|
 
 |
| ORIGINAL ARTICLE |
|
| Year : 2022 | Volume
: 9
| Issue : 2 | Page : 87-92 |
|
Undiagnosed depression and cognitive impairment with possible dementia among elderly population in urban areas of Hyderabad: Prevalence and associated factors
Saba Syed, Pranati Kilaru
Department of Community Medicine, Apollo Institute of Medical Sciences and Research, Hyderabad, Telangana, India
| Date of Submission | 14-Sep-2022 |
| Date of Decision | 03-Nov-2022 |
| Date of Acceptance | 19-Nov-2022 |
| Date of Web Publication | 20-Jan-2023 |
Correspondence Address:
Dr. Saba Syed
10-4-771/8, Flat No 302, Syed Enclave, Sri Ram Nagar Colony, Masab Tank, Hyderabad - 500 028, Telangana
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jgmh.jgmh_46_22
Background: Elderly population in India is steadily increasing and depression and dementia are the most common neuropsychiatric disorders in the older adult population. Epidemiological studies have reported disparity in the prevalence of mental health morbidity in older Indian adults. The aim of the present study was to assess community-based prevalence of undiagnosed depression and cognitive impairment with possible dementia and its associated factors in elderly persons residing in urban areas. Materials and Methods: The present study was a cross-sectional community-based study conducted in persons above 60 years residing in urban localities of selected four different zones of Greater Hyderabad through multistage sampling. The questionnaire consisted of sociodemographic details, the validated “Mini-Mental State Examination (MMSE)” Questionnaire and Geriatric Depression Scale short-form. Results: The study was completed with a total of 230 individuals. The mean age of participants was 68.02 (±5.71) years. The study group comprised 50.87% males and 49.13% females and 56.08% of participants were self-employed/employed. Of total participants, 37.39% were residing alone of whom 70% were male. More than half (57.83%) of study participants had studied less than 8th grade. Cognitive impairment with possible dementia was present in 51.74% of participants, the prevalence of depression was 22.71% and in 16.09% of participants, both conditions coexisted. Factors found to be significantly associated with depression and cognitive impairment with possible dementia or both conditions were current unemployment [Odds ratio [OR] 5.0 (95% CI (2.44–10.81)], residing alone (OR 2.78 [1.48–5.23]) and education less than high school (OR 24.85 [2.53–9.32]). Conclusions: Depression and cognitive impairment with possible dementia were considerably prevalent in the elderly population of Hyderabad, India. Factors significantly associated with the prevalence of either or both conditions were, residing alone and education less than high school.
Keywords: Cognitive impairment, community-based, dementia, depression, elderly persons
How to cite this article:
Syed S, Kilaru P. Undiagnosed depression and cognitive impairment with possible dementia among elderly population in urban areas of Hyderabad: Prevalence and associated factors. J Geriatr Ment Health 2022;9:87-92 |
How to cite this URL:
Syed S, Kilaru P. Undiagnosed depression and cognitive impairment with possible dementia among elderly population in urban areas of Hyderabad: Prevalence and associated factors. J Geriatr Ment Health [serial online] 2022 [cited 2023 Jun 4];9:87-92. Available from: https://www.jgmh.org/text.asp?2022/9/2/87/368296 |
| Introduction | |  |
Globally, the population is aging rapidly, between 2015 and 2050, the proportion of the world's population over 60 years will nearly double, from 12% to 22%.[1] India due to its demographic transition is also witnessing a steady rise in elderly citizens and currently nearly 104 million elderly persons; 53 million females and 51 million males reside here.[2]
As individuals age, significant life events, decline in physical functions due to aging, and other factors can cause chronic stress, exposing them to mental health risks. Depression and dementia are the most common neuropsychiatric disorders in the older adult population but epidemiological studies have reported disparity in the prevalence of mental health morbidity in older Indian adults.[1],[3],[4],[5],[6],[7],[8],[9],[10] The current prevalence of dementia in India is 2.7% with a mean age at presentation being 66.3 years which is a decade younger than in developed countries.[8] The prevalence of depression in older adults shows wide variation from 8.9% to 62.16% in community-based studies[9] Mental health problems however continue to be under-identified by health-care professionals and older people themselves, the stigma surrounding mental illness makes people reluctant to seek help.
