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Determinants of depression in Indian tribal adults: Evidence from the Longitudinal Ageing Study in India Wave-I survey
For correspondence: Prof Ravendra Kumar Sharma, Department of Economics, Chaudhary Charan Singh University, Meerut 250 004, Uttar Pradesh, India e-mail: ravendra_s@yahoo.com
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Received: ,
This article was originally published by Wolters Kluwer - Medknow and was migrated to Scientific Scholar after the change of Publisher.
Abstract
Background & objectives:
The tribal populations are vulnerable to mental health issues owing to various reasons. However, limited research has been conducted to assess depression and related determinants among tribal adults aged ≥45 yr (45 years and older). The present study aimed to assess the prevalence and sociodemographic and health determinants of depressive symptoms among the scheduled tribe (ST) population aged ≥45 yr in India.
Methods:
The present study analyzed the Wave I data of the Longitudinal Ageing Study in India conducted between April 2017 to December 2018. The outcome variables in the present study were self-reported depressive symptoms. Two internationally recognised tools, the Centre for Epidemiologic Studies Depression scale (CES-D) and Composite International Diagnostic Interview-Short Form (CIDI-SF), were used to obtain the data, however, only the CES-D data are utilized in this study. The present study focused on 12,215 ST individuals aged ≥45 yr from whom information about depressive symptoms was collected and analyzed.
Results:
Nearly 25 per cent ST population aged 45 yr or older experienced depressive symptoms. The likelihood of experiencing depressive symptoms among the ST population aged ≥45 yr was negatively associated with 10 or more years of education and living with children and others and positively associated with experiencing multiple morbidity conditions.
Interpretation & conclusions:
Given the substantial burden of depression among the adult ST population, the present study lays emphasis on raising the awareness about depressive symptoms and strengthen the availability of mental health services among the ST community through intensive campaigns and engagement of ST individuals along with other key stakeholders. Higher education, living with spouse and children and a physically active lifestyle can play a crucial role in limiting depressive symptoms among the tribal adults (≥45 yr). It is paramount to regularly screen depressive symptoms and conduct more microlevel studies to evaluate socioeconomic and health determinants of depressive symptoms among ST communities living in different geographic regions.
Keywords
CES-D scale – demography
depression
health
longitudinal study
multi-morbidity
self-reported depression
social isolation
socioeconomic
Depression is one of the most common mental disorders, characterized by feelings of guilt/ low self-worth, sadness, tiredness, loss of interest or pleasure, appetite or disturbed sleep and poor concentration1. It is one of the common disorders affecting mental and overall health, especially in later life. Recent studies revealed a high pooled prevalence rate of depression among adults (≥45 yr) in different regions of South-Asian countries (42%)2 and India (34.4%)3. In India, the age-standardized prevalence of depression among the ≥45 yr was found to be 5.7 per cent4. Multiple morbidity conditions, personality traits (dependent/anxious/avoidant), unfavourable life events (separation/divorce/bereavement/ poverty/ social isolation), living situations, alcohol consumption, smoking and a lack of necessary social and financial support are the factors that moderate the determinants of depression in the population aged ≥45 yr567. The burden of depression and its determinants among the elderly have been studied extensively in India3 but limited research has been conducted to assess depression and related determinants among the scheduled tribe (ST) population. Over 104 million ST people were enumerated in the 2011 census in India classified into 705 ST communities and accounting for 8.6 per cent of the total Indian population8. Being one of the most heterogeneous, vulnerable and marginalized segments of society; the ST population mainly resides in relative social isolation inhabiting rural and remote areas and is culturally or ethnographically unique. The ST populations are more vulnerable to mental health issues compared to their non-ST counterparts for multiple reasons.
The rapid social changes altered tribes’ belief systems, lifestyles and community living. The traditional livelihood system of the ST population has been disrupted by modernization leading to the loss of customary rights over traditional sources of livelihood, such as forest land and produce; relegation and development of low self-esteem, thereby causing immense psychological stress9. Migration to urban spaces, acculturation and use of alcohol and other substances make them vulnerable to several mental health issues in general and depression in particular. Further, ST populations are characterized by poorer health indices, a greater burden of morbidity and mortality and limited access to healthcare resources in comparison to similar non-ST populations, even within the same State10.
