorders has changed from 1990 to 2017 in the states of India
at different levels of development. Finally, this report assessed
the burden of mental disorders that can be attributed to risk
factors.
Implications of all the available evidence
This comprehensive assessment of mental disorders in every
state of India from 1990 to 2017 highlights that a large
proportion of India’s population is affected by these disorders,
emphasising an urgent need to put in place systems that can
facilitate better diagnosis and management of mental
disorders across the country. The state-specific findings of the
burden and time trends of individual mental disorders in this
report could serve as a reference for policy makers to plan
approaches for curbing the growing burden of mental
disorders in a systematic way in India.
See Online for appendix

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Estimation of prevalence, YLDs, and DALYs
Mental disorders and their types were defined on the basis
of the clinical diagnostic criteria from the Diagnostic and
Statistical Manual of Mental Disorders (fourth edition, text
revision) or the International Classification of Diseases
(tenth edition).19 The prevalence of mental disorders was
estimated with use of DisMod-MR (version 2.1), a meta-
regression computational tool for Bayesian disease
modelling that is the standard GBD modelling approach
for describing non-fatal health outcomes by location, age,
sex, and year. This approach involved identification of all
available data sources that could be accessed, estimation
of cause-specific prevalence, estimation of severity
distribution for sequelae, quantification of the magnitude
of health loss by use of disability weights, adjustment for
comorbidity, and computation of YLDs for each location,
age, sex, and year.19 YLDs were estimated as the product
of prevalence estimate and disability weights for health
states of each mutually exclusive sequela, with adjustment
for comorbidities.
Eating disorders were the only mental disorders in
GBD 2017 to which deaths could be attributed directly.17,18
All accessible data, including those for covariates, were
used to develop a set of plausible models and eventually,
the best ensemble predictive model to produce estimates
of deaths and years of life lost (YLLs) due to premature
mortality by location, age, sex, and year.17,18 YLLs were
computed from observed deaths and reference standard
life expectancy at the age of death, which was obtained
from the GBD standard life table.17 DALYs, a summary
measure of total health loss, were computed by adding
YLLs and YLDs for each cause under mental disorders.3
The major data inputs for estimating the prevalence of
mental disorders in India were population-based surveys,
including the World Health Survey 2003 for India, the
National Mental Health Survey 2015–16, and other
published studies (appendix pp 40–46).
Estimation of risk factor exposure and attributable
disease burden
The GBD comparative risk assessment frame work was
used to estimate exposure of risk factors related to
mental disorders and their attributable disease burden.20
Exposure data for risk factors with a categorical or
continuous distribution were collated from all available
data sources that could be accessed, including survey
and other data, adjusted by use of age-sex splitting and
strengthened with the incorporation of covariates for
modelling. For each risk factor, the theoretical minimum
risk exposure level was established as the lowest level of
risk exposure below which its relationship with a disease
outcome was not supported by the available evidence.
The modelling approach integrated multiple data inputs
and borrowed information across age, time, and location
to produce the best possible estimates of risk exposure
by location, age, sex, and year.20 The estimation of
attributable disease burden to risk factors included
ascertainment of the relative risk of disease outcomes
for risk exposure–disease outcome pairs with sucient
evidence of a causal relation in global literature
(ie, randomised controlled trials, prospective cohorts, or
case-control studies). Estimates of mean risk factor
exposure were used to calculate summary exposure
values for each risk, a metric ranging from 0% to 100%
to describe the risk-weighted exposure for a population
or risk-weighted prevalence of exposure.20 The estimates
for summary exposure values were then combined with
relative risk estimates for mental disorders with
sucient evidence of a causal relationship to calculate
deaths, YLLs, YLDs, and DALYs attributable to each
risk factor. A detailed description of exposure and
attributable disease burden estimation for the major
risk factors associated with mental disorders, including
GBD exposure defi nitions and statistical modelling,
is provided in the appendix (pp 31–39) and has
been previously published.20 The risk factors to which
the burden of mental disorders could be attributed
in GBD 2017 included lead exposure, intimate
partner violence, childhood sexual abuse, and bullying
victimisation.20
GBD uses covariates that have a known association
with the outcome of interest to arrive at the best possible
estimate of the outcome of interest when data for the
outcome are scarce but data for covariates are available.
This approach was part of the estimation process for the
findings presented in this Article.3,17–20
Analysis presented in this Article
We report findings for 31 geographical units in India,
comprising 29 states, the Union Territory of Delhi, and
the union territories other than Delhi (combining the
six smaller union territories of Andaman and Nicobar
Islands, Chandigarh, Dadra and Nagar Haveli, Daman
and Diu, Lakshadweep, and Puducherry). The states of
Chhattisgarh, Uttarakhand, and Jharkhand were created
from existing larger states in 2000, and the state of
Telangana was created in 2014. For trends from
1990 onward, we disaggregated data for these four new
states from their parent states on the basis of data from
the districts that now constitute these states. The state of
Jammu and Kashmir was divided into two union
territories in August, 2019. Because we are reporting
findings up to 2017, we report findings for the state of
Jammu and Kashmir. We also present here findings for
three groups of states based on the Socio-demographic
Index (SDI) computed by GBD. SDI is a composite
indicator of development status, ranging from 0 to 1, and
is a geometric mean of the values of the indices of lag-
distributed per-capita income, mean education in people
aged 15 years or older, and total fertility rate in people
younger than 25 years.22 The states were categorised into
three state groups on the basis of their SDI in 2017: low
SDI (≤0·53), middle SDI (0·54–0·60), and high SDI
(>0·60; appendix p 47).23

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We report the overall and age-specific and sex-specific
prevalence and DALY rates in 2017 for each mental
disorder for all states of India. We also report the
comparison of the percentage change in prevalence of
mental disorders from 1990 to 2017, with the percentage
change in the DALY rates reported for India and the SDI
state groups. We assessed the relationship between the
prevalence of depressive disorders, anxiety disorders,
schizophrenia, and bipolar disorder with the suicide
death rate at the state level using correlation analysis.
We present the DALYs for specific mental disorders that
were attributable to risk factors in 2017.