Mental health-care services need to be arranged for 17.13 million older adults in the immediate future to meet the service challenges posed by the psychiatrically ill older adults in the country.[11] Assessing the magnitude of burden of mental morbidity in aged persons and their determinants is crucial to planning effective preventive and curative mental health care services. Screening elderly persons for depression and mild cognitive impairment (MCI) which leads to dementia may offer insights into community-based prevalence of these conditions. As scarce population-based studies have been conducted on both depression and cognitive impairment with possible dementia, especially in south India, the present study aimed to assess community-based prevalence of undiagnosed depression and cognitive impairment with possible dementia and its associated factors in elderly persons residing in urban areas.
| Materials and Methods | | |
The present study was a cross-sectional community-based study conducted between June 2021 and January 2022 in urban localities of Greater Hyderabad selected by simple random technique. Approval from the institution's ethics committee was obtained before commencement of the study.
The sample size was calculated with 95% confidence level using the formula n = 4pq/d2 where P = prevalence of depression 34%,[12] q = (1 − p), and d = precision of the study 7%. The calculated minimum sample size was 183.
Sampling technique
Greater Hyderabad is divided into six municipal zones from which two zones were selected. A list of all wards in each zone was drawn up and by systematic random sampling method, 5 municipal wards were selected from each zone with sampling frame of 20. In each ward, 20 houses were selected initially with sampling interval of 10. The first house was labeled as 1 and thereafter every 10th house was approached till sample size of 20 was reached. If selected house did not have elderly persons/inclusion criteria were not met, consecutive houses were approached till an inclusion criteria were met.
The inclusion criteria were individuals above 60 years of age and willing to give consent. Any eligible person who was found seriously ill or not willing to give consent, already diagnosed with depression and or dementia was excluded from the study. The study was finally completed with a total of 230 individuals above the age of 60 years.
Data collection instrument was a pretested semi-structured questionnaire which comprised socio-demographic details of the respondents such as name, age, gender, and education level. The second part of questionnaire consisted of the validated “Mini-Mental State Examination (MMSE)” Questionnaire, which assessed the respondents' orientation, registration, attention and calculation, recall, language, and praxis. The MMSE is the best-known and widely used short screening tool for providing an overall measure of cognitive impairment in clinical, research, and community settings.[10]
The third part of the questionnaire consisted of the validated “Geriatric Depression Scale (GDS) short form” Questionnaire, which included 15 questions that the respondent had to answer based on how he/she felt over the past week. The MMSE and the GDS were administered by translating into the local language of the study population. All persons who screened positive for depression and MCI were referred to the psychiatry department for further management.
Operational definition
Mini-Mental Scale
The (MMSE) questionnaire included five components such as orientation, registration, attention and calculation, recall, language and praxis. Orientation comprised two questions that scored 5 points each, totaling 10 points. Registration comprised of one question scored 3 points. Attention and calculation comprised of one question total of 5 points were awarded. Recall comprised of one question for 3 points. Language and praxis comprised 6 questions out of which 4 questions were for one point each. One question was for 2 points and one question was for 3 points, totaling to 9 points. The scores were totaled and grouped based on the respondents' education level and following scores were taken as abnormal (cognitive impairment indicative of possible dementia.):
- Score 21 abnormal for 8th grade education and below
- Score <23 abnormal for high school education
- Score <24 abnormal for college education.
The Geriatric Depression Scale
The GDS questionnaire (GDS short form) had 15 questions with a yes or no answer and score was given according to the validated answers in the “GDS short form” Questionnaire. A score of above 5 was suggestive of depression.[13] Participants who had screened positive were referred to the psychiatry department of the institution where researchers are affiliated and assistance was also offered to all patients who could not access these services on their own.
Statistical analysis
Data were entered into MS Excel and analyzed using IBM SPSS Statistics for Windows, version XXIV (IBM Corp., Armonk, N.Y., USA). Categorical data were presented in the form of frequencies and percentages of numerical data as mean, median, and standard deviation. The prevalence of depression, being prone to dementia and both conditions were calculated. Univariate analysis was applied to calculate the odds ratios (ORs) for associated factors with either condition.
| Observations and Results | | |
The study was finally conducted with 230 participants. The mean age of participants was 68.02 (±5.71) years. There were 117 (50.87%) males and 113 (49.13%) females. The mean age of male participants was 69.89 (±6.31) and of female participants was 66.10 (±4.25) years. Majority (95.71%) of participants were Hindus, 3.48% were Muslims, and 1.3% were Christians.
Employment status
A total of 129 (56.08%) of study participants were self-employed/employed at the time of the study, 94 (40.97%) participants were unemployed and 7 (3.04%) participants were retired. Among participants who were self-employed/employed farming was the major occupation in 78 (60.47%) participants, of whom 53.15% were males and 47.85% were males. Teaching was occupation of 15.50% of participants followed by business in 13.95% participants. Other participants were religious leaders (3.10%), doctor (0.78%), nurse (1.55%), and real estate agents (4.65%).
