
==== Front
Lancet Reg Health Southeast Asia
Lancet Reg Health Southeast Asia
The Lancet Regional Health - Southeast Asia
2772-3682
Elsevier

S2772-3682(24)00127-6
10.1016/j.lansea.2024.100477
100477
Articles
Economic burden of suicide deaths in India (2019): a retrospective, cross-sectional study
Nigam Anukrati abc
Vuddemarry Madhurima ad
Zadey Siddhesh sidzadey@asarforindia.org
aefg∗
a Association for Socially Applicable Research, Pune, Maharashtra, India
b Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
c PEGASUS Institute, Waterloo, Ontario, Canada
d Rajarshee Chhatrapati Shahu Maharaj Govt. Medical College and Chhatrapati Pramilatai Raje Hospital, Kolhapur, Maharashtra, India
e Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
f GEMINI Research Center, Duke University School of Medicine, Durham, NC, USA
g Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
∗ Corresponding author. ASAR, D2 Sai Heritage, New DP Road, Aundh, Pune, Maharashtra 411007, India. sidzadey@asarforindia.org
12 9 2024
10 2024
12 9 2024
29 10047719 2 2024
13 8 2024
28 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Summary

Background

India has the highest number of suicide deaths in the world. Suicide prevention requires policy attention and resource allocation. Evidence of economic losses due to disease burden can influence such allocations. We assessed the economic burden and its distribution across states and demographic groups in India.

Methods

We used the human capital approach in this retrospective cross-sectional analysis to assess the economic burden of suicide in India for the year 2019 for 28 Indian states and 3 union territories (UTs). We calculated the monetary value for the years of life lost disaggregated by states, age groups, and sexes. For sensitivity, we present a library of estimates using different discount rates, life expectancy thresholds, and estimates specific to the populations that can participate in the workforce.

Findings

The national economic burden of suicide was US$ 16,749,079,455 (95% Uncertainty Interval: 11,913,034,910–22,404,233,468). The top three states, Karnataka, Tamil Nadu, and Maharashtra, contributed to 44.82% of the total burden in India. The age group 20–34 years had the largest suicide burden and contributed to 53.05% of the overall national economic burden (US$ 8,885,436,385 [6,493,912,818–11,694,138,884]). Twenty states and UTs had a greater economic burden for females than males.

Interpretation

The current analysis ascertains a high economic burden of suicide among the Indian youth and females, necessitating concerted multisectoral efforts and immediate investments.

Funding

None.

Keywords

Suicide
India
Health economics
Human capital approach
==== Body
pmc Research in context

Evidence before this study

We conducted a PubMed search (“india [title/abstract] AND suicide [title/abstract] AND economics”) for articles published till Feb 19, 2023, that resulted in 87 titles. Additionally, relevant reports from government websites were accessed. Multiple studies have noted epidemiological patterns in fatal and non-fatal disease burden of suicide and suicidality. There were individual-level and ecological studies of sociodemographic risk and protective factors for suicide. More recently, a small number of intervention studies have investigated feasibility and efficacy of suicide prevention initiatives. There are also multiple commentaries and perspective articles forming the critical discourse on policy and program design, implementation, and challenges. However, we could not find any study of economic burden of suicide for Indian states.

Added value of this study

We present an analysis of the state-wise economic burden of suicide deaths and their patterns across population age groups and sexes in India and its states. Through comprehensive scenario and sensitivity analyses, we note that the economic burden exceeds US$ 16 billion and impacts young people the most, with a skew toward females. Our estimates depict the cost of policy inaction and form the basis for urgent resource allocation across states for suicide prevention. To our knowledge, these are the first such estimates for India.

Implications of all the available evidence

Findings from our study and previous literature show large disease and economic burden of suicides in India. Yet, investments toward prevention have been limited. Our estimates note the cost to the Indian economy due to inaction. The large economic burden noted here necessitates intersectoral involvement from the Ministries of Finance, Youth Development, Women’s Welfare, Rural Development, and Agriculture of India. Hence, intersectoral coordination, along with investment strategic scale-up, is needed to reduce the disease and economic burden of suicide.

Introduction

Suicide is among the twenty leading causes of death globally, accounting for 9.13 deaths per 100,000 people. Low-income and middle-income countries (LMICs) contribute to 79% of suicide deaths globally.1 India, the most populous lower-middle income country, contributed to 25.73% of these deaths in 2019.2 Also, the age-standardised suicide death rate in India was 13.8 per 100,000 people compared to the global rate of 9,3 making suicide a major health issue.