We present both crude and age-standardised estimates
as relevant. Crude estimates reflect the actual situation
of each state and thus are useful for policy makers. By
contrast, age-standardised estimates allow comparisons
over time and across states after adjusting for the age
structure of the population. The age-standardised rates
were based on the GBD global reference population.18
Estimates are reported with 95% uncertainty intervals
(UIs) wherever relevant. These intervals were based on
1000 runs of the models for each quantity of interest,
with the mean considered as the point estimate and the
2·5th and 97·5th percentiles considered as the 95% UI
(appendix p 39).3,18–20
Role of the funding source
Some of the contributors to this study work with the
Indian Council of Medical Research. The other funder,
the Bill & Melinda Gates Foundation, of the study had no
role in the study design, data collection, data analysis,
data interpretation, or writing of the report. The
corresponding author had full access to all of the data in
the study, and had final responsibility for the decision to
submit for publication.
Results
In 2017, there were 197·3 million (95% UI 178·5–216·4)
people with mental disorders in India, comprising
14·3% of the total population of the country. Mental
disorders contributed 4·7% (3·7–5·6) of the total DALYs
in India in 2017, compared with 2·5% (2·0–3·1) in 1990.24
YLDs made up all the DALYs from mental disorders in
2017, except eating disorders, for which YLDs made up
99·8% of the DALYs. Mental disorders were the leading
cause of YLDs in India, contributing 14·5% of the total
YLDs in 2017.24 The highest contri bution to DALYs due to
mental disorders in India in 2017 was from depressive
disorders (33·8%, 29·5–38·5) and anxiety disorders
(19·0%, 15·9–22·4), followed by IDID (10·8%, 6·3–15·9),
schizophrenia (9·8%, 7·7–12·4), bipolar disorder (6·9%,
4·9–9·6), and conduct disorder (5·9%, 4·0–8·1; table 1).
The contri bution of depressive disorders and eating
disorders to the total DALYs was substantially higher in
females than in males, whereas the contribution of autism
spectrum disorders and ADHD was significantly higher
in males than in females.
Prevalence of mental disorders
Among the major mental disorders that manifest
predominantly during adulthood, the crude prevalence for
both depressive disorders and anxiety disorders was 3·3%
(3·1–3·6 for depressive disorders and 3·0–3·5 for anxiety
disorders), whereas bipolar disorders had prevalence of
0·6% (0·5–0·7) and schizophrenia 0·3% (0·2–0·3)
(table 2). In 2017, 45·7 million (42·4–49·8) people had
depressive disorders in India. Prevalence of depressive
disorders varied 1·9 times among the states, with the
highest prevalence observed in Tamil Nadu, Kerala, Goa,
and Telangana in the high SDI state group; Andhra
Pradesh in the middle SDI state group; and Odisha in the
low SDI state group (figure 1, appendix p 48).
The prevalence of depressive disorders was positively
associated with the suicide death rate at the state level for
both sexes, with a slightly higher correlation coecient in
Both sexes Males Females
Depressive disorders 33·8% (29·5–38·5) 28·9% (25·0–33·3) 38·6% (34·0–43·7)
Major depressive disorder 26·7% (22·6–31·2) 22·7% (19·0–27·0) 30·6% (26·1–35·8)
Dysthymia 7·1% (5·7–8·7) 6·2% (4·9–7·6) 8·0% (6·4–9·7)
Anxiety disorders 19·0% (15·9–22·4) 16·2% (13·5–19·2) 21·7% (18·1–25·5)
Idiopathic developmental intellectual
disability
10·8% (6·3–15·9) 11·8% (7·0–17·4) 9·7% (5·6–14·6)
Schizophrenia 9·8% (7·7–12·4) 11·2% (8·8–14·0) 8·5% (6·7–10·8)
Bipolar disorder 6·9% (4·9–9·6) 7·2% (5·1–10·0) 6·6% (4·7–9·1)
Conduct disorder 5·9% (4·0–8·1) 7·9% (5·5–10·9) 3·9% (2·6–5·6)
Autism spectrum disorders 3·2% (2·7–3·8) 4·8% (4·0–5·7) 1·7% (1·4–2·0)
Eating disorders 2·2% (1·7–2·8) 1·5% (1·1–2·0) 2·8% (2·2–3·6)
Anorexia nervosa 0·5% (0·3–0·6) 0·2% (0·1–0·3) 0·7% (0·5–0·9)
Bulimia nervosa 1·8% (1·3–2·3) 1·3% (1·0–1·8) 2·2% (1·6–2·8)
Attention-deficit hyperactivity disorder 0·3% (0·2–0·5) 0·5% (0·3–0·7) 0·2% (0·1–0·3)
Other mental disorders 8·0% (6·1–10·1) 9·9% (7·5–12·4) 6·3% (4·7–7·9)
Data are percentage, with 95% uncertainty interval in parentheses. DALYs=disability-adjusted life-years.
Table 1: Percentage of total DALYs due to each cause under mental disorders in India, 2017
Both sexes Males Females
All mental disorders 14·3% (12·9–15·7) 14·2% (12·8–15·6) 14·4% (13·1–15·8)
Idiopathic developmental intellectual
disability
4·5% (3·0–6·0) 4·7% (3·1–6·3) 4·3% (2·9–5·7)
Depressive disorders 3·3% (3·1–3·6) 2·7% (2·5–3·0) 3·9% (3·6–4·3)
Anxiety disorders 3·3% (3·0–3·5) 2·7% (2·4–2·9) 3·9% (3·6–4·3)
Conduct disorder 0·8% (0·6–1·0) 1·0% (0·8–1·3) 0·6% (0·4–0·7)
Bipolar disorder 0·6% (0·5–0·7) 0·6% (0·5–0·7) 0·6% (0·5–0·7)
Attention-deficit hyperactivity disorder 0·4% (0·3–0·5) 0·6% (0·5–0·7) 0·2% (0·2–0·3)
Autism spectrum disorders 0·4% (0·3–0·4) 0·5% (0·5–0·6) 0·2% (0·2–0·2)
Schizophrenia 0·3% (0·2–0·3) 0·3% (0·2–0·3) 0·2% (0·2–0·3)
Eating disorders 0·2% (0·1–0·2) 0·1% (0·9–1·4) 0·3% (0·2–0·3)
Other mental disorders 1·8% (1·5–2·0) 2·1% (1·8–2·4) 1·4% (1·2–1·7)
Data are percentage, with 95% uncertainty interval in parentheses.
Table 2: Prevalence of mental disorders in India, 2017

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females (r=0·57, r²=0·33; p=0·0009) than in males
(r=0·44, r²=0·19; p=0·015; appendix p 49).
