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ORIGINAL ARTICLE Table of Contents  
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Anxiety and depression among elderly tribal population of H.D. Kote, Mysuru, India: Prevalence and factors associated with it

1 Postgraduate Student, Department of Community Medicine, School of Public Health, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru, Karnataka, India
2 Assistant professor, Department of Community Medicine, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru, Karnataka, India
3 Operational Manager, Vivekananda Memorial Hospital, Swami Vivekananda Youth Movement, Sargur, Mysuru, Karnataka, India
4 Professor & HOD, Department of Community Medicine, Panimalar Medical College Hospital and Research Institute, Chennai, Tamil Nadu, India
5 Lecturer in Statistics, Department of Community Medicine, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru, Karnataka, India
6 Professor & HOD, Department of Community Medicine, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru, Karnataka, India

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Date of Submission15-Jul-2021
Date of Acceptance24-Sep-2021
Date of Web Publication23-Nov-2021


Keywords: Anxiety, depression, geriatric health, mental health, tribal health

How to cite this URL:
Sindhu K V, Chandrashekarappa SM, Thambad M, Boralingiah P, Gopi A, Narayan Murthy M R. Anxiety and depression among elderly tribal population of H.D. Kote, Mysuru, India: Prevalence and factors associated with it. Arch Ment Health [Epub ahead of print] [cited 2021 Nov 28]. Available from: https://www.amhonline.org/preprintarticle.asp?id=330919

  Introduction Top

Human aging is a universal phenomenon that starts with conception and ends with death.[1] At the biological level, aging occurs due to the degeneration and accumulation of a wide variety of molecular and cellular damage over a period of time. Gradually, this process leads to a reduction in the physical and mental ability to cater to the daily needs of life coupled with the growing risks of diseases and ultimately death.[2]

The boundary of old age cannot be exactly defined because it varies across societies. Conventionally, the United Nations defines older persons as those aged 60 or 65 years or over. Government of India's “National Policy on Older Persons” 1999 defines senior citizen or elderly as a person who is 60 years and above.[3]

It has been projected that in 2050, the global number of older persons will reach 1.5 billion.[4] India being the second largest populated country in the world had nearly 72 million elderly persons above 60 years of age in 2001. It is estimated that in 2031, the population of the elderly aged 60 years and above will increase to 179 million and further escalation to 301 million in 2051. The dynamic increase in the number and proportion of elderly will have a straight impact on the growing demands for health-care facilities and services. Organizing and mobilizing infrastructure and resources to cater to geriatric care prove to be a serious responsibility for health-care providers.[5]

As age advances, the normal functioning of the body declines progressively which gives rise to conditions such as impaired vision, hearing defects, loss of control over several functions, cognitive impairment, psychiatric problems which include depression, dementia, anxiety, and functional impairment. It is projected that by 2020, depression will be the most important single cause of disability in all people in both developed and developing countries, particularly among the elderly population.[6]

Very often, mental illness in the elderly goes untreated due to the misconception that these disorders are a normal part of aging and an innate reaction to chronic illness, loss of family members, and social transition that occurs with aging.[7]

In India, tribal communities are considered the most vulnerable, marginalized, and highly disadvantaged groups in terms of socioeconomic, education, and health development.[8] The historical neglect of the tribal groups is considered a major cause behind this marginalization. Despite the implementation of various plans and initiatives, the lives of tribes have not changed much, as evident from the existing vulnerability.[8] Tribal populations suffer from communicable diseases, noncommunicable diseases, malnutrition, addictions, and also mental illness which are often complicated by poor health-seeking behavior.[9]

Although medical anthropology made a tremendous accomplishment in understanding the crux of the tribal health problems and formulating tribal health programs, there is still a dearth of comprehensive and holistic health research among the tribal populations. Undeniably, tribes suffer from the ailment of greater severity and duration, and they do not have access to basic health-care facilities.[8] Despite remarkable progress in mental health care in the nation, they suffer inequality in health including mental health. Although there has been minimal research on the mental health of tribes in India, relatively little research has examined directly anxiety and depression among the elderly tribes.

Hence, the present study was carried out to estimate the prevalence and understand the factors associated with anxiety and depression among elderly tribes of H.D. Kote taluk, Mysuru District, Karnataka, India.


The objective of the study is to estimate the prevalence of anxiety and depression among the elderly tribal population and assess the sociodemographic factors associated with it.

  Materials and Methods Top

Setting and design

A cross-sectional study was conducted in 12 tribal hamlets of HD Kote taluk, from December 2020 to May 2021, for 6 months. Participants aged 60 years and above who gave consent to participate in the study and those who were residing in the study setting for the past 1 year were included in the study and those who were nontribes were excluded from the study.