Suicide is the fatal outcome of ‘an intent to die’. The intention to die and the behaviours associated with it constitute suicidality (ideation, planning, and attempts), which predisposes a person to suicide death. It is a complex problem with multiple biological, psychological, and social factors interacting with each other to determine the differential levels of risk and disease burdens across population groups. This can be partly observed in the differential patterns of mortality across various sociodemographic characteristics. In 2019, Indian men had 15.35 deaths per 100,000, while the rate among women was 12.67.3 Globally, the suicide death rate among men was 12.6 while that among women, it was 5.4.2 Hence, while India follows the global men-women suicide mortality differential, both Indian men and women have higher suicide mortality rates than their global counterparts. India’s National Crime Records Bureau (NCRB) notes that young Indians are particularly vulnerable to suicide.4 Across socioeconomic groups, suicide deaths are more common among those with merely primary education, unemployed persons, and rural residents.5,6 Past studies also suggest wide mortality heterogeneity by states, religion, and social groups.7 NCRB notes that social pressures including family problems, poverty, unemployment, marriage-related issues, unacceptability toward ‘love affairs’, and other reasons account for over half the suicide deaths, while illness and addictions account for about 25%. Among women, specific contributing reasons include marriage and dowry-related issues. While varying across age groups and socio-economic classes, hanging and poisoning are more common than other means of suicide.

The dominant role of social factors for suicide is not specific to India. However, it might be most clearly visible there due to resource constraints, large population size, and chronic class-wealth disparity. Suicide in LMICs is linked to society-wide financial constraints, poverty, unemployment, and limited financial and social freedoms for women.8,9 Hence, policy action for suicide is inherently tied to other components of public policy, beyond health. Within health policymaking, suicide sits at the intersection of mental health and injury prevention.

Even though developing countries have taken a back seat in public mental health studies in the previous years, suicide mortality in developing countries has attracted much more attention among scholars and policymakers.8 Considering biopsychosocial determinants, an integrated, multi-sectoral, holistic, and patient-centered approach to mental healthcare was envisioned in India’s National Mental Health Policy (NMHP) in 2014, which included reducing the incidence of suicide attempts and deaths as an aim.10,11 However, its implementation has been challenging due to the scarcity of workforce, difficulty in integrating Mental Health Care (MHC) services with primary health care, and lack of concerted efforts by shareholders.12 Subsequently, in 2017, the Mental Health Care Act (MHCA) took a human rights-based approach to decriminalise suicide and uphold several patient rights for persons with severe mental illness.13 However, MHCA’s success is also marred by ambiguity in its implementation.14 India’s latest more directed effort was introduced in 2022: National Suicide Prevention Strategy (NSPS).15 NSPS targets to reduce suicide mortality by 10% by 2030, in line with the Sustainable Development Goals. To realise the goal, NSPS lays down an action framework including immediate, intermediate, and long-term goals with an implementation timeline. However, there have been growing concerns about barriers to NSPS implementation at the grassroots level.16,17

Failures to implement NMHP, MHCA, and NSPS are tied to limited financing. Mental health is underfunded in India, with an annual allocation of <1% of the health budget and no clarity over the allocation of funds to meet the NSPS objectives.18 Limited financing, in part, is due to the failure to recognise suicide as a societal concern with a direct impact on the country’s economy. A way to acknowledge suicide as a major societal concern is to quantify its economic burden. Previously, the economic burden of suicide deaths in 54 African countries was estimated to be 0.12% of the region’s Gross Domestic Product (GDP) in 2019.19 A similar analysis of 11 countries with the highest human development index estimated an economic loss of US$ 5.53 billion.20 A global analysis of the economic burden of self-harm among youth (those up to 24 years of age) estimates the global burden to be $251,779,943,868, with India being the largest contributor.21 Elucidating the economic burden of suicide can be instrumental in advocating for investments in suicide prevention policies.

India is the single largest contributor to suicide mortality, yet an economic burden assessment is missing. We had two important aims in this study: (i) To estimate India’s economic burden of suicide and (ii) to understand the patterns across Indian states, age groups, and sexes.

Methods

Study area and population

This retrospective cross-sectional economic burden assessment included 28 Indian states and three union territories that had 195,336 suicide deaths in 2019. Age group-wise rates of deaths and years of life lost (YLLs) for 2019 are shown in Supplementary Fig. S1. Expectedly, age groups 15–39 years have higher YLL rates than the older age groups. However, the death rates in the age groups 20–39 years are also higher than other adult age groups (except > 80 years).

Data source and variables

Table 1 details the variables included in the analysis and their data sources. The Global Burden of Disease (GBD) 2019 study provides modeled estimates of suicide deaths for both sexes in 28 Indian states and three union territories.22 While the GBD methods have been detailed previously,22 the study uses an ensemble approach to model causes of death using different covariates at multiple geographic levels. In GBD 2019, covariates for the ‘self-harm’ model included per capita alcohol consumption, depression prevalence, healthcare access and quality index, and sociodemographic index among others.Table 1 Variables and data sources.