Residence status
Of total of 230 participants, 144 (62.61%) participants were residing with children and 86 (37.39%) were residing alone. Among participants who were residing alone majority 61 (70.93%) were males and 25 (29.07%) were female.
Education
More than half 133 (57.83%) of study participants had studied less than 8th grade of whom majority (60.15%) were female, 52 (22.61%) had studied up-till high school and 45 (19.57%) participants had a college degree of whom 73.33% were males.
(CI) with possible dementia
The mean MMSE score of all study participants was 19.97 (±6.86) and the median score was 18. In male participants, the mean MMSE score was 21.96 (±6.86) with a median score of 22 and in female participants, the mean MMSE score was 17.9 (±6.66) with a median score of 16. The MMSE score was found to be significantly higher in male participants as compared to female participants (P < 0.001).
A total of 119 (51.74%) participants had cognitive impairment with possible dementia [Figure 1]; majority (59.66%) were male and 40.34% were female.
Prevalence of depression
The mean GDS score of all study participants was 2.36 (±2.47). In male participants, the mean GDS score was 2.22 (±2.41) and in female participants, the mean GDS score was 2.50 (±2.54) with a median score of 1 in both males and females. The mean MMSE score was higher in female participants but the difference was not statistically significant (P > 0.05).
The prevalence of depression [Figure 1] among participants was 22.71%, among whom 27 (51.92%) were male participants and 25 (48.08%) were female participants.
Prevalence of both: Depression and cognitive impairment
The prevalence of both depression and cognitive impairment with possible dementia [Figure 1] was found to be 16.09%, of whom 22 (59.65%) were female and 15 (40.54%) were male.
Association of factors with prevalence of depression and cognitive impairment with possible dementia
The following factors were found to be significantly associated with either or both depression and cognitive impairment with possible dementia: current unemployment [OR 5.0 [95% confidence interval (2.44–10.81)], residing alone (OR 2.78 [1.48–5.23]) education less than high school (OR 24.85 [2.53–9.32]). The age of participants was not found to be significantly associated with either prevalence of depression and/or being prone to dementia. The association of factors associated with the prevalence of depression and/or being prone to dementia is depicted in [Table 1]. | Table 1: Association of sociodemographic factors associated with prevalence of depression and or being prone to dementia
Click here to view |
| Discussion | | |
Over 20% of India's 150 million elderly population suffer from a mental or neurological disorder with depression and dementia being the most common.[14] The present cross-sectional community-based study assessed the prevalence of depression and dementia in persons above 60 years by screening 230 individuals.
Prevalence of cognitive impairment indicative of possible dementia
Dementia syndrome presents as an impairment of mental processes such as memory, thinking, reasoning, and judgment which seriously impairs an individual's ability to perform functions of daily living, and in later stages and patients may not be able to take care of themselves.[8] MCI is a state intermediate between normal cognition and dementia, with essentially preserved functional abilities.[14] In the present study, the prevalence of cognitive impairment indicative of possible dementia was found to be 51.74%, which is higher than reported by other population-based studies from India which ranges from 1% in West Bengal, 10.6% in Chennai, and 25% in Gujarat.[15],[16] However, the exact community prevalence of dementia still remains undetermined.
A higher prevalence of cognitive impairment in the present study could be due to the use of screening tool (MMSE) as opposed to a diagnosis of dementia by DSM IV and reflect differences in sampling methods. Findings also indicate a higher prevalence of cognitive impairment which could progress to dementia in these persons; as brain changes which eventually lead to dementia are known to start at least two decades before the presentation of overt clinical symptoms.
In 2020, 5.3 million, i.e., 1.67% of total population above 60 years in India were living with dementia. Determinants of dementia are large vessel strokes, diabetes, hypertension, obesity, tobacco use, and dyslipidemia. Genetic factors, urban residence, older age, females, low education, low BMI, Vitamin B12, and Vitamin D deficiency, hyperhomocysteinemia are other risk factors found to be associated with dementia in India.[12]
Prevalence of depression
Depression results from the complex interaction of biological predisposition and life events or the person's social and internal world as a potent source of depressive risk over the lifespan.[17]
In the present study, the prevalence of depression among elderly persons was 22.71%. Published studies from different regions in India have reported the prevalence of depression in the elderly varying from 5% to 60% compared to global prevalence of 10.3%.[6],[7],[8],[9],[10],[11],[12],[13],[14],[16],[18],[19] In a recent systematic review and meta-analysis from India, community-based prevalence of depression among the Indian elderly population was reported 34.4%.[12] A recent study from Tamil Nadu has reported 35.5% community prevalence of depression assessed by GDS.[18]
Differences in tools for assessing depression, sampling techniques, and regional sociocultural differences may be probable reasons for the variation of results among studies. Among various screening tools for depression, GDS, and CES-D are used commonly including in the present study. The Geriatric Depression Rating Scale uses a brief yes/no format but is a patient self-report measure of depression and it has limitations when used in patients with MCI/dementia. In the present study, however, the researcher had asked questions in the local language wherever participants could not self-administer the study instruments.
