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Psychological morbidity among co-residents of older people in rural South India: Prevalence and risk factors M Khurram Malik and KS Jacob Int J Soc Psychiatry published online 19 June 2014 DOI: 10.1177/0020764014539287 The online version of this article can be found at: http://isp.sagepub.com/content/early/2014/06/18/0020764014539287
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539287 research-article2014
ISP0010.1177/0020764014539287International Journal of Social PsychiatryMalik and Jacob
E CAMDEN SCHIZOPH
Article
Psychological morbidity among co-residents of older people in rural South India: Prevalence and risk factors
International Journal of Social Psychiatry 1–5 © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0020764014539287 isp.sagepub.com
M Khurram Malik1 and KS Jacob1,2
Abstract Objective: This study attempted to examine psychological morbidity among co-residents of older people living in Vellore, Tamil Nadu, India. Method: This cross-sectional study evaluated psychological morbidity among co-residents using the Self-Reporting Questionnaire and psychiatric morbidity among older people using the 10/66 Dementia Research Group’s populationbased studies protocol. Socio-demographic data were also collected. Logistic regression was used for multivariate analysis. Results: Of 807 residents evaluated, 73 (9.0%) had significant psychological morbidity. Such morbidity was associated with being older, female, poorer, illiterate, currently employed and being a spouse of the older person. A diagnosis of depression, neuropsychiatric symptoms and greater disability in older people were also associated with psychological morbidity among co-residents. Conclusion: Co-residents living with older people have significant psychological morbidity, which needs to be recognised and treated. Keywords Psychological morbidity, co-residents, older people, India
Introduction Psychological distress and morbidity have been documented among older people (Copeland et al., 2004; Rajkumar et al., 2009). They have also been documented in carers (Cuijpers, 2005; Pinquart & Sörensen, 2003) and co-residents (Honyashiki et al., 2011) of older people especially among those caring for people with dementia, mental and physical disease and disability. This study examines psychological morbidity among co-residents of older people living in rural South India.
Method This study was a part of 10/66 Dementia Research Group’s population-based studies (Prince, Acosta, Chiu, Scazufca, & Varghese, 2003). The methodology employed in this study is briefly mentioned here and has been reported elsewhere in detail (Jacob, Kumar, Gayathri, Abraham, & Prince, 2007; Rajkumar et al., 2009). People above the age of 60 years were first identified using a computerised list and by door-to-door survey. All consecutive older people aged 65 years and above, who consented, were enrolled as participants. We have already reported the factors associated with dementia (Jacob et al., 2007), depression (Rajkumar et al., 2009), disability (Duba, Rajkumar, Prince, & Jacob, 2011) and with out-of-pocket
health expenditures (Brinda, Rajkumar, Enemark, Prince, & Jacob, 2012) among these participants. Older people and their informants, who were relatives and usually lived with them (co-residents), were interviewed.
Assessment The Self-Reporting Questionnaire (SRQ; World Health Organization (WHO), 1994) was employed as a casefinding instrument to identify depression, anxiety and common mental disorders among co-residents of older people. It was developed as a screening and case-finding instrument by the WHO mainly for use in low- and middleincome countries to detect psychological morbidity in primary care. Its face, content, criterion and construct validity have been examined. Optimal threshold, sensitivity, specificity and predictive values have been documented. 1Specialist
Mental Health Services for Older People, Penrith, NSW, Australia 2Department of Psychiatry, Christian Medical College, Vellore, India Corresponding author: KS Jacob, Department of Psychiatry, Christian Medical College, Vellore 632002, India. Email: [email protected]
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It employs 20 questions with dichotomous yes/no responses. It has been translated into many different languages and used across diverse cultures and settings. The recommended cut points vary between >3 to < 11 between settings but cluster around >7 (Harpham et al., 2003). Therefore, it was this threshold, which was used to identify psychological morbidity. A structured pro forma to assess socio-demographic characteristics of the carers, relationship with the older subjects, time spent and details of caring was also used. The information on diagnosis among the older subjects was elicited using the following interview schedules: (1) Geriatric Mental State (GMS; Copeland, Dewey, & Griffith-Jones, 1986), (2) Community Screening Instrument for Dementia (CSID; Hall, Hendrie, & Brittain, 1993; Hall et al., 2000), (3) Modified Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) 10-word list learning task (Ganguli et al., 1996), (4) History and Aetiology Schedule Dementia Diagnosis and Subtype (HAS-DDS; Copeland et al., 2002), (5) Neuro Psychiatric Inventory Questionnaire (NPI-Q) (Cummings et al., 1994) and (6) WHO Disability Assessment Scale–II (WHODAS-II) (WHO, 2001). We also obtained selfreports of different mental and physical illnesses. We derived the psychiatric diagnoses among the older subjects based on the computerised algorithms developed by the 10/66 Dementia Research Group (Prince et al., 2003). Tamil versions of these instruments were used. The training of research staff, data collection and quality control procedures were in accordance with 10/66 norms for population-based studies (Prince et al., 2003). The Institutional Review Board of Christian Medical College, Vellore, approved the study.