In 2017, 44·9 million (41·2–48·9) people had anxiety
disorders in India. The prevalence varied 1·4 times across
the states, with the highest prevalence observed in the
states of Kerala, Karnataka, Telangana, Tamil Nadu,
Himachal Pradesh, and Maharasthra in the high SDI
state group; and Andhra Pradesh, Manipur, and West
Figure 1: Crude prevalence of major mental disorders in the states of India, 2017
The state of Jammu and Kashmir was divided into two union territories in August 2019; as we are reporting findings up to 2017, we report findings for the state of Jammu and Kashmir.
Depressive disorders
Prevalence per 100
000
Anxiety disorders
Idiopathic developmental intellectual disabilityConduct disorder
>3750
3500–3749
3250–3449
3000–3249
2750–2999
<2750
Prevalence per 100
000
>3600
3400–3599
3200–3399
3000–3199
<3000
Prevalence per 100
000
>5000
4500–4999
4000–4499
3500–3999
3000–3499
<3000
Prevalence per 100
000
>875
800–874
725–799
650–724
<650
Arunachal Pradesh
Nagaland
Manipur
Mizoram
Tripura
Meghalaya
Assam
Sikkim
Bihar
Jharkhand
West Bengal
Odisha
Chhattisgarh
Madhya Pradesh
Maharashtra
Telangana
Andhra
Pradesh
Goa
Karnataka
Tamil
Nadu
Kerala
Uttar Pradesh
Delhi
Uttarakhand
Himachal Pradesh
Punjab
Jammu & Kashmir
Haryana
Rajasthan
Gujarat
Arunachal Pradesh
Nagaland
Manipur
Mizoram
Tripura
Meghalaya
Assam
Sikkim
Bihar
Jharkhand
West Bengal
Odisha
Chhattisgarh
Madhya Pradesh
Maharashtra
Telangana
Andhra
Pradesh
Goa
Karnataka
Tamil
Nadu
Kerala
Uttar Pradesh
Delhi
Uttarakhand
Himachal Pradesh
Punjab
Jammu & Kashmir
Haryana
Rajasthan
Gujarat
Arunachal Pradesh
Nagaland
Manipur
Mizoram
Tripura
Meghalaya
Assam
Sikkim
Bihar
Jharkhand
West Bengal
Odisha
Chhattisgarh Chhattisgarh
Madhya Pradesh
Maharashtra
Telangana
Andhra
Pradesh
Goa
Karnataka
Tamil
Nadu
Kerala
Uttar Pradesh
Delhi
Uttarakhand
Himachal Pradesh
Punjab
Jammu & Kashmir
Haryana
Rajasthan
Gujarat
Arunachal Pradesh
Nagaland
Manipur
Mizoram
Tripura
Meghalaya
Assam
Sikkim
Bihar
Jharkhand
West Bengal
Odisha
Madhya Pradesh
Maharashtra
Telangana
Andhra
Pradesh
Goa
Karnataka
Tamil
Nadu
Kerala
Uttar Pradesh
Delhi
Uttarakhand
Himachal Pradesh
Punjab
Jammu & Kashmir
Haryana
Rajasthan
Gujarat

Articles
6
www.thelancet.com/psychiatry Published online December 23, 2019 https://doi.org/10.1016/S2215-0366(19)30475-4
Bengal in the middle SDI state group (figure 1, appendix
p 48). We did not find a significant association of the
prevalence of anxiety disorders with the suicide death rate
at the state level (appendix p 49).
In 2017, 7·6 million (95% UI 6·6–9·0) people had
bipolar disorder in India. The prevalence varied 1·3 times
across the states, with Goa, Kerala, Sikkim, and Himachal
Pradesh of the high SDI state group having the highest
prevalence among all states. 3·5 million (95% UI
3·0–4·0) people had schizophrenia in India in 2017.
Prevalences varied 1·6 times among states, with the
highest prevalence obser ved in the states of Goa, Kerala,
Tamil Nadu, and Delhi of the high SDI state group. We
found a modest correlation between the prevalence of
schizophrenia and suicide death rate in males (r=0·33,
r²=0·11; p=0·066) and females (r=0·35, r²=0·12, p=0·052)
which did not reach signifi cance for both sexes
(appendix p 49).
Among mental disorders that have the onset
predominantly during childhood and adolescence, the
crude prevalence for IDID was 4·5% (95% UI 3·0–6·0),
whereas conduct disorder had prevalence of 0·8%
(0·6–1·0), ADHD of 0·4% (0·3–0·5), and autism
spectrum disorders of 0·4% (0·3–0·4; table 2). The
prevalence of IDID varied 3·2 times across the states of
India in 2017, with the highest prevalence observed in
Bihar, Uttar Pradesh, Madhya Pradesh, and Assam of
Figure 2: Age-specific and sex-specific prevalence of mental disorders in India, 2017
Shaded areas show 95% uncertainty intervals.
<5
5–9
10–14
15–19
20–24
25–29
30–34
35–39
40–44
45–49
50–54
55–59
60–64
65–69
70–74
75–79
≥80
0
<5
5–9
10–14
15–19
20–24
25–29
30–34
35–39
40–44
45–49
50–54
55–59
60–64
65–69
70–74
75–79
≥80
0
<5
5–9
10–14
15–19
20–24
25–29
30–34
35–39
40–44
45–49
50–54
55–59
60–64
65–69
70–74
75–79
≥80
0
0·2 0·1
1·0
0·4
2·0 0·6
0·2
3·0 0·8
0·3
1·0 0·4
4·0
1·2 0·5
5·0
1·4
1·6
0·6
6·0 0·7
7·0
Conduct disorder Attention-deficit hyperactivity disorder Eating disorders
1·8 0·8
Prevalence (%)
0 0 0
0·1 1
0·2
0·1
2
0·3
0·2
3
0·3
0·4
0·4 4
0·5
5
0·5
6
0·6 7
0·6
0·7 8
0·8
Schizophrenia Idiopathic developmental intellectual disability Autism spectrum disorders
9 0·7
Prevalence (%)
Age group (years) Age group (years) Age group (years)
0 0 0
210·2
420·4
3
6
4
0·6
850·8
10 1·0
6
12
Depressive disorders Anxiety disorders Bipolar disorder
7 1·2
Prevalence (%)
Females
Males
Figure 3: Crude DALY rates of mental disorders in the states of India grouped
by SDI, 2017
DALY=disability-adjusted life-year. SDI=Socio-demographic Index. UTs=Union
territories. *The state of Jammu and Kashmir was divided into two union
territories in August 2019; because we are reporting findings up to 2017, we
report findings for the state of Jammu and Kashmir.

