Mental Health in India: The Pathway to Zero : Preventive Medicine: Research & Reviews

Introduction

Mental illnesses are the main aetiologies of the non-fatal disease burden in India.^[1] In 2017, in India, 197.3 million people were estimated to have mental illnesses of varying severity,^[1] with a disability-adjusted life years (DALYs) rate of 2,443.^[2] In comparison, in 2019, the global average age-standardised DALY Rate for mental illness was 1,427 among males and 1,703 for females.^[3] DALYs are the summation of the years lived in an imperfect state of health with illness or injury and the years of life lost due to it.^[4] The DALY Rate is defined as DALYs per 100,000 population.^[4]

This article aims to identify a set of evidence-based interventions that address the high risk factors of mental health in India and reduce the burden to zero (as measured by DALY).

Materials and Methods

The authors started with a review of existing models to examine the development of poor mental health. The Bio-Psycho-Social Model developed by American psychiatrist George Engel in 1977 highlights the interplay between biological, social, psychological and economic factors that lead to the development of poor mental health conditions.^[5] In the Indian context, mental health situation requires a similar multi-faceted approach.^[6]Table 1 lists the risk factors that are most likely to impact mental health in India based on these models.

With India’s population is expected to touch 1.5 billion by 2040,^[7] and risks overwhelming the entire health system with an exclusively recovery focused approach. Therefore, the authors present a strategy that comprehensively addresses these risk factors across four dimensions: (i) Resilience: Building the population’s resilience, particularly among young people, to withstand psychological, social and economic stressors. Most of the interventions here will be drawn from the domain of social determinants of health, (ii) Reduce: Strategies that reduce the extent to which the population is exposed to pathogenic stress and other external triggers which can lead to mental illnesses. Here, the interventions will be drawn from the domains of social determinants of health and public health, (iii) Recognise: Early recognition of the presence of risk factors (biological, psychological, social and economic) and vulnerability to mental illnesses within specific groups of individuals so that a rapid response can be mounted without waiting for the situation to deteriorate and for any illness to manifest. Public health and primary care domains will provide most of these interventions, (iv) Recovery: Pathways that focus on making available the best possible recovery pathways to individuals who acquire one or the other mental illnesses. The interventions here will be drawn from the primary, hospital and long-term care domains. These dimensions are translated into real-world domains-(i) social determinants of health, (ii) public health, (iii) primary care, (iv) hospital care and (v) long-term care.

The authors used a pragmatic approach^[8] to identify effective interventions that will address these risk factors. They began with the references used in a course on public mental health taught by the second author and used a snowballing approach to discover additional references from those.^[9] They also consulted several search engines and online databases, including Blueprints,^[10] SAMHSA,^[11] PubMed, the Welch Medical Library at the Johns Hopkins School of Medicine^[12], Google and Google Scholar. This was followed by an iterative process involving multiple consultations with experts from organisations such as the Banyan Academy of Leadership in Mental Health,^[13] Centre for Mental Health Law and Policy,^[14] Schizophrenia Research Foundation,^[15] Possible,^[16] and the National Institute of Mental Health and Neuro Sciences.^[17] The interventions were examined for their potential size of impact, ease of implementation, and the strength of the evidence base. Only those with a material size of impact were retained, the other two criteria were used to group the retained interventions into different sets.

Finally, the authors attempt a simulation exercise to estimate the effect of all retained interventions, individually and collectively, on the overall burden of mental illness in the country by 2040 through a modelling exercise. The model builds off from the current prevalence of mental illness, distributed by the level of the ten most prevalent illnesses. Based on the Lancet crude DALY in India, the authors assume that by the year 2040, all the states will move towards the highest state burden to estimate the DALY burden 15 year later. In consultation with senior psychiatrists, the authors ascertain the frequency of treatment and per unit cost for a premium facility in India – serving as an outermost estimate of the price range. With these assumptions, the model calculates the cost per capita, total beds, and psychiatrists required. In addition, the model also considers possible drop in mental health prevalence by strengthening social determinants, as well as improving primary and tertiary care, thereby reducing the total DALY attributable to mental illness. The interventions listed in this paper fall within these levels of care and simulate the cumulative effect on the DALY at a population level. The details of the simulation model and other information and supplementary material will be available to any expert, following a reasonable email request to the corresponding author.