Analysis We employed descriptive statistics and frequency distributions to describe continuous and categorical variables, respectively. We determined case status among co-residents using the standard threshold (8+) for the SRQ. We examined factors associated with psychological morbidity. We employed the student t-test and the chi-square test to assess the strength of associations. We used logistic regression for multivariate analysis to adjust for common confounders age, gender, income and disability. We employed the statistical software package SPSS version 16.0.
Results We recruited 1000 participants, and the overall response rate was 97.75% (Jacob et al., 2007; Rajkumar et al., 2009). We also recruited 1000 informants, 807 of whom were co-residents. The socio-demographic characteristics of the co-resident and older people are recorded in Table 1. The majority of the co-residents were middle-aged women, with no formal
Table 1. Characteristics of carers in the sample. Characteristic Co-resident’s characteristics Age in years Gender – female Marital status – currently married Relationship Spouse Child Son or daughter-in-law Other No formal education Employment Paid full time Paid part time Housewife Student/retired/unemployed Reported per capita monthly family income (in INR) Total SRQ score SRQ case (8+) Characteristics of older people Age in years Gender – female Marital status – currently married No formal education Employment Paid full time Paid part time Not employed WHODAS-II total score DSM-IV dementia diagnosis 10/66 education adjusted dementia diagnosis ICD-10 depression DSM-IV major depression History of stroke History of transient ischaemic attack History of diabetes mellitus History of high blood pressure History of arthritis problem with significant interference with life History of eye problem with significant interference with life History of hearing problem with significant interference with life History of epileptic fits
Frequency (%), mean (SD) 46.70 (16.11) 669 (82.9) 705 (87.4) 325 (40.3) 162 (20.1) 256 (31.7) 64 (7.8) 370 (45.8) 78 (9.7) 192 (23.8) 433 (53.7) 71 (8.8) 2115.90 (1533.40) 3.90 (2.53) 73 (9.0) 72.52 (5.93) 393 (48.7) 442 (54.8) 502 (62.2) 33 (4.1) 113 (14.0) 661 (71.9) 27.28 (17.95) 6 (0.7) 80 (9.9) 96 (11.9) 32 (4.0) 10 (1.2) 34 (4.2) 54 (6.7) 107 (13.3) 36 (4.5) 16 (2.0) 43 (5.3) 3 (0.4)
INR: Indian Rupees; SRQ: Self-Reporting Questionnaire; WHODAS-II: World Health Organization Disability Assessment Scale–II; DSM-IV: Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition; ICD-10: International Statistical Classification of Diseases and Related Health Problems–10th Revision.
education, were unpaid and informal carers and lived with their older relatives. The majority of the older people were men, currently married and not employed.