In the present study, the mean age of participants was 68.02 (±5.71) years, male participants with depression were almost equal (50.87%) to female participants. Female preponderance has been reported by comparable studies on depression in elderly persons by Andreasen P et al. (62.1%), Pilania et al., and Rodriguez et al.[12],[14]
Both conditions, i.e., depression and cognitive impairment were present in 16.09% of persons in the present study. In a recent meta-analysis which included 20,892 patients from 57 studies published between 2002 and 2015, comorbidity of depression in patients with MCI was reported to be 32%.[19]
Factors associated with depression and/or cognitive impairment with possible dementia
In the present study, factors found to be significantly associated with the prevalence of depression and MCI suggestive of dementia in elderly were current unemployment [OR 5.0 [95% CI (2.44–10.81)] (P<0.001), residing alone (OR 2.78 [1.48–5.23]) (P<0.001) and education less than high school (OR 4.85 [2.53–9.32]) (P<0.001). Current unemployment as a significant factor associated with depression and/or dementia could be indicative of inadequate/lack of financial security and the accompanying emotional vulnerability among elderly persons in India. Residing alone is a factor of concern in elderly persons who are in current/would be in need of physical, nutritional, and emotional support from caregivers, preferably their family members. According to a study, 6% of India's elderly population lives alone, and living alone makes them vulnerable to force, neglect, and even crime.[20]
Memory is one of the most vulnerable psychological function associated with aging and both depression and dementia. Attaining education has been shown to be associated with better cognitive performance and reduced risk for cognitive impairment and dementia in late life. Lack of education less than high school has been shown to affect memory processes in the elderly and may augment the onset or severity of both depression and/or dementia in elderly persons. Thus, education especially higher may be protective in preserving memory through efficient cognitive processing and use of networks.[21]
Low income, bereavement, isolation, neglect, retirement, hunger, decline in socio-economic status, history of cardiac illnesses, head injury, and diabetes are some factors associated with depression reported by comparable studies in India.[16],[17],[18],[19]
Certain changing sociocultural factors unique to the Indian milieu may contribute to burden of depression and/or cognitive impairment in the elderly. Elderly have been traditionally respected in Indian culture with adult children continuing to reside with parents after marriage and having a family of their own. Indian parents in general do not save much and spend their lifesavings on children's upbringing in the understanding that in their old age they would be well taken care of by them. However, with changing societal norms, disintegration of joint family system, there are increasing numbers of elderly admitted to old age homes voluntarily/nonvoluntarily. Among those who live with their children; some face neglect, inheritance-related coercion, and even violence. In addition, a sizeable of young- and middle-aged Indians has migrated to various countries leaving behind vulnerable elderly parents who live alone. The health needs of geriatric persons and their mental well-being have also been traditionally neglected by the over-burdened Indian public health system. All factors result in financial, nutritional, and emotional insecurity and affect the mental health of elderly persons.
Findings of the present study show considerable community-based prevalence of depression (22.7%), cognitive impairment with possible dementia (51.7%), and both conditions (in elderly persons of urban Hyderabad). Both depression and dementia are disabling conditions detrimental to well-being of elderly persons. Large-scale population-based prospective studies on cognitive impairment and dementia to ascertain their prevalence and determinants in the Indian scenario would aid in designing specific preventive interventions. Multimodal lifestyle modifications are promising strategies and include attainment of higher education, improving cardiovascular health through regular moderate physical activity, engagement in mental, spiritual, and social activities, and abstaining from tobacco.[22] Interventions should factor in social, financial psychological, and health-care support for elderly in India.
Strengths of the present study
Findings of the study add to evidence base of the prevalence of cognitive impairment and depression and its associated factors among the elderly population residing in urban areas.
Challenges and limitations of the present study
The challenges faced while conducting the study were language differences and the usage of local colloquial terminologies for different terms in the questionnaire. The researchers had prepared a list of these terms in different languages spoken in Telangana and used as appropriate. Another challenge was that some patients who screened positive for depression/dementia did not want to go to a hospital and some expressed that they could not access health services due to either financial reasons/lack of someone to accompany them.