Variable	Description	Data source	
Number of suicide deaths	Estimated mean and 95% uncertainty interval values of suicide deaths by age and sex were extracted for India for 2019.	Institute of Health Metrics and Evaluation (IHME) -Global Burden of Disease (GBD) 2019 study22	
Indian states extracted	Data was extracted for 28 Indian states and 3 union territories (UTs).
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chhattisgarh
Delhi
Goa
Gujarat
Haryana
Himachal Pradesh
Jammu and Kashmir (J&K) and Ladakh
Jharkhand
Karnataka
Kerala
Madhya Pradesh
Maharashtra
Manipur
Meghalaya
Mizoram
Nagaland
Odisha
Puducherry
Punjab
Rajasthan
Sikkim
Tamil Nadu
Telangana
Tripura
Uttar Pradesh
Uttarakhand
West Bengal	Institute of Health Metrics and Evaluation (IHME) -Global Burden of Disease (GBD) 2019 study22	
Discount rates (r)	3% for primary analysis and 5% and 10% for sensitivity analysis	Similar to what has been used in previous analysis19	
Gross domestic product (GDP) per capita	State-wise GDP per capita was extracted for 28 states and 3 UTs.	National Health Accounts 2021 Report23
Table: A.7	
Government health expenditure (GHE)	State-wise GHE was extracted for 28 states and 3 UTs		
Non-health GDP	State-wise non-health GDP was calculated as the difference between the GDP of each state and the GHE of each state	Author’s calculations	
Years of life lost (k)	Years of life lost due to premature mortality. This is calculated as the difference between life expectancy at birth and average age at death	Author’s calculations	
Life expectancy at birth (LE)	State-wise mean LE at birth was extracted for 28 Indian states and three UTs.	Institute of Health Metrics and Evaluation (IHME) GBD 201924	
	The highest LE globally, reported for Switzerland -Males: 81.75 years,
Females: 85.27 years.		
	Highest LE for any Indian state/UT.
Males: 71.24 years for Delhi and Goa,
Females: 77.82 years for Delhi and Goa.		

Analytical framework

There are multiple ways to measure the economic burden of diseases and injuries. The cost of illness approach typically considers direct and indirect costs including lost productivity from a microeconomic perspective. While the human capital approach (HCA) takes more of a macro perspective to assess the overall loss to the country’s economy from the disease burden. We assessed the economic burden of suicide deaths using HCA. HCA considers the economic productivity of a person’s skill or educational training and can be used to estimate the productivity losses for the years of life lost due to premature mortality.25 HCA has been previously used to estimate the economic burden of several diseases, including non-communicable diseases, injuries, and neglected tropical diseases across countries.21,26,27 Recently, it has also been used to estimate the burden of suicides in Africa and eleven countries with the highest human development index values19,20 and to understand the economic impact of implementation of suicide prevention strategies in Canada.28

HCA can be operationalised in multiple ways with subtle differences in the underlying assumptions. Our approach for the main analysis closely followed that described by Kirigia and colleagues19 relies on YLLs and considered all ages for the sake of completeness of estimates and simplicity of analysis. A simpler approach could consider aggregate disability-adjusted life years (DALYs) instead of discounted YLLs split by age groups and sexes.29 Other approaches use variations of YLLs assuming different life expectancy levels. Studies from High Income Countries (HICs) use years of productive life lost (YPLLs) which can be adjusted for average worker productivity, time spent being economically active, and employability of people with mental conditions and disabilities among other factors.20,30,31 Such assumptions could make the estimates more accurate, only if high-fidelity data required for those assumptions are available. As detailed ahead, the current study considers multiple sensitivity or scenario analyses to investigate how the economic burden of suicide changes under multiple assumptions.

Main analysis

Using HCA, the total monetary value of years of life lost (TMVYLL) was calculated for each state in India for the year 2019. Calculations were conducted following the approach described by Kirigia and colleagues.19 TMVYLL for each state (m) and sex (s) was calculated as the sum of the monetary value of years of life lost (MVYLL) for each age group (j) spanning 5-year intervals from 10 to >95 years (Equation (1)). MVYLL for each state (m), each sex (s), and each age group (j) was calculated using the formula in Equation (2). MVYLL was calculated as the product of the non-health GDP per person and the number of suicide deaths after accounting for discount rates. Discount rates are calculated to attribute to the loss of opportunity costs and positive return on investment.32 In healthcare, discounting rates indicate that the opportunity costs and investments could have been made elsewhere to boost the economy.32 We used discount rates similar to those used by Kirigia and colleagues19 that are prevalent in the literature. Discounting was done by taking the inverse of the discount rate to the power of k for a range from 1 to k, where k is the final year of the years of life lost, which is calculated as the difference between life expectancy (LE) and the average age of death (Equation (3)). The midpoint of age intervals was taken as the average age of death by suicide in each age category (j) per state (m) and per sex (s).(Equation 1) TMVYLLs,m=Σ(MVYLLj,s,m)

(Equation 2) MVYLLj,s,m=∑i=1kj,s,m{[1/(1+discountrate)kj,s,m]×non−healthGDPperpersons,m×SDj,s,m}

(Equation 3) kj,s,m=Lifeexpectancy−averageageofdeathj,s,m

MVYLL and TMVYLL were calculated for 28 states and three UTs, eighteen 5-year age groups, and for both sexes (male and female). For the primary analysis, a discount rate of 3% and state-wise mean LE values were used for the eighteen 5-year age groups and nine 5-year working age groups for both sexes (male and female). Five UTs were excluded due to the unavailability of GDP for UTs without legislature.23 State and UT values were added to get the national (all-India) value. Monetary values are presented in Indian National Rupees (INR) and United States Dollars (US$) at an exchange rate of 1 US$ = 70.394 INR for 2019.33

Uncertainty analysis

Uncertainty was propagated from the suicide death estimates from GBD. Hence, we calculated the 95% uncertainty intervals for MVYLL and TMVYLL using the 95% uncertainty lower and upper bounds of suicide death estimates.