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Malik and Jacob Table 2. Factors associated with common mental disorders in co-residents. Characteristic
Characteristics of co-resident Age (years) Gender (female) Family income (IRS)
Case (SRQ ≥ 8); N = 73; no. (%), mean (SD) 54.89 (13.87) 65 (89.0) 1651.60 (1253.6)
Control (SRQ ≤ 7); N = 734; no. (%), mean (SD)
Bivariate statistics – student t-test/ chi-square test
Multivariate statistics – logistic regression
45.89 (16.10)
t = 5.20; df = 92.42; p = .000 χ2 = 2.13; df = 1; p = .14 t = −3.24; df = 95.39; p = .002 χ2 = 26.57; df = 1; p = .000 χ2 = 12.8; df = 1; p = .000 χ2 = 2.93; df = 1; p = .08
OR = 1.04; 95% CI = 1.02–1.06; p = .000
χ2 = 33.21; df = 1; p = .000 χ2 = 7.58; df = 1; p = .006 χ2 = 33.71; df = 1; p = .000 χ2 = 19.97; df = 1; p = .000 t = 9.84; df = 802; p = .000 t = 9.99; df = 802; p = .000 t = 2.67; df = 805; p = .024
OR = 4.64; 95% CI = 2.36–9.12; p = .000 OR = 4.52; 95% CI = 1.26–16.17; p = .021 OR = 4.12; 95%CI 2.31, 7.36; p = 0.000 OR = 4.49; 95% CI = 1.91–10.52; p = .001 OR = 1.32; 95% CI = 1.24–1.45; p = .000 OR = 1.27; 95% CI = 1.20–1.36; p = .000 OR = 1.02; 95% CI = 1.003–1.03; p = .013
604 (82.3) 2162.1 (1551.6)
Relationship – spouse
50 (68.5)
275 (37.5)
Education – nil
48 (65.8)
322 (43.9)
Employed
31 (42.4)
239 (32.5)
17 (23.3)
39 (5.3)
4 (5.5)
9 (1.2)
24 (32.9)
72 (9.8)
10 (13.7)
22 (3.0)
Score/diagnosis in older relative ICD-10 moderate depression ICD-10 severe depression ICD-10 any depression DSM-IV major depression NPI total severity score
5.70 (3.84)
2.08 (3.00)
NPI total distress score
6.95 (4.20)
2.47 (3.59)
31.81 (20.25)
26.83 (17.66)
WHODAS-II score
OR = 2.75; 95% CI = 1.22–6.19; p = .015 OR = 1.00; 95% CI = 1.00–1.00; p = .019 OR = 2.48; 95% CI 1.05, 5.84; p = 0.038 OR = 1.78; 95% CI = 1.04–3.02; p = .034 OR = 2.09; 95% CI = 1.25–3.50; p = .005
SRQ: Self-Reporting Questionnaire; OR: odds ratio; CI: confidence interval; ICD-10: International Statistical Classification of Diseases and Related Health Problems–10th Revision; DSM-IV: Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition; NPI: Neuro Psychiatric Inventory; WHODAS-II: World Health Organization Disability Assessment Scale–II; TIA: transient ischaemic attack. Logistic regression used to adjust for age, gender, income and disability. The following variables were not significantly associated: gender, marital status of carer, active involvement in care, perceived dependence on co-resident and need for care, cut back in employment; older person’s age, gender, ICD-10 mild depression, DSM-IV dementia, 10/66 Dementia diagnosis, stroke, TIA, diabetes, high blood pressure, eye and hearing impairment, epileptic fits.
The mean SRQ total score was 3.90 (median = 4; standard deviation (SD) = 2.53; range = 0–13). Out of 807 subjects 73 (9.0%) scored above the recommended SRQ threshold of 8 or more. The factors associated with psychological morbidity among co-residents on bivariate analysis (Table 2) were co-resident’s age, gender, income, education and employment. Depression, neuropsychiatric symptoms and disability in older people were also associated with psychological morbidity among co-residents. These factors remained significant on logistic regression after adjusting for coresident age, gender and income and older person’s disability (Table 2).