Results

The search for evidence-based interventions to achieve a zero mental health burden yields two sets of interventions. Table 2 lists the first set of interventions. This set comprises interventions with a considerable weight of evidence behind them and that are conclusively effective and feasible to implement immediately. Table 3 lists the second set of interventions. These comprise interventions that require deeper changes in the formulation and implementation of national policies, such as access to housing, basic income, healthcare and access to finance. They require a considerable investment in validating and developing the evidence base, as well as implementation to scale them.

India currently has 56,600 psychiatric beds^[18] and 9000 psychiatrists.^[19] The total health expenditure in India (across all diseases) during 2019–2020 was INR 4863 per capita, with the government spending INR 2014 per capita of this amount. Of this amount, a mere INR 7.46 per capita was allocated towards government mental hospitals.^[20] With India’s current exclusively recovery-focused approach, this modelling exercise estimates that reducing the burden of mental health effectively, the country will require an annual expenditure of INR 20,000 per capita, 0.8 million beds, and 0.5 million psychiatrists – infeasible at the current rate of growth and budget allocation.

By 2040, with all the socio-economic changes taking place in India, such as urbanisation, heightened income uncertainty, migration and the changes in traditional family structures, this simulation suggests that at the high end, the DALY Rate could go up to 3300 applied over an underlying population of 1.5 billion people. By then, India can expect to have at most 20,000 psychiatrists practising in India.^[19] As shown in Figure 1, with the set of interventions mentioned in Table 2, this simulation suggests that a DALY Rate of 600 could be achievable by 2040 with a per capita expenditure of INR 400 from the government and 15,500 psychiatrists. It is important to note from Figure 1 that the most significant drop from a DALY Rate of 3300–1400, i.e. 69% of the total reduction of 2600 from 3300 to 600, will be achieved through the high-fidelity implementation of the interventions relating to the social determinants of health. The curative portions are expected to account only for a 31% reduction in the DALY rate.

The interventions included in Table 3 collectively represent the possibility of a very large impact on the mental health burden in India. However, the evidence base behind them did not allow us to extend this simulation exercise to assess whether they would be sufficient to achieve the goal of a zero burden from the DALY Rate of 600 that interventions listed in Table 2 could potentially deliver.

Discussion

The mental health burden is a result of several kinds of mental illnesses. Depression is the most significant contributor to India’s DALYs and a major contributor to suicides,^[21] and anxiety disorder is the second most significant contributor to India’s DALYs, affecting 46 million and 45 million people, respectively. Anxiety disorders have considerably higher prevalence rates in urban communities, 35.7%, than in rural communities, 13.9%.^[22] The other illnesses include idiopathic developmental intellectual disability, schizophrenia, bipolar disorder, conduct disorder, autism spectrum disorder, eating disorders and attention-deficit hyperactivity disorder – in the descending order of the burden as measured by DALYs^[1].

In 2019, 23.6 million people in the world were living with schizophrenia.^[3] In India, in 2017, 3.5 million people were living with schizophrenia.^[1] Conditions such as schizophrenia, despite having a very low prevalence of 0.3, severely impact the DALY by nearly 10%. The life expectancy of an individual with schizophrenia is 10–20 years lower than that of the general population.^[23] The disability weight of schizophrenia in its acute state is 0.778 – which means that if 0.00 is full health, and 1.00 is death, a person with schizophrenia is much closer to death than full health.

The prevalence of these conditions and the high disability weights associated with them are further exacerbated by the large treatment gap. In low- and middle-income countries, the treatment gap is estimated to be 85%, compared to only 40% in high-income countries (HICs).^[24] In India, according to the National Mental Health Survey, the treatment gap for all mental illnesses is as high as 83%.^[25] Another study conducted in India found that only 5 out of 100 individuals experiencing mental illness received treatment in a year, indicating a 95% treatment gap.^[26] These numbers refer to all types of treatment – the availability of minimally effective treatment is likely to be even smaller.