The mental health of the ST population is one of the most neglected domains in the field of public health as visualized by limited literature and data11. The ST community has poor health infrastructure and scant mental health resources in comparison to other communities residing in similar areas12. Considering the above scenario, the present study was conducted to assess the prevalence and socioeconomic, demographic and health determinants of depressive symptoms among the ST population aged ≥45 yr in India.
Material & Methods
Data source: The present study analyzed data from Wave-I of the Longitudinal Ageing Study in India (LASI) after procuring permission for using the LASI Wave-I data from International Institute of Population Sciences, Mumbai conducted from April 2017 to December 201813. The LASI is the nationwide longitudinal survey to provide a comprehensive insight into the health and socioeconomic status of adults aged 45 yr and above in India. The LASI survey utilized a multistage stratified cluster sample design to cover 72,250 men and their spouses aged ≥45 in India across all States and Union Territories (except Sikkim). Information about depressive symptoms was collected from 70,386 individuals, including 12,215 ST and 58,171 non-ST respondents. The present study focused on only 12,215 ST individuals aged ≥45 yr (7219 aged 45-59 yr and 4996 aged ≥60 yr). Detailed information about the sampling process; and inclusion and exclusion criteria have been provided in the LASI Wave I report13.
Variables under study:
Outcome variables: The self-reported depressive symptoms, assessed using two internationally validated and comparable tools - the Centre for Epidemiologic Studies Depression Scale (CES-D)14 and the Composite International Diagnostic Interview - Short Form (CIDI-SF)15 scale, is the outcome variable to assess depressive symptoms and episodes. The CES-D scale is a short self-report scale used to screen depressive symptoms in the general population and differed from prior depression scales which were used for clinical diagnosis and/or assessment of the severity of illness over the course of treatment14. The CIDI-SF which is developed to measure more severe episodes of depressive symptoms was administrated only to 4749 respondents, including 411 ST and 4338 non-ST respondents. Hence, the present analysis is restricted to only the CES-D scale and ST population aged ≥45 yr.
The original CES-D screening tool was composed of 20 questions assessing positive, negative or depressed affect, interpersonal difficulties and somatic symptoms14. LASI used a shortened version of the CES-D tool with a 10-item scale including seven negative symptoms (such as feeling depressed and low energy) and three positive symptoms (such as feeling satisfied and happy). A four-point scale was used to record the responses to these symptoms as follows13- rarely/ never < one day), sometimes (1 to 2 days), often (3 to 4 days) and most or all of the time (5 to 7 days) in a week before the interview. For negative symptoms, particularly for ‘rarely or never’ and ‘sometimes’ were scored zero, and ‘often’ and ‘most’ or all of the time were scored one. In case of positive symptoms the scoring was reversed. Individuals with an overall composite score of ≥4 were referred to as having depressive symptoms13.
Covariates:
Sociodemographic variables: Gender (male/female); educational status [no schooling/ primary education (1-5 yr)/ secondary education (6-9 yr)/higher education (10 yr and higher)]; marital status [others (widowed, divorced, separated or never married)or currently married]; working status (not working/currently working); religion (Hindu/Christian/others); residence (rural/urban); regions (North/South/Central/East/West/Northeast); monthly per capita consumption expenditure (MPCE) quintile (proxy measure of socioeconomic status categorized into five quintiles taking into account household consumption data as poor/poorer/poorest/richer/richest); living arrangements (categorized as living alone/living with others only/living with spouse and/or others/living with spouse and children, and living with children and others) and social participation was assessed through the involvement in social organizations (categorized as ‘no’ indicating no community involvement and ‘yes’ indicating community involvement).
Health behaviour was studied by taking into account alcohol intake (categorized as never/ occasional/ most frequently) and physical activity status (categorized as physically active either engaged in moderate/ vigorous physical activity or combination of both and ‘physically inactive’ not engaged in any type of physical activity throughout the week).