Discussion This is the largest study examining the psychological morbidity among co-residents of older people living in India. Its strengths include its large sample, standard and systematic assessments and multivariate statistics. Its limitations are its cross-sectional design and self-reports related to psychological morbidity among co-residents and selfreports of physical diseases among older people. The results of the study document that about one-tenth of co-residents suffered from significant psychological morbidity. Such morbidity was associated with being older, female, poorer and illiterate. The need for current
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International Journal of Social Psychiatry
employment to meet financial needs and being a spouse of an older person added to the stress of coping. A diagnosis of depression, neuropsychiatric symptoms and greater disability in older people was also associated with psychological morbidity among co-residents. However, physical illness among the older people did not seem to impact on psychological morbidity. The fact that self-reports were used to assess physical morbidity in older people resulted in very low rates in the population and could also explain the lack of association. The lack of association between dementia and co-resident psychological distress is striking. However, similar lack of association was also seen in other populations (e.g. China, Mexico and the Dominican Republic) (Honyashiki et al., 2011). Disability rather than a physical diagnosis per se seems to be related to common mental disorders among co-residents and carers, explaining variation across regions and populations. These results are consistent with psychological morbidity in general being associated with increased age, women, those with low literacy and poverty, and people who have roles as carers (Lorant et al., 2003; Navaie-Waliser et al., 2002; Pothen, Kuruvilla, Philip, Joseph, & Jacob, 2003; Shidhaye & Patel, 2010). The results of this analysis differ from the overall conclusions of the meta-analysis published earlier (Honyashiki et al., 2011). Often large data sets tend to mask variations and local realities particular to specific populations, regions and cultures. This analysis highlights the factors associated with psychological morbidity among co-residents living with older people in rural India. The results also suggest the fact that public health approaches need to examine local reality and study factors associated with morbidity in order to suggest public health strategies to meet specific regional contexts and cultures (Jacob, 2012). It argues that generalising finding from research across regions and employing large sample for meta-analysis may not be appropriate. There is a need for a contextual understanding of issues related to ageing populations in general and morbidity among older people and in their co-residents in particular. Acknowledgements We thank Professor M. Prince, Institute of Psychiatry, London, all the study participants as well as their families for their cooperation and the research fellows Mr Senthil Kumar, Ms Gayathri, Ms Kanagathara and Ms Simon for data collection. K.S.J. supervised and implemented the study. M.K.M. and K.S.J. analysed the data and wrote the manuscript. The authors reviewed the manuscript, read and approved the final draft.
Conflict of interest The authors declare that there is no conflict of interest.
Funding This study is a part of the population-based investigations of the 10/66 Dementia Research group of Alzheimer’s Disease International. It was supported by grants from the World Health Organization and from the Institute of Psychiatry, London.
References Brinda, E. M., Rajkumar, A. P., Enemark, U., Prince, M., & Jacob, K. S. (2012). Nature and determinants of out-ofpocket health expenditure among older people in a rural Indian community. International Psychogeriatrics, 24, 1664–1673. Copeland, J. R., Beekman, A. T., Braam, A. W., Dewey, M. E., Delespaul, P., Fuhrer, R., ... Wilson, K. C. (2004). Depression among older people in Europe: The EURODEP studies. World Psychiatry, 3, 45–49. Copeland, J. R., Dewey, M. E., & Griffith-Jones, H. M. (1986). A computerized psychiatric diagnostic system and case nomenclature for elderly subjects: GMS and AGECAT. Psychological Medicine, 16, 89–99. Copeland, J. R., Prince, M., Wilson, K. C., Dewey, M. E., Payne, J., & Gurland, B. (2002). The Geriatric Mental State examination in the 21st century. International Journal of Geriatric Psychiatry, 17, 727–732. Cuijpers, P. (2005). Depressive disorders in caregivers of dementia patients: A systematic review. Ageing and Mental Health, 9, 325–330. Cummings, J. L., Mega, M., Gray, K., Rosenberg-Thompson, S., Carusi, D. A., & Gornbein, J. (1994). The Neuropsychiatric Inventory: Comprehensive assessment of psychopathology in dementia. Neurology, 44, 2308–2314. Duba, A. S., Rajkumar, A. P., Prince, M., & Jacob, K. S. (2011). Determinants of disability among the elderly population in a rural south Indian community: The need to study local issues and contexts. International Psychogeriatrics, 24, 333–341. Ganguli, M., Chandra, V., Gilby, J.E., Ratcliff, G., Sharma, S.D., Pandav, R., ... Belle, S. (1996). Cognitive test performance in a community-based nondemented elderly sample in rural India: The Indo-U.S. Cross-National Dementia Epidemiology Study. International Psychogeriatrics, 8, 507–524. Hall, K. S., Gao, S., Emsley, C. L., Ogunniyi, A. O., Morgan, O., & Hendrie, H. C. (2000). Community Screening Interview for Dementia (CSI ‘D’): Performance in five