Articles
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7
Crude DALY rate per 100
000 population (95% uncertainty interval)
Depressive
disorders
Anxiety
disorders
Idiopathic
developmental
intellectual disability
Schizophrenia Bipolar
disorder
Conduct
disorder
Autism
spectrum
disorders
Eating
disorders
Attention-deficit
hyperactivity
disorder
Other mental
disorders
I
ndia (1380 million population
)
Low SDI states (675 million population
)
Bihar
Madhya Pradesh
Jharkhan
d
Uttar Pradesh
Rajasthan
Chhattisgar
h
Odisha
Assam
Middle SDI states (387 million population
)
Andhra Pradesh
West Bengal
Tripura
Arunachal Pradesh
Meghalaya
Karnataka
Telangana
Gujarat
Manipur
Jammu and Kashmir
*
Haryana
High SDI states (318 million population
)
Uttarakhand
Tamil Nadu
Mizoram
Maharashtr
a
Punjab
Sikkim
Nagaland
Himachal Pradesh
UTs other than Delhi
Kerala
Delhi
Goa
Ratio of
the state DALY rate to median DALY rate for all states
<0·75
0·75–0·99
1·00–1·24
1·25–1·49
1·50–1·74
550 (390–748)
467 (332–635)
406 (287–552)
471 (332–643)
476 (337–648)
443 (316–605)
444 (314–606)
444 (312–605)
720 (504–971)
550 (387–749)
613 (430–828)
793 (555–1065)
535 (375–720)
505 (359–688)
597 (419–813)
577 (405–784)
617 (431–838)
756 (527–1025)
528 (372–716)
616 (436–837)
475 (335–644)
628 (440–851)
651 (461–880)
488 (346–666)
836 (588–1123)
461 (326–633)
626 (443–848)
487 (348–666)
558 (395–762)
504 (353–684)
588 (415–803)
646 (458–884)
641 (451–869)
459 (324–621)
626 (441–848)
309 (220–414)
294 (209–393)
292 (206–392)
268 (188–362)
318 (224–426)
290 (204–389)
312 (220–420)
275 (194–370)
316 (225–423)
307 (215–413)
321 (228–430)
328 (234–436)
331 (233–444)
323 (227–437)
300 (211–404)
298 (208–402)
324 (229–434)
324 (228–434)
302 (214–407)
360 (252–482)
312 (222–422)
309 (219–415)
329 (234–438)
317 (224–426)
325 (230–434)
316 (223–423)
324 (229–432)
307 (217–413)
325 (228–439)
309 (216–414)
329 (234–440)
330 (234–444)
383 (271–511)
321 (226–432)
315 (221–423)
175 (95–283)
213 (118–341)
252 (140–401)
207 (115–333)
192 (104–311)
215 (118–345)
196 (109–315)
181 (98–298)
186 (102–298)
201 (110–322)
155 (82–251)
151 (81–246)
189 (104–300)
179 (97–287)
155 (80–255)
182 (98–294)
142 (74–234)
142 (75–232)
135 (70–222)
184 (99–298)
168 (91–270)
119 (61–198)
121 (63–201)
128 (64–213)
127 (67–210)
159 (84–260)
127 (66–209)
123 (63–204)
112 (56–188)
141 (72–236)
121 (63–201)
103 (51–176)
107 (54–179)
87 (42–146)
71 (32–124)
160 (121–198)
143 (107–177)
133 (100–165)
147 (110–183)
146 (108–182)
137 (102–171)
148 (110–184)
154 (115–192)
163 (122–203)
152 (113–189)
173 (129–215)
177 (132–219)
176 (131–219)
172 (127–213)
148 (109–186)
141 (104–178)
175 (131–220)
175 (130–218)
171 (126–215)
162 (121–200)
160 (119–201)
166 (124–207)
181 (137–224)
164 (122–204)
183 (137–228)
162 (122–203)
178 (133–222)
179 (133–224)
185 (136–231)
153 (113–193)
182 (136–227)
196 (147–244)
192 (143–239)
185 (136–230)
210 (155–262)
113 (71–165)
106 (66–155)
102 (64–151)
106 (66–159)
107 (67–159)
104 (64–153)
109 (68–159)
110 (69–163)
112 (71–167)
108 (67–162)
119 (75–175)
121 (76–177)
120 (76–179)
120 (75–177)
109 (68–162)
108 (67–161)
120 (75–180)
120 (76–178)
117 (74–171)
118 (74–175)
117 (72–176)
114 (72–169)
120 (75–177)
115 (73–171)
113 (71–170)
117 (73–175)
121 (76–181)
121 (75–181)
124 (78–183)
114 (71–170)
123 (77–186)
130 (81–194)
132 (83–196)
122 (76–183)
134 (85–199)
96 (58–154)
108 (65–172)
117 (70–186)
101 (60–161)
118 (72–190)
112 (66–178)
105 (63–168)
96 (57–153)
89 (53–142)
99 (60–158)
86 (51–137)
82 (49–132)
87 (52–139)
89 (53–142)
110 (66–176)
116 (69–185)
71 (42–116)
85 (51–136)
91 (55–144)
96 (57–154)
106 (63–168)
95 (57–151)
84 (50–134)
99 (60–158)
76 (45–121)
100 (60–160)
90 (54–143)
85 (50–135)
90 (53–144)
112 (66–179)
82 (49–130)
82 (49–131)
71 (43–116)
88 (53–141)
72 (43–115)
53 (36–73)
54 (37–74)
54 (37–74)
53 (36–73)
53 (36–74)
54 (37–75)
54 (37–75)
52 (36–73)
52 (35–72)
53 (36–73)
53 (36–72)
52 (35–71)
52 (36–72)
52 (36–72)
54 (37–75)
54 (37–75)
52 (35–72)
52 (36–72)
53 (36–74)
53 (36–73)
54 (37–75)
54 (36–75)
51 (35–71)
53 (35–73)
51 (35–70)
53 (36–74)
53 (36–73)
53 (36–73)
54 (36–75)
54 (37–75)
39 (26–54)
54 (37–75)
47 (32–66)
54 (37–74)
52 (35–71)
36 (23–52)
31 (19–45)
26 (16–38)
32 (20–48)
33 (20–47)
30 (19–44)
34 (22–51)
35 (22–51)
34 (21–50)
33 (21–48)
39 (25–57)
38 (24–56)
37 (23–54)
36 (23–54)
40 (25–59)
36 (23–53)
40 (25–58)
43 (28–64)
41 (25–60)
33 (21–48)
36 (23–53)
43 (27–64)
42 (26–62)
42 (27–62)
41 (26–60)