Sensitivity analysis

For sensitivity analysis, four scenarios were considered to present a library of estimates rather than single-point estimates. In Scenario 1, MVYLL and TMVYLL were calculated using 5% and 10% discount rates for all age groups. Scenario 2 involved similar discount rates to scenario 1, but the calculations were restricted to the working age group (20–64 years old). We also considered different ways to calculate k based on different life expectancy thresholds: global highest life expectancy (Switzerland) and highest life expectancy among Indian states and UTs (Delhi and Goa) in 2019.24 In scenario 3, k was calculated using the global highest life expectancy in 2019–Switzerland’s life expectancy values (81.75 years for males and 85.27 years for females) at 3, 5, and 10% discount rates. In scenario 4, similar calculations were conducted using the highest expected life expectancy for Indian states in 2019–Delhi and Goa, with a life expectancy of 71.24 years for males and 77.82 for females.

Role of funding source

There was no funding source for this study.

Results

Economic burden of suicide in India and its states

The total economic burden of suicide in India in 2019 was US$ 16,749,079,455 (95%UI: 11,913,034,910–22,404,233,468). Across states, this varied from US$ 2,785,582,698 (1,896,469,577–3,633,029,742) in Karnataka to US$ 9,322,913 (5,216,976.099, 22,566,267.17) in Nagaland (Fig. 1). Following Karnataka, Tamil Nadu (US$ 2,545,351,034 [1,893,531,981–3,245,577,321]) and Maharashtra (US$ 2,175,794,678 [1,613,298,513–2,848,295,940]) had the largest burdens. The top three states contributed to 44.82% of the total economic burden of suicide in India. Supplementary Fig. S2 presents the values in INR.Fig. 1 Total monetary value of years of life lost (TMVYLL) in US$ to suicide across Indian states in 2019. 28 states and three union territories are colored by the increasing color intensity, indicating a higher economic burden. Missing data for union territories is shown in gray. Our primary analysis used a 3% discount rate and assumed the respective state life expectancy thresholds obtained from Institute for Health Metrics and Evaluation (IHME), Global Burden of Disease Study (GBD) 2019, and the GDP data obtained from the National Health Accounts 2021 Report.

Economic burden of suicide across age groups

Age groups 20–24 (US$ 3,376,431,276 [2,494,559,929–4,459,891,732]), 25–29 (US$ 3,049,538,782 [2,255,274,912–3,977,288,605]), and 30–34 years (US$ 2,459,466,327 [1,744,077,978–3,256,958,546]) had large values contributing to 53.05% of the total suicide-related economic burden in India (Fig. 2A). Similarly, focusing on the working age group (age 20–64 years), the national economic burden of suicide was US$13,875,427,201 (9,796,185,919–18,609,153,542), contributing to 82.84% of the national economic burden of suicide across all age groups. Within the working age groups, 20–24 years (US$ 3,376,431,276 [2,494,559,929–4,459,891,732]), 25–29 years (US$ 3,049,538,782 [2,255,274,912–3,977,288,605]), and 30–34 years (US$ 2,459,466,327 [1,744,077,978–3,256,958,546]) had large burdens (Fig. 2B). Young adults from 20 to 34 years of age contributed 53.05% of the total economic burden. The top three states (Karnataka, Tamil Nadu, and Maharashtra) in each of these age groups were similar to the top three states for the national burden of suicide (see the Supplementary Data File). Overall, these three age groups for the top three states contribute to 23.88% of the total economic burden of suicide in India. Supplementary Fig. S3 presents the values in INR for all age groups (Supplementary Fig. S3A) and working age groups (Supplementary Fig. S3B).Fig. 2 Monetary value of years of life lost (MVYLL) in US$ due to suicide in Indian states in 2019 across (a) all age groups and (b) working age groups at a 3% discount rate. J & K: Jammu and Kashmir, USD: US$.