disparate study sites. International Journal of Geriatric Psychiatry, 15, 521–531. Hall, K. S., Hendrie, H. C., & Brittain, H. M. (1993). The development of a dementia-screening interview in two distinct languages. International Journal of Methods in Psychiatric Research, 3, 1–28. Harpham, T., Reichenheim, M., Oser, R., Thomas, E., Hamid, N., Jaswal, S., ... AIDOO, M. (2003). Measuring mental health in a cost-effective manner. Health Policy and Planning, 18, 344–349. Honyashiki, M., Ferri, C. P., Acosta, D., Guerra, M., Huang, Y., Jacob, K. S., ... Prince, M. J. (2011). Chronic diseases among older people and co-resident psychological morbidity: A 10/66 Dementia Research Group population-based survey. International Psychogeriatrics, 23, 1489–1501. Jacob, K. S. (2012). Dementia: Toward contextual understanding. International Psychogeriatrics, 24, 1703–1707. Jacob, K. S., Kumar, P. S., Gayathri, K., Abraham, S., & Prince, M. J. (2007). The diagnosis of dementia in the community. International Psychogeriatrics, 19, 669–678. Lorant, V., Deliège, D., Eaton, W., Robert, A., Philippot, P., & Ansseau, M. (2003). Socioeconomic inequalities in
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Malik and Jacob depression: A meta-analysis. American Journal of Epidemiology, 15, 157, 98–112. Navaie-Waliser, M., Feldman, P. H., Gould, D. A., Levine, C., Kuerbis, A. N., & Donelan, K. (2002). When the caregiver needs care: The plight of vulnerable caregivers. American Journal of Public Health, 92, 409–413. Pinquart, M., & Sörensen, S. (2003). Associations of stressors and uplifts of caregiving with caregiver burden and depressive mood: A meta-analysis. Journal of Gerontology. Series B: Psychological Sciences and Social Sciences, 58, 112–128. Pothen, M., Kuruvilla, A., Philip, K., Joseph, A., & Jacob, K. S. (2003). Common mental disorders among primary care attenders in Vellore, South India: Nature, prevalence and risk factors. International Journal of Social Psychiatry, 49, 119–125. Prince, M. J., Acosta, D., Chiu, H., Scazufca, M., & Varghese, M. (2003). Dementia diagnosis in developing countries: A cross-cultural validation study. Lancet, 361, 909–917.
Rajkumar, A. P., Thangadurai, P., Senthilkumar, P., Gayathri, K., Prince, M., & Jacob, K. S. (2009). Nature, prevalence and factors associated with depression among the elderly in a rural south Indian community. International Psychogeriatrics, 21, 372–378. Shidhaye, R., & Patel, V. (2010). Association of socio-economic, gender and health factors with common mental disorders in women: A population-based study of 5703 married rural women in India. International Journal of Epidemiology, 39, 1510–1521. World Health Organization. (1994). A user’s guide to the Self Reporting Questionnaire (SRQ). WHO/MNH/PSF 94.8. Geneva, Switzerland: Author. Retrieved from http://whqlibdoc.who.int/hq/1994/WHO_MNH_PSF_94.8.pdf World Health Organization. (2001). WHODAS II Disability Assessment Schedule: 12-Item interviewer administered version. Geneva, Switzerland: Author.
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Psychological morbidity among co-residents of older people in rural South India: Prevalence and risk factors M Khurram Malik and KS Jacob Int J Soc Psychiatry published online 19 June 2014 DOI: 10.1177/0020764014539287 The online version of this article can be found at: http://isp.sagepub.com/content/early/2014/06/18/0020764014539287
Published by: http://www.sagepublications.com
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>> OnlineFirst Version of Record - Jun 19, 2014 What is This?
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539287 research-article2014
ISP0010.1177/0020764014539287International Journal of Social PsychiatryMalik and Jacob
E CAMDEN SCHIZOPH
Article
Psychological morbidity among co-residents of older people in rural South India: Prevalence and risk factors
International Journal of Social Psychiatry 1–5 © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0020764014539287 isp.sagepub.com
M Khurram Malik1 and KS Jacob1,2
Abstract Objective: This study attempted to examine psychological morbidity among co-residents of older people living in Vellore, Tamil Nadu, India. Method: This cross-sectional study evaluated psychological morbidity among co-residents using the Self-Reporting Questionnaire and psychiatric morbidity among older people using the 10/66 Dementia Research Group’s populationbased studies protocol. Socio-demographic data were also collected. Logistic regression was used for multivariate analysis. Results: Of 807 residents evaluated, 73 (9.0%) had significant psychological morbidity. Such morbidity was associated with being older, female, poorer, illiterate, currently employed and being a spouse of the older person. A diagnosis of depression, neuropsychiatric symptoms and greater disability in older people were also associated with psychological morbidity among co-residents. Conclusion: Co-residents living with older people have significant psychological morbidity, which needs to be recognised and treated. Keywords Psychological morbidity, co-residents, older people, India
Introduction Psychological distress and morbidity have been documented among older people (Copeland et al., 2004; Rajkumar et al., 2009). They have also been documented in carers (Cuijpers, 2005; Pinquart & Sörensen, 2003) and co-residents (Honyashiki et al., 2011) of older people especially among those caring for people with dementia, mental and physical disease and disability. This study examines psychological morbidity among co-residents of older people living in rural South India.