Sample size

Based on the study by Vimala and Phalke,[10] the prevalence of depression being 21% with an absolute precision of 5%, and a confidence interval of 95%, using the formula z2pq/d2, a sample size of 255 was arrived at. Although the minimum sample size was estimated as 255, data were obtained from 339 participants and the results are interpreted for 339 participants.

Sampling technique

A multistage sampling technique was adopted [Figure 1].
Figure 1: Multistage sampling of the study population

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Data collection tools

These included a semistructured pretested questionnaire to gather information about:

  1. Sociodemographic characteristics (age, gender, religion, education, occupation, socioeconomic status, marital status, living status, family type, financial dependency, personal habits, and comorbid status)
  2. Kannada Geriatric Depression Scale (GDS-15) was used to assess depression.[11] It consists of 15 items with yes or no answers. Each question attracts a score of either 0 or 1. The score between 0 and 4 was considered as no depression, 5 and 10 as mild to moderate depression, and score ≥11 as severe depression
  3. Generalized Anxiety Disorder (GAD-7) scale was used to assess anxiety.[12] It consists of 7 items wherein each item was scored from 0 to 3. A score of 0–4 suggests minimal symptoms, 5–9 as mild anxiety, 10–14 as moderate anxiety, and 15–21 suggests severe anxiety
  4. Katz Index of Independence in Activities of Daily Living (ADL) was used to assess the functional status as a measurement of the participant's ability to perform ADL independently.[13] The Index included six functions of bathing, dressing, toileting, transferring, continence, and feeding. Participants were scored yes/no for independence in each of the six functions. A score of 6 indicated full function, 4 indicated moderate impairment, and 2 or less indicated severe functional impairment.

Data collection procedure

All study participants were personally interviewed by conducting house-to-house visits after obtaining informed consent.

Ethical considerations

Ethical clearance was obtained from JSS Medical College, Mysuru, and Vivekananda Memorial Hospital, Sargur.

Statistical analysis

The data thus obtained was coded and entered into MS excel 2010 spreadsheet and analyzed using SPSS version 25 (IBM SPSS Statistics for Windows, Version 25.0 (IBM Corp.,Armonk, NY.,USA)) (licensed to the institution). Descriptive statistical measures were expressed in numbers and arithmetic mean, standard deviation, median, interquartile range, and proportions. Data were represented in tables and graphs as relevant. Chi-square test/Fisher's exact test was used for finding the association between various sociodemographic variables with anxiety and depression (Yates continuity correction was applied wherever required). P <0.05 was considered statistically significant.

  Results Top

The mean age of the study participants was 64.46 ± 4.723 years with 279 (82.3%) in the age group of 60–69 years, 57 (16.8%) in the age group 70–79 years, and the remaining 3 (0.9%) above 80 years. There were 214 (63.1%) female and 125 (36.9%) male participants. All belonged to the Hindu religion. The majority of the study subjects, i.e., 294 (86.7%) were illiterate while only 3 (0.9%) had completed high school education. Those engaged in unskilled work were 213 (62.8%) while 1 (0.3%) were engaged in semiskilled work and the rest 125 (36.9%) were unemployed.

As per the modified BG Prasad (2019) socioeconomic status scale,[14] 96 (28.3%) of the study population belonged to Social Class III (per capita income Rs. 2102–3503 per month), 131 (38.6%) belonged to Social Class IV (per capita income Rs. 1051–2101 per month), and 112 (33.1%) belonged to Social Class V (per capita income Rs. 1050 and below per month). Most of them were living in the nuclear family, i.e., 197 (58.1%) and only 10 (2.9%) were living in a joint family. According to the marital status, 211 (62.2%) were married, 5 (1.5%) were unmarried, 14 (4.1%) were separated from the spouse, and 109 (32.2%) were widow/widower. As per the living status, 141 (41.6%) were living with their spouse and children while 31 (9.1%) were living alone. Nearly 172 (50.7%) were financially independent while 38 (11.2%) were partially dependent and the rest 129 (38.1%) were financially dependent on others. Among financially dependent subjects, 89 (69%) were getting financial assistance from the government, while 40 (31%) were not getting any sort of financial assistance. The majority of study participants, i.e., 277 (81.8%) had one or the other addictive habits such as smoking 48 (14.2%), alcoholism 27 (8%), tobacco chewing 135 (39.8%), and betel chewing 67 (19.8%). Comorbidities such as polyarthralgia/hypertension/diabetes/ischemic heart disease/hemiplegia were seen in 57 (16.8%) of the subjects while 282 (83.2%) did not have any comorbidity. According to Katz index, 3 (0.9%) had moderate impairment and 336 (99.1%) were independent in their daily activities [Figure 2].
Figure 2: Distribution of study subjects based on Katz Index of Independence in Activities of Daily Living