38 (24–57)
43 (27–63)
40 (25–59)
52 (33–77)
39 (25–57)
41 (26–60)
48 (31–71)
38 (24–55)
52 (33–77)
54 (34–80)
5·0 (3·0–8·1)
5·1 (3·0–8·3)
5·3 (3·0–8·7)
5·0 (3·0–8·2)
5·1 (3·0–8·4)
5·2 (3·1–8·5)
4·9 (2·9–7·8)
4·9 (2·9–7·8)
4·6 (2·8–7·5)
5·0 (3·0–8·2)
4·8 (2·8–7·7)
4·5 (2·7–7·3)
4·7 (2·7–7·6)
4·7 (2·8–7·8)
5·3 (3·1–8·6)
5·4 (3·2–8·7)
4·9 (2·8–7·8)
4·7 (2·8–7·5)
4·8 (2·8–7·8)
4·9 (2·9–7·9)
5·2 (3·0–8·5)
4·9 (2·9–8·0)
5·2 (3·1–8·3)
4·9 (2·9–8·0)
4·9 (3·0–7·9)
5·0 (3·0–8·2)
6·2 (3·7–9·9)
4·6 (2·8–7·5)
4·9 (2·9–8·0)
5·3 (3·1–8·6)
4·5 (2·6–7·2)
4·3 (2·6–6·9)
3·3 (2·0–5·5)
4·8 (2·8–7·9)
2·2 (1·2–3·9)
131 (86–181)
120 (79–167)
114 (75–158)
123 (81–171)
121 (79–168)
118 (78–164)
122 (80–169)
127 (83–175)
135 (89–186)
127 (83–176)
139 (92–192)
143 (94–198)
141 (93–196)
139 (92–192)
119 (78–165)
115 (75–159)
141 (93–195)
140 (92–193)
136 (89–188)
133 (87–184)
130 (85–180)
132 (87–183)
144 (95–198)
132 (88–183)
147 (97–202)
130 (84–179)
142 (93–197)
144 (94–198)
142 (93–197)
124 (81–172)
145 (95–199)
148 (97–205)
149 (98–205)
141 (93–194)
156 (103–215)

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8
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the low SDI state group (figure 1, appendix p 48).
The prevalence of conduct disorder varied 1·7 times
between the states, with the highest prevalence observed
in Jharkhand, Bihar, and Uttar Pradesh of the low
SDI state group; and in the north-eastern states of
Meghalaya, Nagaland, and Arunchal Pradesh. The prev-
alence of autism spectrum disorders varied 1·4 times
between the states, with the highest prevalence found in
Jammu and Kashmir and Arunachal Pradesh of the
middle SDI state group, and Bihar and Uttar Pradesh of
Figure 4: Percentage change in prevalence and DALY rate of mental disorders in the states of India grouped by SDI, 1990–2017
Error bars represent 95% uncertainty intervals. DALY=disability-adjusted life-year. SDI=Socio-demographic Index.
–5 0 5 10 15 20
India
High SDI
Middle SDI
Low SDI
Depressive disorders (crude)
–25 –20 –15 –10 –5 0
Depressive disorders (age-standardised)
0 5 10 15 2520 30
Schizophrenia (crude)
–25 –20 –15 –10 –5 0 5
Schizophrenia (age-standardised)
0 5 10 15 20
India
High SDI
Middle SDI
Low SDI
Anxiety disorders (crude)
–15 –10 –5 0 5
Anxiety disorders (age-standardised)
India
High SDI
Middle SDI
Low SDI
–30 –20 –10 0 10
Conduct disorder (crude)
–15 –5 5 15 25
Conduct disorder (age-standardised)
–20 –10 0 10 20
India
High SDI
Middle SDI
Low SDI
Attention-deficit hyperactivity disorder
(crude)
–20 –10 0 10 20
Attention-deficit hyperactivity disorder
(age-standardised)
–6 –5 –4 –3 –1–2 0
Autism spectrum disorders
(crude)
–3 –2 –1 0 1 2 3
Autism spectrum disorders
(age-standardised)
0 20 40 50 80 100
India
High SDI
Middle SDI
Low SDI
Eating disorders (crude)
0 20 40 60 80 100
Eating disorders (age-standardised)
Percentage change 1990–2017 Percentage change 1990–2017
Percentage change 1990–2017 Percentage change 1990–2017
Prevalence
DALY rate
4·0
16·0
13·3
14·3
11·6
9·5
6·8
8·6
8·5
1·8
1·0
2·7
2·3
3·4
2·6
2·5
1·9
49·4
49·0
62·5
62·2
58·0
57·9
37·8
37·1
–2·9
–3·1
–4·1
–4·0
–0·7
–1·3
–2·0
–8·0
–2·5
–3·6
–4·0
–5·5
–4·6 –3·1
–3·7
–3·6
–2·0
–2·5
–1·3
–2·2
–17·2
–17·5
–19·3
–19·9
–9·5
–10·1
–0·1
–0·8
0·1
1·0
1·3
5·8
6·3
0·8
1·2
–0·5
0·1
–0·5
0·0
–0·6
48·2
47·8
68·6
69·2
67·8
67·9
58·2
58·2
0 5 10 15 20 25
Bipolar disorder (crude)
–5 0 5 10 15 20
Bipolar disorder (age-standardised)
11·8
11·1
16·2
16·4
0·9
0·4
0·7
–0·1
0·8
0·1
1·0
0·2
14·6
14·6
13·4
13·1
10·1
10·3
10·5
10·8
7·3
6·7
–6·8
–8·4
–7·0
–7·0
–9·6
–7·6
–5·5
–8·5
–2·2
–0·6
–1·1
20·7
20·8
–0·9
–9·6
–3·4
8·7
8·0
–1·4
21·6
21·6
–1·7
14·7
14·9
–1·5
–0·7
–1·4
–0·9
–1·3
–0·6
–1·5
–0·8
1·3
–40 –30 –20 –10 0
Idiopatic developmental intellectual
disability (crude)
–35 –25 –15 –5 5
Idiopatic developmental intellectual
disability (age-standardised)
–17·5
–33·0 –27·7
–29·9 –25·0
–28·1 –22·8
–21·8
–6·3
–9·6
–6·9
–3·6
–26·4
–17·3
–13·5
–12·9

Articles
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9
the low SDI state group. The prevalence of ADHD varied
2·8 times between the states, with the highest prevalence
found in Maharashtra of the high SDI state group,
Meghalaya and Arunachal Pradesh of the middle SDI
state group, and Bihar of the low SDI state group. The
prevalence of eating disorders varied 2·1 times between
the states, with the highest prevalence observed in Goa,
Delhi, and Sikkim of the high SDI state group; and
Haryana of the middle SDI state group.