Economic burden of suicide across sexes

Nationally, the economic burden was US$ 8,674,951,237 (6,167,374,882–11,604,176,049) (51.79%) for females and US$ 8,074,128,218 (5,745,660,028–10,800,057,419) for males. Most states had a higher economic burden for females than males (Fig. 3). The top three states were Karnataka (females: US$ 1,445,764,279 (982,652,673–1,886,614,313); males: US$ 1,339,818,419 (913,816,905–1,746,415,429), Tamil Nadu (females: US$ 1,321,106,839 [982,040,316–1,685,327,296]; males: US$ 1,224,244,195 [911,491,665–1,560,250,024]), and Maharashtra (females: US$ 1,138,785,867 [844,057,603–1,491,120,206]); males: US$ 1,037,008,810 [769,240,910–1,357,175,734]). Nine states/UTs (Arunachal Pradesh, Goa, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura, and Puducherry) had a higher burden among males than females. Supplementary Fig. S4 presents the corresponding burden differences in INR.Fig. 3 Comparison of the state-wise total monetary value of years of life lost (TMVYLL) of suicide in US$ across females (orange) and males (green) in 2019. J & K: Jammu and Kashmir, USD: US$.

Age and sex intersections

The analysis of 36 age-sex intersections found that the top three age groups with large economic burdens were 20–24, 25–29, and 30–34 across the male and female sexes (Fig. 4). Out of the 36 age-sex intersections (obtained as a product of two sexes and 18 age groups) considered, 18 age-sex intersections of females contributed to 51.79% of the total economic burden of suicide in India. Females in the age group 20–24 years (US$ 1,733,059,407 [1,280,428,732–2,289,152,179]) had the highest economic burden of suicide nationally, followed by those in the age groups 25–29 years (US$ 1,574,155,849 [1,164,206,547–2,053,008,419]) and 30–34 years (US$ 1,278,970,341 [907,007,321–1,693,634,064]). Similarly, among males, the age group 20–24 years had the highest economic burden of suicide in India (US$ 1,643,371,869 [1,214,131,197–2,170,739,554]), followed by the 25–29 years and 30–34 years with the economic burden of (US$ 1,475,382,933 [1,091,068,365–1,924,280,186]) and respectively (US$ 1,180,495,987 [837,070,656–1,563,324,482]). Supplementary Fig. S5 presents the values for the intersection of age and sex in INR.Fig. 4 Monetary value of years of life lost (MVYLL) in US$ due to suicide in Indian states in 2019 across all age groups for each sex at a 3% discount rate. J & K: Jammu and Kashmir, USD: US$.

Sensitivity analyses

In Scenario 1, looking at all age groups using 5% and 10% discount rates, we observed that with increasing discount rates, the absolute values of TMVYLL reduced compared to that in the primary analysis (Supplementary Figs. S6–S8). However, overall patterns were retained (Supplementary Figs. S9–S14). At a discount rate of 3%, the economic burden of the working age groups contributed to 82.87% of India’s total economic burden across all age groups in 2019 (Supplementary Figs. S15–S17). Scenario 2, which considered only the working age groups at 5% and 10% discount rates, resulted in a similar pattern to that of Scenario 1, showing reductions in TMVYLL with increasing discount rates (Supplementary Figs. S18–S23). Scenario 1 noted a 24.67% reduction in TMVYLL when the discount rate changed from 3 to 5% and a further 37.35% reduction for the 10% discount rate. Scenario 2 observed a 25.14% reduction in TMVYLL when the discount rate changed from 3 to 5% and a 41.76% reduction in TMVYLL with a discount rate change from 5 to 10%.

Scenario 3 considered the world’s highest life expectancy according to Institute for Health Metrics and Evaluation (IHME), USA, at 3%, 5%, and 10% discount rates. The economic loss was higher than that observed with the Indian state/UT’s expected life expectancy thresholds. However, the patterns across age, sex, and states were similar to those observed in Scenarios 1 (All age groups, Supplementary Figs. S6–S13 and S24–S32) and 2 (Working age groups, Supplementary Figs. S15–S23 and S33–41). Scenario 4 used India’s highest state Life Expectancy in 2019 at a rate of 3, 5, and 10%. Scenario 4, based on India’s highest state life expectancy, calculated TMVLL at 3, 5, and 10% discount rates. Here, we observed that economic loss was higher than in our primary analyses. However, the patterns were similar to Scenarios 1 (All age groups, Supplementary Figs. S6–S14 and S42–S50) and 2 (Working age group, Supplementary Figs. S15–S23 and S51–S59).

Discussion

In India, the economic burden of suicide in 2019 was over US$ 16 billion. A greater portion of this burden fell on those in the 20–24 age group, skewed toward females. Karnataka, Tamil Nadu, and Maharashtra, due to their high number of suicide deaths, large population sizes, and high GDPs, had a greater share of the burden among states. With the sensitivity analyses, we present a library of estimates accounting for the effects of different assumptions. First, we show the distribution of values across two other discounting rates of 5% and 10%. Second, we consider the working age group of 20–64 years contributing to the country’s economic productivity. Further, we consider the influence of life expectancy thresholds. Across these scenarios, the value of the national economic burden varies from US$ 6,109,808,484 (95%UI: 4,288,238,366–8,225,299,178) in the case of the working age group at a 10% discount rate for observed life expectancy in 2019 to US$ 18,790,992,230 (13,344,553,064–25,147,450,756) for all ages at a 3% discount rate with aim to reach globally highest life expectancy.