The health conditions were assessed if the respondent was diagnosed with at least two morbidity conditions by a health professional (categorized as ‘no morbidity’, ‘single morbidity condition’ and ‘multiple morbidity conditions’).
Statistical analysis: STATA SE 16.0 (StataCorp LLC, College Station, TX, USA) was used for data processing and statistical analysis. Descriptive statistics were used to depict the characteristics of the studied population. A multivariable binary logistic regression was used to identify important determinants of depressive symptoms after adjusting for other selected sociodemographics, health conditions and behaviour characteristics among ≥45 yr ST population.
Results
Prevalence of symptoms of depression among the scheduled tribe (ST) population aged ≥45 yr in India: According to the CES-D scale, about one-fourth (25.2%; 95% confidence interval: 24.4-26%) ST population aged ≥45 yr experienced depressive symptoms. The prevalence of depressive symptoms among the ST population increased from 21 per cent in the age group 45-49 yr to 29 per cent among ≥70 yr (Chi-square for linear trend=23.55, P<0.001) (Figure). A significantly higher proportion of females compared to their male counterparts reported depressive symptoms. A significantly lower proportion of currently married individuals reported having depressive symptoms compared to other (widowed or divorced or never married) individuals. Nearly three in every ten illiterate ST individuals aged ≥45 yr experienced depressive symptoms during the reference period compared to about one in every ten literate individuals with 10 yr or higher education. A significant difference was observed in the reporting of depressive symptoms by educational status among ST individuals aged ≥45 yr.

- Percentage of depressive symptoms (CES-D scale) by age group among the tribal population aged ≥45 yr in India, 2017-2018. Note: Based on authors calculation of LASI wave-I raw data.
More than two-fifths of the ≥45 yr individuals living alone experienced depressive symptoms. In contrast, around one-fifth of ≥45 yr individuals living with their spouse and children experienced depressive symptoms. Nearly 31 per cent of ST individuals aged 45 and above having multiple morbidities reported depressive symptoms compared to 23.4 per cent of ST individuals without any morbidities. Nearly three in every 10 ST individuals in the richest quintile experienced depressive symptoms, ST individuals currently not working, residing in urban areas and physically inactive were also at a higher risk of experiencing depressive symptoms.
Determinants of symptoms associated with depression among the scheduled tribe (ST) population aged ≥45 yr in India: ST individuals with 10 yr or higher education were around 50 per cent less likely to experience depressive symptoms compared to the reference category. ST individuals aged ≥45 yr living with children and others were 36 per cent less likely to experience depressive symptoms compared to individuals living alone. The ST individuals with multiple comorbidities were nearly 40 per cent more likely to experience symptoms of depression as compared to disease-free ST individuals. ST populations residing in different regions were about 2-4 times more likely to report experiencing depressive symptoms compared to the ST population residing in the northeastern region. A detailed description of socioeconomic and demographic determinants of depressive symptoms is provided in Table I. Similar kind of results was also observed based on the multiple linear regression method (Table II).