Although we found no dierence in the overall
prevalence of mental disorders between males and
females, the prevalence of depressive disorders, anxiety
disorders, and eating disorders was significantly higher in
females than in males and the prevalence of conduct
disorder, autism spectrum disorders, and ADHD was
substantially higher in males than in females (table 2). The
age-specific prevalence of depressive disorders increased
with age in India in 2017, with the highest prevalence
observed in older adults. This prevalence was significantly
higher in females than in males, starting at 45 years
(figure 2, appendix p 50). The prevalence of anxiety
disorders in both sexes increased rapidly in adolescents
and young adults and was higher in females than in males
in most age groups. The prevalence of bipolar disorder
increased during adolescence and plateaued during most
of adulthood, with a slight decline in older age groups. The
prevalence of schizophrenia increased swiftly in young age
groups, peaked in the 35–44 years age group, and declined
steadily in older age groups.
The prevalence of IDID was highest in the youngest
age groups and decreased with increasing age in both
sexes (figure 2, appendix p 50). The prevalence of autism
spectrum disorders was highest in the youngest age
groups, decreased with increasing age, and had a higher
prevalence in males than in females across all ages.
Conduct disorder was mainly prevalent between the ages
of 5–20 years, with the peak occurring in the 10–14 years
age group in both males and females; a small prevalence
remained after age 18 years that included individuals
who did not meet the criteria for classi fication as
personality disorder. The prevalence of ADHD peaked in
the 10–14 years age group and was signifi cantly higher in
males than in females for ages 5–64 years. The prevalence
of eating disorders increased during adolescence and
young adulthood, peaked at 30–34 years in both sexes,
and tapered thereafter.
DALY rate of mental disorders
There were variations between the states in the crude
DALY rates of individual mental disorders, though the
uncertainty intervals overlapped in many instances
(figure 3). The crude DALY rate of depressive disorders
varied 2·1 times between the states in 2017 and was highest
in Tamil Nadu of the high SDI state group, followed by
Telangana and Andhra Pradesh of the middle SDI state
group, and Odisha of the low SDI state group. The crude
DALY rate varied between the states 1·4 times for anxiety
disorders, 1·6 times for schizophrenia, and 1·3 times for
bipolar disorder. Crude DALY rates for IDID varied
3·5 times between the states, with the highest rates
occurring in Bihar, Madhya Pradesh, Rajasthan,
Jharkhand, Uttar Pradesh, and Assam in the low SDI state
group; and in West Bengal in the middle SDI state group.
Crude DALY rates varied between states 1·7 times for
conduct disorder and 1·4 times for autism spectrum
disorders. The DALY rates for ADHD were very low across
states. Crude DALY rates for eating disorders varied
2·1 times among states in 2017, with the highest rates
observed in Goa, Delhi, and Sikkim in the high SDI state
group. Point estimates of DALY rates for mental disorders
that have onset predominantly in childhood and
adolescence were higher in the low SDI state group than in
the middle and high SDI state groups, whereas point
estimates of mental disorders that manifest predominantly
during adulthood were lower in the low SDI state group
than in the middle and high SDI state groups, though the
95% UIs overlapped (figure 3).
Trends from 1990 to 2017
The crude prevalence and DALY rate of depressive disor-
ders, anxiety disorders, bipolar disorder, and schizo-
phrenia increased in India from 1990 to 2017 (figure 4).
The increase in prevalence and DALY rate was higher in
the high SDI and middle SDI state groups than in the
low SDI state group for depressive disorders and schizo-
phrenia, but no significant dierences were observed
between the SDI state groups for the increase in anxiety
and bipolar disorders. By contrast, the age-standardised
prevalence and DALY rate of depressive disorders
decreased in India during this period, with similar
changes in the SDI state groups, but with no significant
changes in the age-standardised prevalence and DALY
rates of anxiety disorders, bipolar disorder, and schizo-
phrenia during this period.
The crude prevalence and DALY rate of IDID, conduct
disorder, and autism spectrum disorders decreased in
India from 1990 to 2017, with a stronger decrease in the
high and middle SDI state groups than in the low SDI
state group (figure 4). The crude prevalence of ADHD
also decreased during this period, but the DALY rate did
not change significantly. The age-standardised prevalence
and DALY rate of IDID decreased significantly in India
between 1990 and 2017, but no substantial change was
observed for conduct disorder, autism spectrum
disorders, and ADHD during this period. The crude
prevalence and DALY rate of eating disorders increased in
India from 1990 to 2017. This increase was higher in high
and middle SDI state groups than in low SDI state group,
with a similar trend for age-standardised prevalence and
DALY rate.
Risk factors
A small proportion of DALYs for depressive disorders
and anxiety disorders could be attributed to known risk

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factors, with 6·9% of DALYs for depressive disorders due
to childhood sexual abuse, 4·6% due to intimate partner
violence, and 3·3% due to bullying victimisation (table 3).
The proportion of DALYs for depressive disorder that
could be attributed to childhood sexual abuse was
significantly higher in females than in males. A large
proportion of DALYs for IDID (62·8%) was attributable
to lead exposure.
Discussion
This report reveals that in 2017, one among every
seven people in India had a mental disorder, ranging
from mild to severe. The proportional contribution of
mental disorders to the total disease burden in India
almost doubled from 1990 to 2017. Among the mental
disorders that manifest predominantly during adult-
hood, the highest disease burden in India was caused
by depressive and anxiety disorders, followed by
schizophrenia and bipolar disorder. Among the mental
disorders that have their onset predominantly during
childhood and adolescence, the highest disease burden
was caused by IDID, followed by conduct disorder and
autism spectrum disorders.