The economic burden for suicide deaths has been estimated using similar methods for other countries and regions. In 2017, 54 African countries had an overall burden of US$ 6,989,963,325, with the highest burden in Egypt (US$ 1,272,197,958 in 2019).19 Present analyses estimate the national burden in India to be 16,749,079,455 US$. Our analysis noted four Indian states, Karnataka (US$ 2,785,582,698 [95%UI: 1,896,469,577–3,633,029,742]), Tamil Nadu (US$ 2,545,351,034 [1,893,531,981–3,245,577,321]), Maharashtra (US$ 2,175,794,678 [1,613,298,513–2,848,295,940]), and Gujarat (US$ 1,479,678,439 [1,125,190,862–1,923,860,517]) with higher total monetary burden than Egypt. The higher values for these states cannot be attributed to the number of suicide deaths as Karnataka (1310 deaths), Tamil Nadu (1457 deaths), Maharashtra (730 deaths), and Gujarat (785 deaths) had fewer deaths in 2019 than Egypt in 2017 (4756 deaths).

In another study, the average value of lost productivity due to suicide in the age group 15–24 years was estimated to be US$ 820,729 in 2019 per death across ten countries with the highest human development index.20 The average cost per suicide death in India for the same age group (15–24 years) amounts to US$ 2,871,814. These values should be compared with caution since the methods employed in both analyses differ in their assumptions about lost productivity, with our study having a more liberal estimate.

Further, a previous global analysis of youth self-harm estimated India to have the largest economic burden of US$ 71,098,857,448 (60,118,492,219–83,332,732,126) in 2019 in the 10–24 age group.21 The current analysis places the financial burden of suicide deaths in the age group of 10–24 years at US$ 5,828,762,229 (4,337,700,633–7,635,194,303). The significant difference is due to the use of aggregate disability-adjusted life years. Additionally, there was a lack of discounting, use of appropriate life expectancy thresholds, and consideration for state-wise differences in GDP in the previous analysis. Our methods are conservative and more appropriate for noting the burden that can be potentially prevented.

The economic burden of suicides in India should be an impetus for investing in suicide prevention. Our estimates note the cost to the Indian economy due to inaction. Despite an existing National Suicide Prevention Strategy, barriers to its implementation are evident and widespread.17 One critical barrier is poor financing. This is mainly due to the failure to acknowledge suicide as a societal problem requiring concerted attention beyond the health ministry. The large economic burden noted here necessitates intersectoral involvement from the Ministries of Finance, Youth Development, Women’s Welfare, Rural Development, and Agriculture in India. Hence, intersectoral coordination, along with investment strategic scale-up, is needed to reduce the disease and economic burden of suicide.

In the broader health and public policy discourse, whether there is an ethical basis to value human lives in monetary terms and how such an exercise should be conducted and used further, are certainly debatable, especially in the diverse socio-cultural contexts across LMICs. Hence, debate on the ethical use of economic arguments for health is needed in India. Our perspective while presenting these economic burden estimates has been to note the cost of policy inaction. Public health ethics guide that suicide prevention should be a policy priority, regardless of the problem’s magnitude. However, for decision-makers allocating limited budgets to competing social issues, who intend to see greater returns for the public, suicide prevention can get off the priority. The current study adds to the toolbox of suicide prevention and mental health advocates who typically rely on ethical, medical, and public health, development, and social well-being arguments and evidence to invest urgently in suicide prevention.

India’s NSPS lists wide-ranging collaborative interventions that can be implemented to achieve a 10% reduction in suicide mortality in a time-bound manner. As noted earlier, different populations are at different levels of risk for suicide owing to differences in underlying biopsychosocial pathways, access to means of suicide, and lethality of those means. Hence, a menu of interventions is needed for appropriate and effective suicide prevention. The current study strongly advocates for investments in suicide prevention. However, it is beyond our scope to recommend a selection of specific preventive interventions. More rigorous assessments for optimal and culturally acceptable resource allocations should be conducted in the future to prioritise interventions with reliable evidence on effectiveness, cost-effectiveness, and implementation feasibility.

This is a novel analysis providing a comprehensive library of economic burden estimates across age groups, sexes, and geographic regions within India. The extensive scenario or sensitivity analyses and uncertainty analyses ensure the robustness of the findings. However, this study has multiple limitations. Our HCA is agnostic to determinants of health and focuses only on age, sex, and the economy of the Indian state or UT. As observed above, the death rates are higher in the 20–34 age groups than in pediatric or middle-aged people. So, these agree groups, which also fall in the working ages, contribute to a large portion of YLLs due to their large population share and high suicide mortality rates. Age and sex are relevant as a lot of young people are dying with a higher number of female deaths which warrants healthcare investments in mental health. This is a cross-sectional analysis wherein the cumulative losses over the years were not calculated. Only data from 2019 was included due to the unavailability of more recent estimates during the analysis, and hence, would have missed the impact of COVID-19 pandemic. Only suicide deaths were considered for calculations excluding the burden of non-fatal self-harm behaviours. For calculating economic burden, we used HCA which estimates lost productivity for the working age groups in the population. An alternative and arguably more comprehensive approach is called value-of-life-year or full-income analysis.34 We used HCA given that it is a well-defined methodology for LMICs. We considered GBD 2019 estimates over other data sources such as the NCRB reports and Million Death Study (MDS) due to known underreporting issues in NCRB and lack of recent data in the MDS.6,35,36 Additionally, using GBD estimates also makes our findings more comparable with those from similar studies conducted in other countries and regions. Furthermore, economic burden estimates for social groups, wealth quintiles, religions, etc. Could not be calculated due to the lack of such data.