| Background characteristics | Bivariate analysis | Multivariable logistic regression, AOR (95% CI) | ||
|---|---|---|---|---|
| Depressive symptoms (%) | n | OR (95% CI) | ||
| Age of respondents | ||||
| 45-59® | 23.5 | 7219 | - | - |
| 60+ yr | 27.5 | 4996 | 1.23 (1.14-1.34)*** | 0.91 (0.75-1.11) |
| Sex of the respondents | ||||
| Male® | 23.7 | 5163 | - | - |
| Female | 26.3 | 7052 | 1.15 (1.06-1.25)*** | 0.84 (0.68-1.03) |
| Marital status | ||||
| Currently married® | 22.2 | 9309 | - | - |
| Others (currently not married) | 34.1 | 2906 | 1.81 (1.65-1.98)*** | 1.51 (0.69-3.27) |
| Religion | ||||
| Hindu® | 25.6 | 5274 | - | - |
| Christian | 21.4 | 5146 | 0.79 (0.72-0.86)*** | 1.12 (0.88-1.42) |
| Others | 28.8 | 1795 | 1.17 (1.04-1.32)** | 1.39 (0.86-2.22) |
| Education | ||||
| No schooling® | 27.7 | 6520 | - | - |
| Less than five years | 20.8 | 1690 | 0.68 (0.6-0.78)*** | 0.73 (0.56-0.97)** |
| 5-9 completed | 22.4 | 2588 | 0.68 (0.6-0.71)*** | 0.87 (0.67-1.13) |
| 10 or more years | 15.4 | 1417 | 0.75 (0.68-0.84)*** | 0.52 (0.36-0.76)*** |
| Region | ||||
| North-East® | 13 | 5423 | - | - |
| East | 25.4 | 1346 | 2.28 (1.97-2.14)*** | 2.39 (1.88-3.04)*** |
| West | 22.6 | 1769 | 1.95 (1.71-2.25)*** | 2.14 (1.6-2.85)*** |
| North | 26.8 | 733 | 2.44 (2.04-2.95)*** | 2.42 (1.79-3.27)*** |
| South | 39.2 | 1803 | 4.32 (3.82-4.88)*** | 3.97 (2.75-5.73)*** |
| Central | 28.3 | 1141 | 2.64 (2.27-3.07)*** | 2.79 (2.07-3.76)*** |
| Work status | ||||
| Currently working ® | 22.9 | 6933 | - | - |
| Not working | 29 | 5282 | 1.37 (1.27-1.49)*** | 1.17 (0.96-1.43) |
| MPCE quintile | ||||
| Poorest ® | 25.1 | 3484 | - | - |
| Poorer | 23.4 | 2600 | 0.91 (0.81-1.02) | 0.74 (0.49-1.12) |
| Middle | 26.4 | 2241 | 1.07 (0.95-1.21) | 0.88 (0.6-1.29) |
| Richer | 24.1 | 1922 | 0.95 (0.88-1.08) | 0.74 (0.51-1.07) |
| Richest | 29 | 1968 | 1.22 (1.08-1.38)*** | 0.81 (0.56-1.19) |
| Living arrangements | ||||
| Living alone® | 42.3 | 403 | - | - |
| Living with others only | 34.9 | 502 | 0.74 (0.56-0.96)* | 0.77 (0.46-1.29) |
| Living with children and others | 32.3 | 2162 | 0.66 (0.53-0.81)*** | 0.64 (0.41-0.99)** |
| Living with spouse and/or others | 26 | 1629 | 0.48 (0.38-0.64)*** | 0.68 (0.29-1.62) |
| Living with spouse and children | 21.2 | 7519 | 0.36 (0.3-0.45)*** | 0.58 (0.25-1.36) |
| Place of residence | ||||
| Rural® | 25 | 9458 | - | - |
| Urban | 26.6 | 2757 | 1.08 (0.98-1.19)* | 1.1 (0.77-1.56) |
| Drinking alcohol | ||||
| Never® | 26.1 | 8878 | - | - |
| Occasional | 24.4 | 2484 | 0.91 (0.82-1.01)* | 0.94 (0.76-1.16) |
| Most frequently | 20.3 | 853 | 0.72 (0.6-0.85)*** | 0.75 (0.54-1.05) |
| Multi-morbidity | ||||
| No morbidity® | 23.4 | 8600 | - | - |
| Single morbidity | 29.9 | 2451 | 1.37 (1.26-1.54)*** | 1.4 (1.12-1.74)*** |
| Two or more morbidity | 31.2 | 1164 | 1.48 (1.38-1.7)*** | 1.38 (1-1.91)* |
| Physically active | ||||
| Inactive® | 28.9 | 3515 | - | - |
| Active | 24.1 | 8700 | 0.78 (0.71-0.85)*** | 0.91 (0.73-1.13) |
| Total/constant | 25.2 | 12,215 | 0.29 (0.12-0.72)*** | |
P *<0.05; **<0.01; ***<0.001. Results based on authors calculations of LASI wave-I raw data. OR, odd ratio; AOR, adjusted OR; LASI, Longitudinal Ageing Study in India; MPCE, monthly per capita consumption expenditure; CI, confidence interval; ®Reference category for logistic regression
| Background characteristics | Coefficient | SE | P>t | 95% CI |