Method This study was a part of 10/66 Dementia Research Group’s population-based studies (Prince, Acosta, Chiu, Scazufca, & Varghese, 2003). The methodology employed in this study is briefly mentioned here and has been reported elsewhere in detail (Jacob, Kumar, Gayathri, Abraham, & Prince, 2007; Rajkumar et al., 2009). People above the age of 60 years were first identified using a computerised list and by door-to-door survey. All consecutive older people aged 65 years and above, who consented, were enrolled as participants. We have already reported the factors associated with dementia (Jacob et al., 2007), depression (Rajkumar et al., 2009), disability (Duba, Rajkumar, Prince, & Jacob, 2011) and with out-of-pocket
health expenditures (Brinda, Rajkumar, Enemark, Prince, & Jacob, 2012) among these participants. Older people and their informants, who were relatives and usually lived with them (co-residents), were interviewed.
Assessment The Self-Reporting Questionnaire (SRQ; World Health Organization (WHO), 1994) was employed as a casefinding instrument to identify depression, anxiety and common mental disorders among co-residents of older people. It was developed as a screening and case-finding instrument by the WHO mainly for use in low- and middleincome countries to detect psychological morbidity in primary care. Its face, content, criterion and construct validity have been examined. Optimal threshold, sensitivity, specificity and predictive values have been documented. 1Specialist
Mental Health Services for Older People, Penrith, NSW, Australia 2Department of Psychiatry, Christian Medical College, Vellore, India Corresponding author: KS Jacob, Department of Psychiatry, Christian Medical College, Vellore 632002, India. Email: [email protected]
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It employs 20 questions with dichotomous yes/no responses. It has been translated into many different languages and used across diverse cultures and settings. The recommended cut points vary between >3 to < 11 between settings but cluster around >7 (Harpham et al., 2003). Therefore, it was this threshold, which was used to identify psychological morbidity. A structured pro forma to assess socio-demographic characteristics of the carers, relationship with the older subjects, time spent and details of caring was also used. The information on diagnosis among the older subjects was elicited using the following interview schedules: (1) Geriatric Mental State (GMS; Copeland, Dewey, & Griffith-Jones, 1986), (2) Community Screening Instrument for Dementia (CSID; Hall, Hendrie, & Brittain, 1993; Hall et al., 2000), (3) Modified Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) 10-word list learning task (Ganguli et al., 1996), (4) History and Aetiology Schedule Dementia Diagnosis and Subtype (HAS-DDS; Copeland et al., 2002), (5) Neuro Psychiatric Inventory Questionnaire (NPI-Q) (Cummings et al., 1994) and (6) WHO Disability Assessment Scale–II (WHODAS-II) (WHO, 2001). We also obtained selfreports of different mental and physical illnesses. We derived the psychiatric diagnoses among the older subjects based on the computerised algorithms developed by the 10/66 Dementia Research Group (Prince et al., 2003). Tamil versions of these instruments were used. The training of research staff, data collection and quality control procedures were in accordance with 10/66 norms for population-based studies (Prince et al., 2003). The Institutional Review Board of Christian Medical College, Vellore, approved the study.
Analysis We employed descriptive statistics and frequency distributions to describe continuous and categorical variables, respectively. We determined case status among co-residents using the standard threshold (8+) for the SRQ. We examined factors associated with psychological morbidity. We employed the student t-test and the chi-square test to assess the strength of associations. We used logistic regression for multivariate analysis to adjust for common confounders age, gender, income and disability. We employed the statistical software package SPSS version 16.0.
