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ORIGINAL ARTICLE
Year : 2019  |  Volume : 63  |  Issue : 1  |  Page : 51-57  

Development of integrated care tool – BRIEF for screening the unmet psychosociomedical needs of older Indians


1 Assistant Professor, Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India
2 Professor, Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
3 Professor, Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India
4 Independent Researcher, Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
5 Physiotherapist, Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India
6 Professor and Head, Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India

Date of Web Publication12-Mar-2019

Correspondence Address:
Dr. Prasun Chatterjee
Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijph.IJPH_187_18

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   Abstract 


Background: With demographic shifts, there is an unprecedented increase in noncommunicable diseases, multimorbidity, and geriatric syndromes among older adults, especially in economically weaker sectors. However, there is no socioculturally appropriate tool to screen older adults for age-related health needs, multimorbidity, and geriatric syndromes at their doorstep. Objective: Our objective was to create a self-assessment tool, “integrated care tool” (ICT), and to assess its psychometric properties by applying it on older adults from multiple settings such as hospital, community, and old-age home (assisted living services). Methods: new questionnaire was developed using standardized procedure including item development, pilot testing, and psychometric validation. After obtaining the institutional ethics committee clearance, data were collected from consenting respondents attending the Outpatient Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, community settings through health camps, and long-term care center, between May 2016 and February 2017. Data were computerized and analyzed by principal component analysis as extraction method and orthogonal varimax as rotation method. Results: The final 30-item questionnaire was arranged into various domains as per rotated component matrix analysis. Overall internal consistency of the final questionnaire, as calculated by Cronbach's alpha, was 0.79, and the measure of sampling adequacy was 0.79. Conclusion: ICT-BRIEF is a simple, self-assessment/caregiver-assisted tool to screen the health needs of older adults. This tool can be validated for developing risk score and scaled up to generate a large database to create elderly centered care plans.

Keywords: Active aging, intrinsic capacity, self-assessment tool


How to cite this article:
Chatterjee P, Rebok GW, Dwivedi SN, Kumar DA, Madan R, Dey AB. Development of integrated care tool – BRIEF for screening the unmet psychosociomedical needs of older Indians. Indian J Public Health 2019;63:51-7

How to cite this URL:
Chatterjee P, Rebok GW, Dwivedi SN, Kumar DA, Madan R, Dey AB. Development of integrated care tool – BRIEF for screening the unmet psychosociomedical needs of older Indians. Indian J Public Health [serial online] 2019 [cited 2019 May 25];63:51-7. Available from: http://www.ijph.in/text.asp?2019/63/1/51/253883




   Introduction Top


India, home of world's second largest elderly population,[1] is preparing to provide dignified and independent late life but at a snail's pace.[2] The obvious challenges against active aging, which is defined as the process of optimizing opportunities for health, participation, and security to enhance quality of life as people age,[3] are multimorbidity and functional decline due to age-specific health and social and familial issues.[3] National Programme for the Health Care of Elderly [4] was a much-needed step by the Government of India to cater to the needs of older adults in a comprehensive way but with its implementation difficulties.[2] Health awareness and health-seeking behavior among older adults are poor [5] even though noncommunicable diseases such as diabetes mellitus, hypertension, and coronary artery diseases are highly prevalent among this group.[6] Further, it has been documented that most of the older Indians from poor socioeconomic status visit hospital only when the symptoms are too obvious due to end-organ damage.[7] This not only increases the hospital burden but also leads to wasteful expenditure of national health budget. Similarly, very few seek health care for common age-related ailments such as sleep problems, uneventful fall, forgetfulness, social isolation, and depression unless these ailments affect their activities of daily living (ADL). As of today, there is no mechanism in place to actively screen these age-related problems at doorstep.