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The overall prevalence of anxiety was 8.2%, of which 16 (4.7%), 10 (2.9%), and 2 (0.6%) had mild, moderate, and severe anxiety, respectively [Figure 3]. The median and interquartile range of the score of overall anxiety was 0 (0–0), mild anxiety was 6 (6–7), moderate anxiety was 11 (11–12), and the GAD-7 scores of those who had severe anxiety was 15 and 16. Occupation, financial dependence, and comorbid status were significantly associated with anxiety [P < 0.05; [Table 1]]. Anxiety was seen in 21 (12.3%) of the elderly in the age group 70–79 years and 7 (7.5%) in the age group 60–69 years had anxiety. The proportion of males having anxiety was 12 (9.6%) and of females was 16 (7.5%). Based on the educational status, 2 (9.1%) of literates and 26 (8.8%) of illiterates had anxiety. Anxiety was common among 13 (11.6%) of elderly belonging to Social Class V (per capita income Rs. 1050 and below), 11 (8.4%) of those belonging to Social Class IV (per capita income Rs. 1051–2101 per month), and 4 (4.2%) belonging to Social Class III (per capita income Rs. 2102–3503 per month). A higher proportion of unmarried/separated/widow/widower, i.e., 13 (49.7%) had anxiety as compared to married subjects, i.e., 15 (7.1%). Anxiety was more common among the study participants living in the joint family, i.e., 1 (10.0%) compared to those living in nuclear, i.e., 17 (8.7%) or three-generation family, i.e., 10 (7.6%). Anxiety was also more common among the study participants who consumed alcohol, i.e., 3 (11.1%) compared to other addictions like betel chewing, i.e., 5 (9%), tobacco chewing, i.e., 9 (6.7%), and smoking, i.e., 5 (10.5%) or those who did not have any addictive habits, i.e., 5 (8.1%). Among the subjects who had moderate impairment in carrying out daily activities, 1 (33.3%) had anxiety but this was not statistically significant.
Figure 3: Prevalence of anxiety

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Table 1: Sociodemographic factors associated with anxiety

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The overall prevalence of depression was 22.4%, of which 64 (18.9%) were having moderate depression and 12 (3.5%) were having severe depression [Figure 4]. The median and interquartile range of the score of overall depression was 0 (0–3), moderate depression was 6 (6–7), and severe depression was 12 (11.25–13). Gender, occupation, marital status, living status, financial dependence, addictive habits, comorbid status, and independence in ADL were significantly associated with depression [P < 0.05; [Table 2] and [Table 3]]. In the age category of 70–79 years, 18 (31.6%) of the elderly had depression, and 58 (20.8%) of those in the age group 60–69 years had depression. Although a majority of participants were illiterate, only 69 (23.5%) of the illiterates had depression while 7 (61.9%) of the literates had depression. Depression was common among 33 (29.5%) of those with per capita income <Rs. 1050 per month compared to other social classes. A higher prevalence of depression was seen among the elderly living in the joint family, i.e., 3 (30.0%) compared to those living in nuclear, i.e., 46 (23.4%) or three-generation family, i.e., 27 (20.5%). All the subjects 3 (100%) who had moderate impairment in carrying out their ADL were depressed and this association was statistically significant.
Figure 4: Prevalence of depression

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Table 2: Sociodemographic factors associated with depression

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Table 3: Association of other risk factors with depression

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  Discussion Top

The overall prevalence of anxiety among elderly tribes was 8.2%. In a study conducted by Nagoor et al., the prevalence of anxiety in the rural geriatric population was 7.2%.[15] The study conducted by Nayak et al. observed that the prevalence of anxiety among the elderly population in urban areas of Odisha was 57.3%.[16] This variation in the prevalence of anxiety could be probably due to the difference in the geographic location, the methodology, and the instruments used to assess anxiety levels. Our study observed that 9.6% of males and 7.5% of females had anxiety. The study conducted by Verma et al. observed that anxiety was more among the female gender than the male gender in a rural area.[17] Tribal men usually work in remote locations away from their families and the constant stress of work, family, and relationships are likely to cause anxiety. Although a majority of study subjects were illiterate, the prevalence of anxiety among illiterates was 8.8% and literates were 9.1%. In a study by Kirmizioglu et al., GAD was significantly higher among illiterate than literate elderly study participants in Turkey.[18] Educated elderly tribes probably lacked greater professional possibilities resulting in a lack of economic independence as well as several hurdles in overcoming their problems which increased anxiety as a result of greater stress.