|---|---|---|---|---|
| Age of respondents | −0.001 | 0.006 | 0.865 | −0.012-0.01 |
| Sex of respondents | ||||
| Male® | ||||
| Female | −0.071 | 0.117 | 0.545 | −0.300-0.158 |
| Marital status | ||||
| Currently married® | ||||
| Others | −0.341 | 0.354 | 0.335 | −1.034-0.352 |
| Religion | ||||
| Hindu® | ||||
| Christian | −0.045 | 0.121 | 0.708 | −0.282-0.192 |
| Others | 0.271 | 0.195 | 0.165 | −0.112-0.653 |
| Education | −0.013 | 0.012 | 0.298 | −0.037-0.011 |
| Region | ||||
| North-East® | ||||
| East | 0.358 | 0.119 | 0.003 | 0.124-0.592 |
| West | −0.119 | 0.139 | 0.393 | −0.392-0.154 |
| North | 0.542 | 0.152 | 0 | 0.244-0.84 |
| South | 1.32 | 0.256 | 0 | 0.818-1.822 |
| Central | 0.686 | 0.137 | 0 | 0.417-0.955 |
| Work status | ||||
| Currently working® | ||||
| Not working | −0.047 | 0.102 | 0.645 | −0.246-0.152 |
| MPCE quintile | ||||
| Richest® | ||||
| Richer | 0.018 | 0.168 | 0.917 | −0.312-0.347 |
| Middle | −0.11 | 0.168 | 0.515 | −0.44-0.221 |
| Poorer | −0.093 | 0.162 | 0.565 | −0.41-0.224 |
| Poorest | 0.112 | 0.168 | 0.505 | −0.218-0.443 |
| Living arrangements | ||||
| Living alone® | ||||
| Living with others only | −0.633 | 0.418 | 0.13 | −1.451-0.186 |
| Living with children and others | −0.527 | 0.309 | 0.088 | −1.133-0.079 |
| Living with spouse and/or others | −0.786 | 0.451 | 0.081 | −1.67-0.098 |
| Living with spouse and children | −1.046 | 0.439 | 0.017 | −1.907−0.185 |
| Place of residence | ||||
| Rural® | ||||
| Urban | −0.162 | 0.114 | 0.156 | −0.385-0.062 |
| Drinking alcohol | ||||
| Never® | ||||
| Occasional | −0.152 | 0.119 | 0.2 | −0.385-0.08 |
| Most frequently | −0.214 | 0.161 | 0.183 | −0.528-0.101 |
| Multi-morbidity | 0.149 | 0.073 | 0.043 | 0.005-0.293 |
| Physically active | ||||
| Inactive® | ||||
| Active | −0.332 | 0.11 | 0.003 | −0.548-−0.117 |
| Constant | 3.748 | 0.57 | 0 | 2.63-4.866 |
Result based on MLR method. SE, standard error; MLR, multiple linear regression
Discussion
The present study found that one in every fourth ST individuals aged ≥45 yr experienced depressive symptoms which is also similar to the national average13. It was further found that the studied population with ‘10 yr age or higher education’ was less likely to experience depressive symptoms. Education helps to build psychological and economic resources and make individuals more aware of health issues that stave off potential health issues linked with depression in later life16. Previous studies have also reported that illiteracy contributes to depression among older adults1718. Living with children and others significantly reduced the likelihood of experiencing depressive symptoms among the ST population. Similar to earlier studies1819 the married adults in the present study exhibited a lower proportion of depressive symptom as compared to those who were not currently married /unmarried or separated or widowed. Studies have indicated widowhood and solo living (unpartnered) as determinants of poor mental health among the older adult population in general20. This may be owed to the increased stress because of spousal loss; lack of emotional and financial support21. ST people have their unique identity and cultural patterns but owing to rapid urbanization, displacement, acculturation and loss of traditional livelihood, the ST people have faced socioeconomic and mental health issues922232425262728.