Elderly health is a comprehensive concept of cumulative effect of multiple interlinked domains, which include (a) physical – organ-specific problems such as impairment in vision and hearing, heart, and lung problems; (b) functional – related to physical independence; (c) psychological – about mood and anxiety; (d) mental health – cognitive status; (e) geriatric syndromes – clinical conditions in older persons that do not fit into discrete disease categories, very often present with atypical symptoms such as frailty, falls, incontinence, and polypharmacy and lead to significant disability;[8] (f) financial security and social involvement – determine active aging; (g) elder abuse – a roadblock against successful aging; and (h) health perception and life satisfaction.[9]

EASYCare-2010[10] is one such instrument that was framed and validated in educated elderly. However, it has got some limitations to be applied in Indian scenario, which are as follows: (a) it does not assess the frailty status of older participants which is an important predictor for vulnerability,[11] (b) life satisfaction, a surrogate marker of active aging, has not been included, (c) it is time-consuming with 49 items, so it might be difficult for older adults to respond to, and (d) the questions of EASYCare-2010 are close-ended with yes/no options, difficult to answer sometimes. For example, for the question, “During the last month, have you often been bothered by feeling down, depressed or hopeless?,” the options available in the questionnaire are “Yes” or “No.” It may be difficult for less-educated older adults to answer close-ended questionnaire with confidence as their answer could be “sometimes.”

To overcome these limitations and to screen elderly at their doorstep, we created a socioculturally appropriate simple, easy-to-understand, less time-intensive, and self-assessment tool with Likert type of items, including all the relevant domains such as physical, functional, psychological, mental health, geriatric syndromes, financial security, social involvement, elder abuse, health perception, and life satisfaction. The objective of the present study was to create a self-assessment tool “integrated care tool” (ICT) and to assess its psychometric properties by applying it on older adults from multiple settings such as hospital, community, and old-age home (assisted living services).


   Materials and Methods Top


Development of the integrated care tool

Approval from the institutional ethics committee, All India Institute of Medical Sciences (AIIMS), New Delhi, was obtained before the commencement of the study (IEC/NP/67/06.02.2015, RP-09/2015).

Development of ICT was carried out as per previously reported procedure including item development, pilot testing, and psychometric validation.[12] Items pertaining to various domains were generated with the help of experts from the respective fields, including geriatricians, statistician, public health specialist, epidemiologist, psychiatrist, dietician, physiotherapist, and public health scientist. This process involved extensive review of literature pertaining to each domain, interaction with target group, examination of each selected item by expert committee, and cognitive debriefing of a small number of target population.

Following literature survey [Annexure A] and target group interaction, 40 items representing various domains including physical, functional, geriatric syndrome, vaccination, mental health, social, finance, state of well-being, and safety which reflected the construct-concept of ICT were generated. Ten consenting older adults were interviewed by the members of expert committee, and responses obtained from this interaction were qualitatively analyzed to check the construct-concept of each item. A list of 40 draft items was developed based on the construct-concept while taking utmost care to avoid the omission of necessary concepts. Cognitive debriefing was performed on 10 participants to assess whether respondents understand the questionnaire the same as it would be understood.



Pilot testing of the questionnaire was performed by circulating it among doctors (10) and older adults (10 participants), and feedback from the respondents was analyzed to evaluate its readability, clarity, and comprehensiveness. Face validity was established by having experts look at the items in the questionnaire and support their relevance. It was then translated into Hindi with the help of a language expert followed by back translation to English to ensure quality, precision, and accuracy in the questions. Care was taken to include both positively and negatively worded items to avoid the chances of acquiescent response by the study participants. Once consensus was obtained from all members, the questionnaire was finalized. Protocol also included questions pertinent to sociodemoeconomic and morbidity profile. Options for the questions were framed in the form of Likert type of items as respondents can choose one option that best aligns with their view. It helps to express the extent to which the respondents agree or disagree with a particular question or statement.[13]

Psychometric evaluation

A cross-sectional study was conducted to collect responses to each item in the questionnaire for psychometric validation.

Study location

Data were collected from (1) older adults attending the Outpatient Department (OPD) of Geriatric Medicine, AIIMS, New Delhi, (2) residents of Tau Devi Lal Old Age Home, Faridabad, and (3) health-care seeking older adults from the community through health camps (Vasant Kunj, Noida, and Hazaribagh) to have representation from various strata of the society.