The large economic burden of suicide deaths in India notes the cost of inaction. The cost of inaction translates to a high number of preventable suicide deaths among working-age males and females that burden the country’s growth. Advocates can use these estimates for increased financing of suicide prevention efforts in the most populous country.

Contributors

Conceptualization: SZ; Data curation: AN, MV; Formal Analysis: AN; Investigation: AN, SZ; Methodology: AN, SZ; Project administration: MV; Resources: SZ; Supervision: SZ; Visualization: AN; Writing—original draft: AN, MV; Writing—review & editing: All authors.

Data sharing statement

The analysis code is available at https://github.com/anukratinigam/mh_burden_india_2019. The data used and generated through this analysis is publicly available at Harvard Dataverse (https://doi.org/10.7910/DVN/EVZCQV).

Editor note

The Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations.

Declaration of interests

SZ is the Co-founding Director of the Association for Socially Applicable Research (ASAR). He also serves as the Permanent Council Member, The G4 Alliance Chair, SOTA Care in South Asia Working Group, The G4 Alliance, and the Drafting Committee Member for Maharashtra State Mental Health Policy. The other authors declare no conflicts of interest. There was no funding source for this study.

Appendix A Supplementary data

Supplementary Figs. S1–S59

Acknowledgements

None.

Appendix A Supplementary data related to this article can be found at https://doi.org/10.1016/j.lansea.2024.100477.
==== Refs
References

