We report the findings of a population based survey of the prevalence, socio-economic risk factors and help-seeking for depression in a rural population in India. Our main findings are that the prevalence of depression varied greatly between the two sites of the study; higher age, female gender, lower education, economic status below poverty line and indebtedness were associated with depression; and while a contact coverage with formal health care was very low, a large proportion of affected persons had consulted family members. Almost all who went to a health care provider had consulted a general physician. The median costs of care for the episode was equivalent to four and half times the median rural per capita income of the country .
There is a wide variation in prevalence of depression in India with figures in the range of 2–57 %  and one meta-analysis reports a pooled prevalence of 8.9 % for depression , a figure that closely approximates our overall prevalence estimate, although it varied over two fold across the two talukas. This variation was observed despite the same research team and methodology and timing of the survey. The findings from the World Mental Health Surveys has also shown that the prevalence of depression and other common mental disorders varies widely between populations cross-nationally [26, 27]. Our prevalence estimates are also higher than those reported by Ferrari et al. from the Global Burden of Disease 2010 study  as well as the rates reported by Bromet et al. from the World Mental Health Survey . Estimates from these studies are based on assessment of depression using structured diagnostic tool such as Composite International Diagnostic Interview (CIDI), while our estimates are based on use of screening tool (PHQ-9) which might possibly explain some of these differences. However, a large community-based study from South India using a modified PHQ-9 has observed 15.1 % prevalence of depression which is very close to our overall estimate  and, further, the higher prevalence observed in our study may also be a true reflection of the higher prevalence of risk factors associated with the condition. The strong independent association of site with depression after adjusting for demographic and socio-economic factors suggests that other unknown ecological factors are key drivers for depression.
We observed a monotonic increase in prevalence of depression with age which is contrary to the literature from high-income countries  which suggest that depression peaks in middle age. However, our findings are consistent with other studies from India [29, 31]. This difference in the age distribution requires further study and may indicate a higher prevalence of risk factors in older people such as chronic diseases. It is proposed that structured, complex interview schedules such as Composite International Diagnostic Interview (CIDI) tend to underestimate prevalence of mental disorders in older age groups compared to screening tools (GHQ-12, K10) , and this might possibly explain the increased prevalence of depression in older age groups we observed in our study. Our findings of a higher risk in women, however, is consistent with the global and contextual literature [29, 33, 34]. Our findings support the robust evidence regarding the association of lower socio-economic position with depression. There is high level of inequity in the distribution of CMDs across socio-economic strata within societies, with significantly increased rates of depression among lower socio-economic groups [35–37]. Our finding of independent associations between lower levels of education, living below poverty line and indebtedness supports this observation. However, we did not observe any association between being a member of a disadvantaged sub-group (Scheduled castes and tribes) and depression. Importantly, in the context of the ongoing concerns about the mental health of farmers we did not observe any association between agricultural occupations and depression. Nevertheless, suicides in farmers needs to be explored further. Two studies based on psychological autopsies of farmer’s suicides found that indebtedness and hopelessness due to crop failure leads to decline in economic status resulting in family disputes, depression and drinking problems [7, 38]. This, coupled with easy access to pesticides and government compensation following death due to suicide, creates a toxic brew of circumstances which ultimately lead to farmers attempting suicide.
The contact coverage for depression was only 5 % but over half of affected persons had discussed their problems with someone in their social network (e.g. spouse, children, friends etc.). Furthermore, most of the individuals who did seek care visited a general physician. Only one individual had sought care from psychiatrist and none had approached community health workers or para-medical staff in public health sector. Our findings are consistent with those observed in a multi-centric epidemiological study of mental disorders conducted by the Ministry of Health which found that only 5.1 % people with mental disorders in past 12 months had utilized mental health services and were provided a prescriptive treatment. A study conducted as part of the World Health Survey has reported 12.5 % coverage for people with depression . The large difference in the contact coverage observed between two sites could be potentially explained by the fact that villages in Dhamangaon taluka have good transportation and access to specialist (psychiatrist) services available in two medical colleges providing tertiary care in Wardha city which is the neighboring district headquarter. One of these medical colleges, Datta Meghe Institute of Medical Sciences provides free transportation to patients (including those with mental disorders) in adjoining rural areas including villages in which VISHRAM was implemented. Thus, for patients with depression in Dhamangaon taluka, services are available in two cities (Amravati and Wardha) compared to only one (Amravati) for those in Chandur Bazaar taluka. In addition, transportation related barriers associated with ‘access to care’ are also addressed resulting in better contact coverage.
Conceptualization of mental illness and beliefs in effectiveness of treatment modalities influence help-seeking for depression . In India, and particularly in rural communities, mental disorders are conceptualized as equivalent to psychosis and epilepsy and the symptoms associated with depression are perceived as secondary to the social and economic problems . Non-recognition of these symptoms as a medical condition (depression) as well as stigma attached to labels related to mental disorders are likely to be important reasons for the low levels of contact coverage. Availability of services also impacts help-seeking behavior as described above. Currently the specialist services are available only at the district headquarters [Amravati and Wardha (for Dhamangaon taluka)] which plays a significant role in delaying help-seeking and general physicians in public as well as private sector do not explicitly provide services for common mental disorders. In this context, community-based health workers could play an important role in as they are ideally placed to identify people experiencing depression, provide low intensity psychosocial interventions, make appropriate referrals to primary care, and contribute to raising awareness about depression being a treatable condition.
Other studies from India have demonstrated that individuals with depression spend more days being unable to work as usual due to their illness . A study in India in primary care estimated the cost of an episode of a common mental disorder to be equivalent to 3 weeks’ wages for agricultural workers . A population based study of the health care costs of three common conditions affecting women (reproductive tract infections, anaemia and depression) reported that only depression was associated with increased health care costs and markedly increased the risk of catastrophic health expenditure . The data from our study on costs of care for depression in rural settings in very limited as only 9 individuals had accessed services for their complaints related to depression. The median cost of care was very high and was primarily for the consultation fees of the doctor indicating the use of private practitioners for depression. Very high costs of care is are potentially an important barrier to access health services resulting in low contact coverage. Lack of adequate protection against financial risks leading to catastrophic health expenditures pushes millions of Indians into poverty trap  which essentially underlines the importance of integrating mental health care in the public health care system where the costs incurred by patients are primarily related to travel and medications.
As with all cross-sectional surveys, our study is not able to unpack the causal inferences about the associations we observed. Importantly, while we observed a large variation in prevalence across the two talukas, the assessments we carried out were unable to explain this. Variables specifically related to women’s mental health such as husband’s alcohol intake, and inter-personal violence were not part of the questionnaire. Physical health is also associated with depression, but was also not assessed. We are unable to comment on effective coverage and we also have limited data on cost of care for depression from this survey.
Notwithstanding these limitations, this paper describes one of the few studies from India which attempts to assess the treatment coverage of services for depression in rural settings. There are also very few recent studies from rural India which have assessed association of various socio-economic factors with depression. Thus, this study does address key research questions on the epidemiology of depression in rural India.
Our findings clearly indicate that psycho-social distress in rural communities in Maharashtra is strongly associated with social determinants such as gender, poverty and indebtedness and affects the entire population and not just farmers. Although depression is a common condition, there are wide small area variations which require explanation. Treatment gaps are very high and it is essential to implement community based mental health programs which address both the demand side and supply side barriers which contribute to low levels of contact coverage. This is the goal of the VISHRAM program and the findings of the repeat survey in the same population will be reported in due course.