Results We recruited 1000 participants, and the overall response rate was 97.75% (Jacob et al., 2007; Rajkumar et al., 2009). We also recruited 1000 informants, 807 of whom were co-residents. The socio-demographic characteristics of the co-resident and older people are recorded in Table 1. The majority of the co-residents were middle-aged women, with no formal
Table 1. Characteristics of carers in the sample. Characteristic Co-resident’s characteristics Age in years Gender – female Marital status – currently married Relationship Spouse Child Son or daughter-in-law Other No formal education Employment Paid full time Paid part time Housewife Student/retired/unemployed Reported per capita monthly family income (in INR) Total SRQ score SRQ case (8+) Characteristics of older people Age in years Gender – female Marital status – currently married No formal education Employment Paid full time Paid part time Not employed WHODAS-II total score DSM-IV dementia diagnosis 10/66 education adjusted dementia diagnosis ICD-10 depression DSM-IV major depression History of stroke History of transient ischaemic attack History of diabetes mellitus History of high blood pressure History of arthritis problem with significant interference with life History of eye problem with significant interference with life History of hearing problem with significant interference with life History of epileptic fits
Frequency (%), mean (SD) 46.70 (16.11) 669 (82.9) 705 (87.4) 325 (40.3) 162 (20.1) 256 (31.7) 64 (7.8) 370 (45.8) 78 (9.7) 192 (23.8) 433 (53.7) 71 (8.8) 2115.90 (1533.40) 3.90 (2.53) 73 (9.0) 72.52 (5.93) 393 (48.7) 442 (54.8) 502 (62.2) 33 (4.1) 113 (14.0) 661 (71.9) 27.28 (17.95) 6 (0.7) 80 (9.9) 96 (11.9) 32 (4.0) 10 (1.2) 34 (4.2) 54 (6.7) 107 (13.3) 36 (4.5) 16 (2.0) 43 (5.3) 3 (0.4)
INR: Indian Rupees; SRQ: Self-Reporting Questionnaire; WHODAS-II: World Health Organization Disability Assessment Scale–II; DSM-IV: Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition; ICD-10: International Statistical Classification of Diseases and Related Health Problems–10th Revision.
education, were unpaid and informal carers and lived with their older relatives. The majority of the older people were men, currently married and not employed.
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Malik and Jacob Table 2. Factors associated with common mental disorders in co-residents. Characteristic
Characteristics of co-resident Age (years) Gender (female) Family income (IRS)
Case (SRQ ≥ 8); N = 73; no. (%), mean (SD) 54.89 (13.87) 65 (89.0) 1651.60 (1253.6)
Control (SRQ ≤ 7); N = 734; no. (%), mean (SD)
Bivariate statistics – student t-test/ chi-square test
Multivariate statistics – logistic regression
45.89 (16.10)
t = 5.20; df = 92.42; p = .000 χ2 = 2.13; df = 1; p = .14 t = −3.24; df = 95.39; p = .002 χ2 = 26.57; df = 1; p = .000 χ2 = 12.8; df = 1; p = .000 χ2 = 2.93; df = 1; p = .08
OR = 1.04; 95% CI = 1.02–1.06; p = .000
χ2 = 33.21; df = 1; p = .000 χ2 = 7.58; df = 1; p = .006 χ2 = 33.71; df = 1; p = .000 χ2 = 19.97; df = 1; p = .000 t = 9.84; df = 802; p = .000 t = 9.99; df = 802; p = .000 t = 2.67; df = 805; p = .024
OR = 4.64; 95% CI = 2.36–9.12; p = .000 OR = 4.52; 95% CI = 1.26–16.17; p = .021 OR = 4.12; 95%CI 2.31, 7.36; p = 0.000 OR = 4.49; 95% CI = 1.91–10.52; p = .001 OR = 1.32; 95% CI = 1.24–1.45; p = .000 OR = 1.27; 95% CI = 1.20–1.36; p = .000 OR = 1.02; 95% CI = 1.003–1.03; p = .013
604 (82.3) 2162.1 (1551.6)
Relationship – spouse
50 (68.5)
275 (37.5)
Education – nil
48 (65.8)
322 (43.9)
Employed
31 (42.4)
239 (32.5)
17 (23.3)
39 (5.3)
4 (5.5)
9 (1.2)
24 (32.9)
72 (9.8)
10 (13.7)
22 (3.0)
Score/diagnosis in older relative ICD-10 moderate depression ICD-10 severe depression ICD-10 any depression DSM-IV major depression NPI total severity score
5.70 (3.84)
2.08 (3.00)
NPI total distress score
6.95 (4.20)
2.47 (3.59)
31.81 (20.25)
26.83 (17.66)
WHODAS-II score
OR = 2.75; 95% CI = 1.22–6.19; p = .015 OR = 1.00; 95% CI = 1.00–1.00; p = .019 OR = 2.48; 95% CI 1.05, 5.84; p = 0.038 OR = 1.78; 95% CI = 1.04–3.02; p = .034 OR = 2.09; 95% CI = 1.25–3.50; p = .005
SRQ: Self-Reporting Questionnaire; OR: odds ratio; CI: confidence interval; ICD-10: International Statistical Classification of Diseases and Related Health Problems–10th Revision; DSM-IV: Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition; NPI: Neuro Psychiatric Inventory; WHODAS-II: World Health Organization Disability Assessment Scale–II; TIA: transient ischaemic attack. Logistic regression used to adjust for age, gender, income and disability. The following variables were not significantly associated: gender, marital status of carer, active involvement in care, perceived dependence on co-resident and need for care, cut back in employment; older person’s age, gender, ICD-10 mild depression, DSM-IV dementia, 10/66 Dementia diagnosis, stroke, TIA, diabetes, high blood pressure, eye and hearing impairment, epileptic fits.