The limitation of the study was its cross-sectional. The present study did not involve follow-up of patients to assess their confirmation of diagnosis, initiation of treatment, and outcomes.
| Conclusions | | |
Depression and cognitive impairment with possible dementia were considerably prevalent in elderly population of Hyderabad, India. Factors significantly associated with the prevalence of depression were current unemployment, residing alone, and education less than high school.
Acknowledgment
The authors would like to acknowledge the support and guidance of the Institutional review board and faculty of the Department of Community Medicine, AIMSR.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | |
| 2. | |
| 3. | Ramchandran V, Sarda MM, Ram MB. Psychiatric disorders in subjects aged over fifty. Indian J Psychiatry 1979;22:193-8.  |
| 4. | Rao AV, Madhavan T. Gerospsychiatric morbidity survey in a semi-Urban area near Madurai. Indian J Psychiatry 1982;24:258-67. [ PUBMED] [Full text] |
| 5. | Prakash R, Chaudary SK, Singh U. A study of morbidity pattern among geriatric population in the urban area of Udaipur, Rajasthan. Indian J Community Med 2004;119:35-40. |
| 6. | Srivastava RK, editor. Multi-Centric Study to Establish Epidemiological Data on Health Problems in Elderly. WHO [ World Health Organization]: WHO-Govt. of India Report; 2007. |
| 7. | Tiwari SC. Geriatric psychiatric morbidity in rural northern India: Implications for the future. Int Psychogeriatr 2000;12:35-48. |
| 8. | Premarajan KC, Danabalan M, Chandrasekar R, Srinivasa DK. Prevalence of psychiatry morbidity in an Urban community of Pondicherry. Indian J Psychiatry 1993;35:99-102. [ PUBMED] [Full text] |
| 9. | Tiwari SC, Kar AM, Singh R, Kohli VK, Agarwal GG. An Epidemiological Study of Prevalence of Neuro-Psychiatric Disorders with Special Reference to Cognitive Disorders, Amongst (Urban) Elderly – Lucknow Study. New Delhi: ICMR Report; 2009. |
| 10. | Tiwari SC, Srivastava G, Tripathi RK, Pandey NM, Agarwal GG, Pandey S, et al. Prevalence of psychiatric morbidity amongst the community dwelling rural older adults in Northern India. Indian J Med Res 2013;138:504-14. [ PUBMED] [Full text] |
| 11. | Tiwari SC, Pandey NM. Status and requirements of geriatric mental health services in India: An evidence-based commentary. Indian J Psychiatry 2012;54:8-14. [Full text] |
| 12. | Pilania M, Yadav V, Bairwa M, Behera P, Gupta SD, Khurana H, et al. 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. |
| 13. | Sinha SP, Shrivastava SR, Ramasamy J. Depression in an older adult rural population in India. MEDICC Rev 2013;15:41-4. |
| 14. | Llibre Rodriguez JJ, Ferri CP, Acosta D, Guerra M, Huang Y, Jacob KS, et al. Prevalence of dementia in Latin America, India, and China: A population-based cross-sectional survey. Lancet 2008;372:464-74. |
| 15. | Ravindranath V, Sundarakumar JS. Changing demography and the challenge of dementia in India. Nat Rev Neurol 2021;17:747-58. |
| 16. | Sumana M, Sreelatha CY, Sreeranga A, Arpitha B, Akshatha SP, Anand HD. Prevalence of dementia and other psychiatric morbidities among geriatric population of Salagame primary health Centre in Hassan district, Karnataka, India. Int J Community Med Public Health 2016;3:1315-7. |
| 17. | O'Sullivan C. The psychosocial determinants of depression: A lifespan perspective. J Nerv Ment Dis 2004;192:585-94. |
| 18. | Buvneshkumar M, John KR, Logaraj M. 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. [ PUBMED] [Full text] |
| 19. | Ismail Z, Elbayoumi H, Fischer CE, Hogan DB, Millikin CP, Schweizer T, et al. Prevalence of depression in patients with mild cognitive impairment: A systematic review and meta-analysis. JAMA Psychiatry 2017;74:58-67. |
| 20. | Lee J, Park H, Chey J. Education as a protective factor moderating the effect of depression on memory impairment in elderly women. Psychiatry Investig 2018;15:70-7. |
| 21. | UNFPA, BKPAI Report on Status of the Elderly in the Select States of India, 2011 and the State Reports; 2012. |
| 22. | Ciumărnean L, Milaciu MV, Negrean V, Orăşan OH, Vesa SC, Sălăgean O, et al. Cardiovascular risk factors and physical activity for the prevention of cardiovascular diseases in the elderly. Int J Environ Res Public Health 2021;19:207. |
[Figure 1]
[Table 1]
|
Search Pubmed for