Our study observed that occupation was significantly associated with anxiety (P = 0.001). A higher proportion of unemployed study participants had anxiety, i.e., 15.2%. Similar findings were observed in the study by Nagoor et al.[15] This could be due to the fact that unemployment causes financial dependency, making it difficult to afford health care and other necessities. As a result, individuals experience poorer health outcomes which contribute to greater levels of stress and thereby higher anxiety levels.

Our study observed that a higher proportion of unmarried/separated/widow/widower had anxiety as compared to married subjects, which were similar to the findings of the study by Verma et al.[17] This is likely due to the fact that older individuals require affection, care, and acceptance in their current state which is usually provided by their intimate partner. Lack of this support leads to anxiety. The present study showed a significant association between financial dependency and anxiety (P = 0.003). This finding is comparable with the study done by Nagoor et al. in the rural geriatric population.[15] This could be because elderly people should always rely on others even for their basic requirements and expenses which turns out to be stressful thereby leading to anxiety.

Comorbid status was significantly associated with anxiety in the present study (P < 0.001). The study by El-Gabalawy et al. also observed that the presence of comorbidities like chronic painful conditions was positively associated with anxiety in the older population.[19] This could be because physical ailments by themselves cause anxiety, and also the lack of numerous aspects involved in seeking health care for physical ailments such as lack of finance, lack of physical, and mental support from loved ones, also leads to anxiety.

The overall prevalence of depression was 22.4. The study by Vimala and Phalke also noted the prevalence of depression as 21%,[10] which is almost similar to the findings of our study. The study conducted by Pranay Jadav among old-aged people living in urban slums observed that the prevalence of depression was 30.7%.[1] Another study by Pilania et al. among the elderly in rural Haryana by using GDS-30 observed that the prevalence of depression was 14.4%.[20]

Gender was significantly associated with depression. Similar findings were observed by Pilania et al.[20] This could be because the stress females carry impacts them more which might lead to depression. Apart from this, a significant association was found between occupation, financial dependency, comorbid status, and depression. The study by Buvneshkumar et al. also observed similar findings.[21] Unemployment often leads to financial insecurity and low self-esteem. The elderly who are financially dependent on others lack financial freedom and their needs and necessities are always at the mercy of others, which could lead to mental agony and depression. Furthermore, elderly people with chronic illnesses require long-term care, for which they are dependent on others. These stresses can result in isolation, loneliness, and depression.

Marital status and living status were also significantly associated with depression which was akin to the findings by Thilak et al. in the rural areas of Kannur[22] and the study by Chaiut et al. among hill tribe elderly in Thailand.[6] As people get older, they have a greater need for the support of their partners or children which is very important for the psychological well-being of the elderly. A significant association was noted between addictive habits and depression which was similar to the study findings of Jain et al.[23] The association between substance abuse and depression is bi-directional. People who are depressed use substances to lift their mood. Conversely, people become depressed once the effects of these substances wear off.

In the present study, it was seen that all the study subjects who had moderate impairment in ADL were depressed, and this association between independence in ADL and depression was significant. A study by Shinya Matsuda et al. indicated that a person with higher depression showed a higher possibility of worsening in ADL level.[24]


GAD-7 and GDS-15 being screening tools, the generalizability of prevalence of anxiety and depression has its limitations over diagnostic criteria.

  Conclusion Top

The overall prevalence of anxiety in the study was 8.2% of which 4.7% had mild anxiety, 2.9% had moderate anxiety, and 0.6% had severe anxiety. The overall prevalence of depression was 22.4%, of which 18.9% were having moderate depression and 3.5% were having severe depression. Anxiety and depression deserve the same consideration and remedy as any other illness among the elderly. Only a concerted effort from both public and private sectors can bring about remarkable changes in improving this condition. Further studies focusing on Cognition, Dementia, and other mental illness should be planned to address the issue of mental illness at the grassroots level in this vulnerable population.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

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Sukai TB. Geriatric mental health care in India: Issues and challenges. Internat J Appl Soc Sci 2019;6:1024-33.  Back to cited text no. 3
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Rajan SI, Sarma PS, Mishra US. Demography of Indian aging, 2001-2051. J Aging Soc Policy 2003;15:11-30.  Back to cited text no. 5
Chaiut W, Ruanjai T, Trongsakul S, Tamornpark R, Apidechkul T. Prevalence and factors associated with depression among the hill tribe elderly population, Thailand. J Med Assoc Thail 2018;101:977-85.  Back to cited text no. 6
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Correspondence Address:
KV Sindhu,
Department of Community Medicine, School of Public Health, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru, Karnataka
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/amh.amh_103_21


  [Figure 1], [Figure 2], [Figure 3], [Figure 4]

  [Table 1], [Table 2], [Table 3]


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