The mean SRQ total score was 3.90 (median = 4; standard deviation (SD) = 2.53; range = 0–13). Out of 807 subjects 73 (9.0%) scored above the recommended SRQ threshold of 8 or more. The factors associated with psychological morbidity among co-residents on bivariate analysis (Table 2) were co-resident’s age, gender, income, education and employment. Depression, neuropsychiatric symptoms and disability in older people were also associated with psychological morbidity among co-residents. These factors remained significant on logistic regression after adjusting for coresident age, gender and income and older person’s disability (Table 2).
Discussion This is the largest study examining the psychological morbidity among co-residents of older people living in India. Its strengths include its large sample, standard and systematic assessments and multivariate statistics. Its limitations are its cross-sectional design and self-reports related to psychological morbidity among co-residents and selfreports of physical diseases among older people. The results of the study document that about one-tenth of co-residents suffered from significant psychological morbidity. Such morbidity was associated with being older, female, poorer and illiterate. The need for current
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International Journal of Social Psychiatry
employment to meet financial needs and being a spouse of an older person added to the stress of coping. A diagnosis of depression, neuropsychiatric symptoms and greater disability in older people was also associated with psychological morbidity among co-residents. However, physical illness among the older people did not seem to impact on psychological morbidity. The fact that self-reports were used to assess physical morbidity in older people resulted in very low rates in the population and could also explain the lack of association. The lack of association between dementia and co-resident psychological distress is striking. However, similar lack of association was also seen in other populations (e.g. China, Mexico and the Dominican Republic) (Honyashiki et al., 2011). Disability rather than a physical diagnosis per se seems to be related to common mental disorders among co-residents and carers, explaining variation across regions and populations. These results are consistent with psychological morbidity in general being associated with increased age, women, those with low literacy and poverty, and people who have roles as carers (Lorant et al., 2003; Navaie-Waliser et al., 2002; Pothen, Kuruvilla, Philip, Joseph, & Jacob, 2003; Shidhaye & Patel, 2010). The results of this analysis differ from the overall conclusions of the meta-analysis published earlier (Honyashiki et al., 2011). Often large data sets tend to mask variations and local realities particular to specific populations, regions and cultures. This analysis highlights the factors associated with psychological morbidity among co-residents living with older people in rural India. The results also suggest the fact that public health approaches need to examine local reality and study factors associated with morbidity in order to suggest public health strategies to meet specific regional contexts and cultures (Jacob, 2012). It argues that generalising finding from research across regions and employing large sample for meta-analysis may not be appropriate. There is a need for a contextual understanding of issues related to ageing populations in general and morbidity among older people and in their co-residents in particular. Acknowledgements We thank Professor M. Prince, Institute of Psychiatry, London, all the study participants as well as their families for their cooperation and the research fellows Mr Senthil Kumar, Ms Gayathri, Ms Kanagathara and Ms Simon for data collection. K.S.J. supervised and implemented the study. M.K.M. and K.S.J. analysed the data and wrote the manuscript. The authors reviewed the manuscript, read and approved the final draft.
Conflict of interest The authors declare that there is no conflict of interest.
Funding This study is a part of the population-based investigations of the 10/66 Dementia Research group of Alzheimer’s Disease International. It was supported by grants from the World Health Organization and from the Institute of Psychiatry, London.
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