Nearly one in every four occasional alcohol drinkers experienced depressive symptoms. Data from India corroborates the high rate of alcohol use among the tribal population29, which is associated with a wide range of social issues such as family dissolution, income loss, and income being diverted from meeting family needs and health problems such as high rates of morbidity and early death30. Emotional problems, distress, societal acceptance of alcohol consumption and peer pressure were cited as the major aetiology for the higher prevalence of substance dependence in ST communities31. ST individuals having multiple morbidities such as hypertension and diabetes were more vulnerable to depression. Depression shares a bidirectional relationship with chronic comorbidities such that the former is a potent risk factor for developing chronic diseases and the latter can also contribute to depression32. Compared to physically inactive individuals, a lower proportion of physically active individuals experienced depressive symptoms. Physically active adult ST, individuals could be either engaged in moderate or vigorous physical activity regime or combination of both13. These physical activities could impact their functional ability, cognitive performance, social connectivity, physical health and overall well-being, thereby reducing the risk of mental health disorders. ST population residing in northeastern regions were least to report depressive symptoms compared to the ST population residing in other regions. These regional differences could be attributed to an array of contextual factors including but not limited to education, dietary habits, co-existing behavioural and chronic health conditions, social setup, profession and physical activity. However, in contrast, to the present study, Singh et al33 found that the general population aged ≥45 yr residing in the southern region were less likely of experiencing depressive symptoms.
The present study is subject to certain limitations. First, the LASI wave-1 data allowed us to examine only the link between determinants and self-reported depressive symptoms. The self-reported information is subject to bias and errors. The multicollinearity among socioeconomic variables is an issue and may be responsible for changes in the direction of the results of some variables. Second, the tools used for screening and diagnosing depressive symptoms cannot replace a comprehensive interview for clinically confirming and diagnosing depression. However, the CES-D tool is useful for public health programmes. Despite the above mentioned limitations, the present study has strengths as well. Owing to scant information on depression among the adult ST population in India, the LASI data offered an opportunity to conduct a pan-India study to assess the magnitude and determinants of depressive symptoms among the ≥45 yr old ST population. This is the latest dataset (released in 2021) in India that allowed us to bring forth the current picture of depressive symptoms among the adult ST population taking into account the representative sample from each State in India.
The present study revealed that the likelihood of experiencing depressive symptoms among adult ST population aged ≥45 yr was negatively associated with 10 or more years of education and living with children and others and positively associated with a region and experiencing multiple morbidity conditions. It is paramount to raise awareness about depressive symptoms and strengthen the availability of mental health services among the ST community through intensive campaigns and engagement of ST individuals along with other key stakeholders to reduce the burden of depression among the ST population. However, more micro level studies are required to monitor the severity of mental health issues and evaluate socioeconomically, and health behaviour variables linked to depression among various ST communities living in different geographic regions, and at various sociodemographic and economic transitional stages. This study provides crucial information for future reference, thereby aiding in the development and planning of depression prevention, control and treatment strategies amongst the ST populations in India.
Financial support and sponsorship
None.
Conflicts of interest
None.
References
- Depression among older adults:A systematic review of South Asian countries. Psychogeriatrics. 2021;21:201-19.
- [Google Scholar]
- Prevalence of depression among the elderly (60 years and above) population in India, 1997-2016: A systematic review and meta-analysis. BMC Public Health. 2019;19:832.
- [Google Scholar]
- Sub-national patterns and correlates of depression among adults aged 45 years and older:Findings from wave 1 of the longitudinal ageing study in India. Lancet Psychiatry. 2022;9:645-59.
- [Google Scholar]
- The World Health Report 2001 — Mental health: new understanding, new hope. Bull World Health Organ. 20011085;79
- [Google Scholar]
- Multimorbidity and depression among older adults in India:Mediating role of functional and behavioural health. PLoS One. 2022;17:e0269646.
- [Google Scholar]
- Does living arrangement predict urban–rural differential in depressive symptoms among older adults in India?A study based on longitudinal ageing study in India survey. Population Ageing. 2021;19:1-9.