Inclusion and exclusion criteria

Older adults (aged 60 and above), who consented to participate, were included in this study. Denial of consent was the only exclusion criteria.

Study duration

The data collection was from May 2016 to February 2017.

Participants and survey procedure

Data from 290 respondents (170 from OPD, Department of Geriatric Medicine, AIIMS, New Delhi, 90 from Vasant Kunj Health Camp, and 30 from Tau Devi Lal Old Age Home) were randomly collected using ICT containing 40 questions, described as follows:

  • Geriatric medicine OPD (AIIMS), New Delhi: the objective and possible outcomes of the study were explained to the patients and caregivers who were waiting for consultation. A group of volunteers were trained by the principal investigator to ensure uniformity in explaining study objectives and data collection after obtaining informed written consent. The participants were instructed to read and fill the questionnaire. Average time taken by the participants to complete the questionnaire (original) was 20 min. The duration was 30 min if assisted by caregiver/volunteer
  • Community: Health camp was organized at Vasant Kunj, New Delhi, on November 16, 2016, by Healthy Aging India, a nonprofit organization, in association with the Department of Geriatric Medicine, AIIMS, New Delhi. A group of facilitators, comprising 4–6 elderly people, and their caregivers were trained for sensitization on data collection through a focus group discussion. Twenty study participants were allocated per facilitator. One week before, the camp facilitators traveled along the area to get the questionnaire filled in by respondents or with the help of caregivers. Travel expenses were borne by Healthy Aging India. On the designated day, doctors from AIIMS visited the area and examined the registered respondents through comprehensive geriatric assessment and free medicines were provided. Complicated cases were referred to the Department of Geriatric Medicine, AIIMS, for further management.


A list of long-term care centers (old-age home) was obtained from the Ministry of Social Justice and through internet survey. The volunteers telephonically contacted various long-term care centers randomly. The first center to give consent to conduct the study was Tau Devi Lal Old Age Home, Faridabad, Haryana. It comprised 75 older adults and their general and health-care needs were completely borne by the owner of the center. To collect data, trained volunteers of Healthy Aging India visited the center and registered the consenting participants. After getting informed written consent, the participants were instructed to fill the questionnaire. Doctors from AIIMS also visited the center to conduct comprehensive health checkup, and medicines were distributed free of cost to all residents.

Statistical analysis

Of 290 respondents, data from 267 were computerized as the rest were incomplete. Statistical analysis was performed using SPSS software (Version: 20.0, Armonk, NY: IBM Corp). Intercorrelations between the items were analyzed in two steps. A significant Bartlett's test of sphericity was examined for possible intercorrelations of the items and a determinant of correlation matrix <0.00001 revealed if there is any multicollinearity.[14]

Although intercorrelations between the items is a requirement to avoid the problem of collinearity, the correlation matrix was examined to observe the presence of high correlation between items which can cause difficulties in the determination of unique contribution of an item. One of the two highly correlated items (having a correlation of ≥0.70 or more) was removed instead of random deletion of the items.[14]

Internal consistency was determined using Cronbach's alpha Coefficient. A coefficient of 0.7 or higher was considered as acceptable test–retest reliability.[15] Factor analysis was performed to elucidate the construct validity, using principal component analysis method as extraction method, which creates uncorrelated linear combinations of weighted observed variable and accounts for the maximal amount of variance present in the data. Orthogonal varimax method was used as the rotation method.

Further, analysis was repeated after reducing four highly correlated items, to see any variations in the results. Items were grouped into various domains based on the highest value obtained in the correlation matrix. Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphericity of analysis showed inadequate sampling (KMO <0.5); hence, the need of further modification and item reduction of the original questionnaire was warranted.