The prevalence of mental disorders that manifest
predominantly during adulthood was generally higher
in the more developed southern states than in the less
developed northern states, whereas the prevalence of
mental disorders with onset predominantly in child hood
and adolescence was generally higher in the less
developed northern states than in the more developed
southern states. The higher prevalence of depressive and
anxiety disorders in southern states could be related to
the higher levels of modernisation and urbanisation in
these states and to many other factors that are not yet
well understood.25–28 We found a positive, but modest,
relationship between depressive disorders and suicide
death rates at the state level, with suicide death rates also
being higher in the southern states than in the northern
ones.21 This relationship has also been reported in
previous studies.29,30 It is also important to note that the
high prevalence of depression among older adults has
substantial implications because the population in India
is ageing rapidly.
Sex dierentials were observed in the distribution of
mental disorders in India. The observed higher preva-
lence of depressive and anxiety disorders in females
than in males has also been reported previously,29,31
which could be related to gender discrimination,
violence, sexual abuse, antenatal and postnatal stress,
and adverse socio-cultural norms.32–35 A significantly
higher prevalence of eating disorders in females than in
males has been reported elsewhere36 and, apart from
genetic and biological factors, it is also probably linked
with socio-cultural, media, and peer pressure to diet.37,38
The higher prevalence of autism spectrum disorders and
ADHD in males than in females has been reported
previously.39 Past studies have sug gested that genetic and
hormonal factors could be behind the sex dierentials in
these disorders.40 The high prevalence of depressive
disorders in older adults could be due to various factors,
including chronic illness, social isolation and inadequate
social support, and elder abuse.41–44 This pattern of
increasing prevalence with increasing age has not been
reported in high-income countries, as also reported
previously.1,45
There was a varying degree of heterogeneity between
the states of India in the DALY rates for individual
mental disorders in 2017. On one hand, the population-
level burden of depressive disorders, anxiety disorders,
schizo phrenia, bipolar disorder, and eating disorders
increased in India between 1990 and 2017, with the
increase being generally higher in the more developed
states than in the less developed states. On the other
hand, the population-level burden of mental disorders
with onset in childhood and adolescence decreased by
varying degrees for the individual disorders, and this
decrease was generally smaller in the less developed
states than in the more developed states. The increase in
the burden of depressive disorders, anxiety disorders,
schizophrenia, and bipolar disorder was driven by the
ageing of the population because age-standardisation
nullified this increase. The decrease in IDID could partly
be attributed to the implementation of laws to reduce
lead contamination in the country,46,47 though this
decrease was smaller in the less developed states than in
the more developed ones. The increase in the burden of
Risk factor Proportion of total DALYs attributable to each risk factor (95% uncertainty intervals)
Both sexes Males Females
Depressive disorders Bullying victimisation 3·3% (2·0–4·9) 3·8% (2·3–5·7) 3·0% (1·8–4·4)
Depressive disorders Childhood sexual abuse 6·9% (5·7–8·2) 5·0% (4·1–6·2) 8·3% (6·6–10·3)
Depressive disorders Intimate partner violence* 4·6% (3·3–6·2) NA 8·0% (5·8–10·7)
Anxiety disorders Bullying victimisation 7·0% (4·5–9·7) 7·7% (5·0–10·7) 6·4% (4·1–9·1)
Idiopathic developmental
intellectual disability
Lead exposure 62·8% (32·2–81·2) 63·8% (32·9–82·1) 61·7% (31·7–80·4)
Data are percentage, with 95% uncertainty interval in parentheses. DALYs=disability-adjusted life-years. NA=not applicable. *Intimate partner violence in GBD 2017 was
modelled only for females.
Table 3: Percentage contribution of major risk factors to mental disorders DALYs in India, 2017

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11
eating disorders could be related to several factors,
including increasing exposure in India to global body-
image trends.37,38
India launched the National Mental Health Programme
in 1982, which was relaunched in 1996 as the District
Mental Health Programme.48 The National Mental Health
Policy was introduced in 2014,5 and a rights-based Mental
Healthcare Act in 2017, which replaced the Mental
Healthcare Act of 1987.49 The child health programme
under the National Health Mission and the National
Adolescent Health Programme include components to
address the mental health of children and adolescents.50,51
The Ayushman Bharat (Healthy India) initiative launched
in 2018 aims to provide comprehensive primary health
care and health insurance coverage for non-commu-
nicable diseases including mental disorders, which could
contribute to reducing the adverse eect of mental
disorders at the population level.52,53
Despite these eorts by the government, poor imple-
mentation of mental health services in India has been
documented, with a high treatment gap for mental
disorders, poor evidence-based treatment, and gender-
dierentials in treatment.10,12,54–58 A shortage of mental
health personnel in India exists, with two mental health
workers and 0·3 psychiatrists per 100 000 population,
which is much lower than the global average.59 Additionally,
the discriminatory attitude of health workers towards
people with mental illness60,61 and demand-side barriers
such as low perceived need for care, paucity of knowledge
of mental disorders, and stigma attached to mental
disorders are challenges that need to be addressed.61–64 An
integrated approach to detect, treat, and manage patient
needs related to mental and physical health is urgently
needed in India because people with mental disorders die
prematurely and have excess disability, though sub-
stantially more work is needed for it to be implemented on
a large-scale.61,64–66 Task-sharing with non-specialists and
appropriate training of com munity health workers can
improve mental health service provision.67,68 Importantly,
the positive association of depressive disor ders and
schizophrenia with suicide deaths, especially for females,
needs urgent attention in primary care for suicide
prevention, because Indian women have double the global
suicide death rate.21 Furthermore, telemedicine to provide
mental health services in remote and inaccessible areas,
internet-based and telephone-based helplines, and mental
health mobile apps can reduce the burden on existing
mental health services.69–71
Communities and families have an important role
in addressing mental health by reducing stigma and
discrimination, raising awareness, and promoting inclu-
sion.72,73 Community-based programmes have the poten tial
to reduce the treatment gap for mental disorders in
India.63,74,75 School-based mental health programmes can
help improve mental health in children.76 Yoga, a traditional
Indian practice, is also suggested to be potentially
beneficial for depressive disorders.77
The general limitations of the GBD methods, and those
for estimation of mental disorders, have been discussed
previously.3,17–20 A major limitation of this study is that the
population-level data on the prevalence of many mental
disorders are scant across the states of India, which might
have introduced unknown biases in our estimates.