- [Google Scholar]
- Report of the high level committee on socio-economic, health and educational status of tribal communities of India. Available from: https://ruralindiaonline.org/en/library/resource/report-of-the-high-level-committee-on-socio-economic-health-and-educational-status-of-the-tribals-of-india/#:~:text=This%20report%20was%20written%20by,and%20legal%20and%20constitutional%20matters
- Tribal health report. Available from: https://tribalhealthreport.in/
- Mental health research on scheduled tribes in India. Indian J Psychiatry. 2020;62:617-30.
- [Google Scholar]
- Rural Health Statistics 2016-17. Available from: https://hmis.mohfw.gov.in/downloadfile?filepath=publications/Rural-Health-Statistics/RHS%202016-17.pdf
- H. Chan School of Public Health, University of Southern California (USC). Longitudinal Ageing Study in India (LASI) Wave 1, 2017-18, India Report, Mumbai. Available from: https://www.iipsindia.ac.in/sites/default/files/LASI_India_Report_2020_compressed.pdf
- [Google Scholar]
- The CES-D scale: A self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385-401.
- [Google Scholar]
- Composite international diagnostic interview – Version 1.1. Geneva: World Health Organization; 1993.
- Education, social status and health. New York: Aldine de Gruyter; 2003.
- Prevalence and factors influencing depression among elderly living in the urban poor locality of Bengaluru city. Int J Health Allied Sci. 2014;3:105-9.
- [Google Scholar]
- Depression and related factors among the elderly Chakhesang population. Indian J Gerontol. 2018;32:7-20.
- [Google Scholar]
- The association of widowhood and living alone with depression among older adults in India. Sci Rep. 2021;11:21641.
- [Google Scholar]
- Association of self-perceived income status with psychological distress and subjective well-being:A cross-sectional study among older adults in India. BMC Psychol. 2021;9:82.
- [Google Scholar]
- Prevalence of dementia and other psychiatric morbidities among geriatriciew population of Salagame primary health centre in Hassan district, Karnataka, India. Int J Community Med Public Health. 2016;3:1315-7.
- [Google Scholar]
- A study on prevalence of depression and associated risk factors among elderly in a rural block of Tamil Nadu. Indian J Public Health. 2018;62:89-94.
- [Google Scholar]
- Comparisons of the prevalence of and risk factors for elderly depression between urban and rural populations in Japan. Int Psychogeriatr. 2012;24:1235-41.
- [Google Scholar]
- Work status, retirement, and depression in older adults:An analysis of six countries based on the study on global ageing and adult health (SAGE) SSM Popul Health. 2018;6:1-8.
- [Google Scholar]
- Comparative assessment of psychosocial status of elderly in urban and rural areas, Karnataka, India. J Family Med Prim Care. 2019;8:2870-6.
- [Google Scholar]
- Geriatric health policy in India:The need for scaling-up implementation. J Family Med Prim Care. 2016;5:242-7.
- [Google Scholar]
- Multidimensional impact of mental illness on tribal families in India. Taiwan J Psychiatry. 2022;36:82.
- [Google Scholar]
- A cross sectional study of alcohol consumption among tribal and non-tribal adults of Narayanganj block in Mandla district of Madhya Pradesh, India. Int J Community Med Public Health. 2017;3:791-5.
- [Google Scholar]
- Factors associated with alcohol misuse among indigenous tribal men in Wayanad:A qualitative study. Indian J Psychol Med. 2019;41:516-22.
- [Google Scholar]
- Reasons for substance use:A comparative study of alcohol use in tribals and non-tribals. Indian J Psychol Med. 2012;34:242-6.
- [Google Scholar]
- Depression as an emerging public health problem in rural India:A case study of a geriatric population in a tribal region of eastern Maharashtra, India. Glob J Med Public Health. 2020;9:1-9.
- [Google Scholar]
- An association between multi-morbidity and depressive symptoms among Indian adults based on propensity score matching. Sci Rep. 2022;12:15518.
- [Google Scholar]