So far, India’s mental health landscape is currently exclusively focused on recovery, delivered mainly through hospital-based treatment services. There are 46 government mental healthcare institutions and several non-governmental and private organisations working on treatment and recovery, but a large treatment gap remains.^[25] The District Mental Health Program (DMHP) was started by the government in 1982 under the National Mental Health Program to meet the large treatment gap. The DMHP has been successful in expanding access to treatment up to the district level, but beyond that, its efforts have been limited to building awareness, in large part because the Mental Healthcare Act of 2017,^[27] while comprehensively codifying the rights of the mentally disabled, does not provide for treatment by non-mental health professionals,^[28] and does not account for the severe shortage of psychiatrists in the country or provide alternatives. Moreover, as discussed above, focusing only on recovery, no matter how well designed and implemented, is insufficient and infeasible, given the resource constraints. In comparison to other countries, India’s mental health landscape has substantial gaps in strategy, as shown in Figure 2. As discussed above, given the severe human and financial resource limitations, the only way forward for us is to intervene simultaneously on all the four dimensions of resilience, reduce, recognise and recovery, using interventions drawn from all five domains of the social determinants of health, public health, and primary, hospital and long-term care.

Mor and Shukla^[29] find that with India’s considerable cost advantages on the human-resources-for-health front, at INR 2000 per capita (2018 prices), all Indian states should be able to offer Universal Health Coverage (UHC) to their residents and that by the year 2030, state government expenditures on health in almost all the Indian states should equal or exceed that number (at 2030 prices). By 2040, adjusting the above-mentioned INR 2000 estimates for inflation at 5% per annum,^[29] the estimated per capita cost is INR 5850 available from each state government for health care. With mental health accounting for a disease burden of about 10%^[30] assuming a proportional allocation with a UHC framework, the money available on a per-capita basis for mental health is likely to be at least INR 585 per capita in each state. As discussed above, a simulation of the impact of interventions listed in Table 2 suggests that a DALY Rate of 600 may be achievable with an expenditure of INR 400 per capita by 2040 with the help of 15,500 psychiatrists. This leaves INR 185 per capita (or INR 277.5 bn for a population of 1.5 bn) for a deeper exploration of the interventions listed in Table 3.

On the implementation front, of the two sets of interventions listed in Tables 2 and 3, the evidence base and the immediate feasibility of implementation are higher for those included in Table 2. However, even for these interventions, detailed design of implementation strategies, advocacy, and continuous efficacy monitoring would be required. For interventions listed in Table 3, substantial original research will additionally be needed before recommending them for national scale-ups. Before proceeding with any large-scale implementations, as a first step, we recommend establishing a set of specialised research, design, and advocacy centres that will continually examine the available evidence and where necessary, propose entirely new interventions and gather the evidence for them. Large-scale interventions could then follow as a next step. Based on our analysis and evidence review, the authors recommend that the following three centres be established as a first step.

Conclusion

India has a high and growing burden of mental illness. The current Indian strategy of focusing exclusively on treatment is likely to have a limited impact and is, moreover, infeasible given the resource constraints. The only way forward is for us to work simultaneously on the four dimensions of (i) resilience: building the resilience of populations, particularly young people, (ii) reduce: reducing their exposure to pathogenic stress, (iii) recognise: early recognition of exposure to risk factors and (iv) recovery: ensuring the availability of strong recovery pathways. This can be done effectively by implementing interventions drawn from the five domains of (i) social determinants of health, (ii) public health, (iii) primary care, (iv) hospital care and (v) long-term care, with those from social determinants of health more than halving the disease burden. The rest of the disease burden can be effectively addressed through a combination of public health, primary care, hospital care, and long-term care strategies situated within a UHC framework.