1 World Health Organization Suicide worldwide in 2019: global health estimates 2021 World Health Organization https://www.who.int/publications/i/item/9789240026643
2 Institute of Health Metrics and Evaluation Global burden of diseases 2019 2019 https://vizhub.healthdata.org/gbd-compare/
3 Institute for Health Metrics and Evaluation GBD 2019 Results - VizHub. GBD 2019 results tool 2020 https://vizhub.healthdata.org/gbd-results/?params=gbd-api-2019-permalink/91f6967efb4e64a836428f2f312d5134
4 National Crime Records Bureau (Ministry of Home Affairs) Government of India Accidental deaths and suicides in India 2022 2023 https://ncrb.gov.in/accidental-deaths-suicides-in-india-year-wise.html?year=2022&keyword=
5 Ministry of Home Affairs ADSI-2021 | national Crime Records Bureau 2021 https://ncrb.gov.in/en/ADSI-2021
6 Patel V. Ramasundarahettige C. Vijayakumar L. Suicide mortality in India: a nationally representative survey Lancet 379 2012 2343 2351 10.1016/S0140-6736(12)60606-0 22726517
7 Arya V. Page A. Dandona R. Vijayakumar L. Mayer P. Armstrong G. The geographic heterogeneity of suicide rates in India by religion, caste, tribe, and other backward classes Crisis 40 2019 370 374 10.1027/0227-5910/a000574 30813825
8 Iemmi V. Bantjes J. Coast E. Suicide and poverty in low-income and middle-income countries: a systematic review Lancet Psychiatr 3 2016 774 783 10.1016/S2215-0366(16)30066-9
9 Meda N. Miola A. Slongo I. Zordan M.A. Sambataro F. The impact of macroeconomic factors on suicide in 175 countries over 27 years Suicide Life Threat Behav 52 2022 49 58 10.1111/sltb.12773 34032310
10 Ministry of Health and Family Welfare National mental health policy of India 2014 https://www.nhp.gov.in/sites/default/files/pdf/national%20mental%20health%20policy%20of%20india%202014.pdf
11 Directorate General Of Health Services National mental health program 1982 http://dghs.gov.in/content/1350_3_NationalMentalHealthProgramme.aspx
12 Gupta S. Sagar R. National mental health policy, India (2014): where have we reached? Indian J Psychol Med 44 2022 510 515 10.1177/02537176211048335 36157023
13 Ministry of Law and Justice, India India code: mental healthcare Act, 2017 2017 https://www.indiacode.nic.in/handle/123456789/2249
14 Mahajan S. Mental healthcare act: supreme court seeks explanation from centre on validity of provision decriminalising attempt to commit suicide Bar Bench 2020 published online Sept 11 https://www.barandbench.com/news/litigation/supreme-court-centre-notice-mental-healthcare-act-attempt-suicide
15 Ministry of Health and Family Welfare National suicide prevention strategy 2022 https://www.mhinnovation.net/resources/indias-national-suicide-prevention-strategy#:∼:text=This%20national%20strategy%20aims%20to,suicides%20during%20COVID%2D19%20pandemic
16 Vijayakumar L. Chandra P.S. Kumar M.S. The national suicide prevention strategy in India: context and considerations for urgent action Lancet Psychiatr 9 2022 160 168 10.1016/S2215-0366(21)00152-8
17 Ransing R. Arafat S.M.Y. Menon V. Kar S.K. National Suicide Prevention Strategy of India: implementation challenges and the way forward Lancet Psychiatr 10 2023 163 165 10.1016/S2215-0366(23)00027-5
18 Shastri M. Mind matters: India’s mental health budget crisis PLoS Blogs 2023 published online May 25 https://speakingofmedicine.plos.org/2023/05/25/mind-matters-indias-mental-health-budget-crisis/
19 Kirigia J.M. Muthuri R.D.K. Muthuri N.G. The monetary value of human lives lost to suicide in the African continent: beating the African war drums Healthcare (Basel) 8 2020 84 10.3390/healthcare8020084 32252495
20 Doran C.M. Kinchin I. Economic and epidemiological impact of youth suicide in countries with the highest human development index PLoS One 15 2020 e0232940 10.1371/journal.pone.0232940
21 Zadey S. The global economic burden of youth self-harm: a systematic analysis of 204 countries and territories for 2019 HPHR 2023 10.54111/0001/SSS1
22 GBD 2019 Diseases and Injuries Collaborators Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019 Lancet 396 2020 1204 1222 10.1016/S0140-6736(20)30925-9 33069326
23 National Health Systems Resource Centre National health accounts estimates for India (2019-2020) 2023 Ministry of Health and Family Welfare, Government of India New Delhi https://main.mohfw.gov.in/sites/default/files/5NHA_19-20_dt%2019%20April%202023_web_version_1.pdf
24 Global Burden of Disease Collaborative Network Global burden of disease study 2019 (GBD 2019) life expectancy and healthy life expectancy 1990-2019 2020 Institute for Health Metrics and Evaluation (IHME) 10.6069/5r23-rq49
25 Mushkin S.J. Collings F.D. Economic costs of disease and injury Public Health Rep 74 1959 795 809 PMID: 14425499 14425499
26 Bloom D.E. Cafiero-Fonseca E.T. Candeias V. Economics of non-communicable diseases in India: the costs and returns on investment of interventions to promote healthy living and prevent Treat, and manage NCDs 2014 published online Nov https://www3.weforum.org/docs/WEF_EconomicNonCommunicableDiseasesIndia_Report_2014.pdf#:∼:text=India%20faces%20the%20human%20and%20economic%20threat%20posed,injuries%20and%20communicable%2C%20maternal%2C%20prenatal%2C%20and%20nutritional%20conditions
27 Kirigia J.M. Sambo H.B. Sambo L.G. Barry S.P. Economic burden of diabetes mellitus in the WHO African region BMC Int Health Hum Rights 9 2009 6 10.1186/1472-698X-9-6 19335903
28 Vasiliadis H.-M. Lesage A. Latimer E. Seguin M. Implementing suicide prevention programs: costs and potential life years saved in Canada J Ment Health Policy Econ 18 2015 147 155 PMID: 26474050 26474050
29 Dalal K. Svanström L. Economic burden of disability adjusted life years (DALYS) of injuries Health 7 2015 487 494 10.4236/health.2015.74058
30 Łyszczarz B. Abdi Z. Factors associated with out-of-pocket health expenditure in polish regions Healthcare (Basel) 9 2021 1750 10.3390/healthcare9121750 34946475
31 Kinchin I. Doran C.M. The cost of youth suicide in Australia Int J Environ Res Public Health 15 2018 672 10.3390/ijerph15040672 29617305
32 Attema A.E. Brouwer W.B.F. Claxton K. Discounting in economic evaluations Pharmacoeconomics 36 2018 745 758 10.1007/s40273-018-0672-z 29779120
33 Webster I. $3,000,000 in 2005 → 2020 | inflation calculator 2023 published online Aug 13 https://www.officialdata.org/us/inflation/2005?endYear=2020&amount=3000000
34 Jamison D.T. Summers L.H. Alleyne G. Global health 2035: a world converging within a generation Lancet 382 2013 1898 1955 10.1016/S0140-6736(13)62105-4 24309475
35 Arya V. Page A. Armstrong G. Kumar G.A. Dandona R. Estimating patterns in the under-reporting of suicide deaths in India: comparison of administrative data and Global Burden of Disease Study estimates, 2005-2015 J Epidemiol Community Health 2020 10.1136/jech-2020-215260 published online Nov 30
36 Armstrong G. Vijayakumar L. Suicide in India: a complex public health tragedy in need of a plan Lancet Public Health 3 2018 e459 e460 10.1016/S2468-2667(18)30142-7 30219339