Importantly, the GBD burden estimation for mental
disorders relies on severity distributions primarily from
high-income countries, which might not reflect the
distribution in India. Because there is a paucity of
research in India on risk factors for mental disorders,
only well established risk factors from global data that
could meet the strict risk-cause association criteria were
included in the analysis. To address these limitations
when data are scarce for a particular variable, GBD
uses covariates and other techniques that borrow strength
over space and time to arrive at the best possible
estimates. We have presented the best possible estimates
that could be modelled with the available data, which
could be improved as more population-level data become
available for mental disorders in India. It is also important
to note that the total burden of mental disorders in this
report is likely to be an underestimate, because the
methods used do not fully include the contribution of
mental disorders to mortality and morbidity from
associated physical causes.29,61,64,78 The strengths of this
study include the use of data sources in India that could
be accessed to estimate the trends and patterns of mental
disorders in every state of India, the use of the standardised
GBD methods for comparison across locations and years,
and the inclusion of a comprehensive eort that
benefitted from inputs from a network of leading experts
in India.
In conclusion, mental disorders adversely aect a
large proportion of Indians. Given the poor coverage of
mental health services, the lack of awareness, and the
stigma attached to mental disorders in the country,
India needs to invest heavily in mental health services
to facilitate prevention where possible and to provide
aordable treatment, care, and rehabilitation, as well as
to attempt integration of mental and physical health
services. The state-specific data trends in this report can
be useful for mental health policies and programme
planning at the individual state level and for India as a
whole.
India State-Level Disease Burden Initiative Mental Disorders Collaborators
Rajesh Sagar, Rakhi Dandona, Gopalkrishna Gururaj, R S Dhaliwal,
Aditya Singh, Alize Ferrari, Tarun Dua, Atreyi Ganguli,
Mathew Varghese, Joy K Chakma, G Anil Kumar, K S Shaji,
Atul Ambekar, Thara Rangaswamy, Lakshmi Vijayakumar,
Vivek Agarwal, Rinu P Krishnankutty, Rohit Bhatia*, Fiona Charlson*,
Neerja Chowdhary*, Holly E Erskine*, Scott D Glenn*, Varsha Krish*,
Ana M Mantilla Herrera*, Parul Mutreja*, Christopher M Odell*,
Pramod K Pal*, Sanjay Prakash*, Damian Santomauro*, D K Shukla*,
Ravinder Singh*, R K Lenin Singh*, J S Thakur*,
Akhil S ThekkePurakkal*, Chris M Varghese*, K Srinath Reddy,
Soumya Swaminathan, Harvey Whiteford, Hendrik J Bekedam,
Christopher J L Murray, Theo Vos, Lalit Dandona.
*Listed alphabetically

Articles
12
www.thelancet.com/psychiatry Published online December 23, 2019 https://doi.org/10.1016/S2215-0366(19)30475-4
Affiliations
Department of Psychiatry (Prof R Sagar MD), National Drug
Dependence Treatment Centre (Prof A Ambekar MD), and Department
of Neurology (Prof R Bhatia DM), All India Institute of Medical Sciences,
New Delhi, India; Public Health Foundation of India, Gurugram, India
(Prof R Dandona PhD, A Singh PhD, G A Kumar PhD,
R P Krishnankutty MPH, P Mutreja MA, A S ThekkePurakkal PhD,
C M Varghese MPH, Prof K S Reddy DM, Prof L Dandona MD);
Institute for Health Metrics and Evaluation, University of Washington,
Seattle, USA (Prof R Dandona, A Ferrari PhD, F Charlson PhD,
H E Erskine PhD, S D Glenn MSc, V Krish BA,
A M Mantilla Herrera PhD, C M Odell MPP, D Santomauro PhD,
Prof H Whiteford PhD, Prof C J L Murray MD, Prof T Vos PhD,
Prof L Dandona); Centre for Public Health (Prof G Gururaj MD),
Department of Psychiatry (Prof M Varghese MD), and Department of
Neurology (Prof P K Pal DM), National Institute of Mental Health and
Neuro Sciences, Bengaluru, India; Indian Council of Medical Research,
New Delhi, India (R S Dhaliwal MS, J K Chakma MD, D K Shukla PhD,
R Singh MCH, Prof L Dandona); University of Queensland School of
Public Health and Queensland Centre for Mental Health Research,
Brisbane, Australia (A Ferrari, F Charlson, H E Erskine,
A M Mantilla Herrera, D Santomauro, Prof H Whiteford); World Health
Organization, Geneva, Switzerland (T Dua MD, N Chowdhury MD,
S Swaminathan MD); WHO India Country Oce, New Delhi, India
(A Ganguli MPH, H J Bekedam MD); Government Medical College,
Thrissur, Kerala, India (Prof K S Shaji MD); Schizophrenia Research
Foundation, Chennai, India (T Rangaswamy PhD); SNEHA and
Department of Psychiatry, Voluntary Health Services, Chennai, India
(Prof L Vijayakumar PhD); Department of Psychiatry, King George’s
Medical University, Lucknow, India (Prof V Agarwal MD); Department
of Neurology, Medical College Baroda and Shri Sayajirao General
Hospital, Vadodra, India (Prof S Prakash DM); Department of
Psychiatry, Regional Institute of Medical Sciences, Imphal, India
(Prof R K Lenin Singh MD); Department of Community Medicine and
School of Public Health, Post Graduate Institute of Medical Education
and Research, Chandigarh, India (Prof J S Thakur MD).
Contributors
LD, RSa, and RD conceptualised the Article and drafted it with
contributions from GG, AS, AF, TD, AG, RPK, HW, HJB, and TV.
The other authors provided data, participated in the analysis, or reviewed
the findings (or a combination of these), and contributed to the
interpretation. All authors agreed with the final version of the Article.
Declaration of interests
RSD, JKC, DKS, RSi, and LD work with the Indian Council of Medical
Research, which partly funded this research. All other authors declare no
competing interests.
Acknowledgments
The research reported in this publication was funded by the Bill &
Melinda Gates Foundation and the Indian Council of Medical Research,
Department of Health Research, Government of India. The content of
this publication is solely the responsibility of the authors and does not
necessarily represent the ocial views of the Bill & Melinda Gates
Foundation, the Government of India, or the World Health Organization.
We thank the Ministry of Health and Family Welfare of the Government
of India for its support and encouragement of the India State-Level
Disease Burden Initiative, the governments of the states of India for their
support of this work, the many institutions and investigators across India
who provided data and other inputs for this study, the valuable guidance
of the Advisory Board of this initiative, and the large number of sta at
the Indian Council of Medical Research, Public Health Foundation of
India, and the Institute for Health Metrics and Evaluation for their
contribution to various aspects of the work of this initiative.
Editorial note: the Lancet Group takes a neutral position with respect to
territorial claims in published maps and institutional aliations.
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