Following this step, the questionnaire was reviewed by the subject and the language experts, to further reduce the number of questions and to simplify the language. Care was taken during this process to address the original research questions and not to affect the overall structure and reliability of the questionnaire. The sample size was reviewed and decided in view of the required sample size for factor analysis.[16],[17] The sampling adequacy was further reflected by appropriate KMO value.[18],[19] Modified questionnaire had 30 questions (ICT-BRIEF) belonging to nine domains [Annexure B].



Second phase of the study

Using the modified questionnaire, data from 635 respondents were collected from Geriatric Medicine OPD (244), Tau Devi Lal Old Age Home (14) inhabitants, and the community through health camps at Hazaribagh, representing rural India, on February 18 and 19, 2017 (355 respondents), and Noida on February 25, 2017 (23 respondents), by following the same procedure as explained in the first phase. Statistical analysis was performed as described above.


   Results Top


The mean age of the sample was 66.8 ± 7.0 years and 52% were males. Demographic data of the study participants are summarized in [Table 1]. The questions were distributed into various domains as per the highest numeral (irrespective of the sign) obtained in the rotation matrix [Table 2]. Measure of sampling adequacy and Bartlett's test of sphericity were found to be satisfactory (KMO >0.7), as given in [Table 3]. Overall internal consistency of the final questionnaire, as calculated by Cronbach's alpha, was found to be 0.79, which is satisfactory. Sequence of the domains was rearranged for the convenience of data collection [Table 4].
Table 1: Demographic characteristics of the participants

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Table 2: Rotated component matrix for questionnaire with 30 questions

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Table 3: Kaiser-Meyer-Olkin and Bartlett's test

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Table 4: Distribution of questions into various domains

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   Discussion Top


ICT-BRIEF was found to have good internal consistency and content validity. It covered all domains relevant to older adults.[9] It is simple and can be easily filled in by an individual who can read and understand Hindi or with the help of the caregiver and takes only 15 min to complete.

Statistically, physical domain included questions related to vision, hearing, and falls. Hearing loss and vision impairment, which are mostly under corrected,[20] are known to have a direct relationship with falls in elderly as these factors help an individual to have spatial and environmental awareness and thus in planning and coordinating the movement.[21],[22] Fall is often an ignored entity by individual and family members although it has detrimental effect on overall quality of life other than morbidity and mortality.[23]

Responses on chewing, deglutition, and process of eating were found to be in the same domain. These physiological processes are usually found to be impaired among older adults due to various reasons such as loss of tooth,[24] ill-fitting dentures,[25] hyposalivation due to atrophy of glands, gum diseases, and hormonal imbalance.[26] Further, this may lead to malnutrition and sarcopenia and related complications.[26] As per the reports from various parts of India, malnutrition ranges from 11.6% to 51.67% among older Indians.[27],[28]

Difficulty in urination, urinary incontinence (UI), and constipation were in the same domain along with ADL impairment (ability to dress up and to get up from chair or floor). The possible explanation could be that constipation and UI are highly prevalent among functionally impaired and frail population.[29],[30]

Geriatric syndrome, frailty (measured by frequency of going out of the house per week), and cognitive decline (forgetfulness) were found to be along with mood disorders (restlessness and sleep disorder). A population-based study by Kulmala et al. revealed a strong association between frailty and cognitive impairment.[31] Further, it is evidenced from various studies that frailty is associated with restricted life-space mobility [32] and depression.[33]

Responses on weight loss, polypharmacy, and hospital admission were in the same domain. Polypharmacy and weight loss, either independently or together, can lead to recurrent hospital admission as reported by Koh et al.[34] and Moriguti et al.[35] Unintentional and medically significant weight loss is an alarming sign among older Indians, tuberculosis and malignancy being the common factors.[36] Hence, it usually leads to hospital admission for further evaluation and investigation.

Sharing thoughts and feelings, contact during emergency, and feeling of safety at home were in the same domain (social domain). Sharing ones' feelings with friends and family members can make the elderly individuals feel secure and safe as social coherence helps a person to cope with both internal and external stress and the feeling of insecurity.[37] The problems of loneliness and social isolation are conventionally explained as normal aging changes and often ignored. This finding is of great significance, especially in this era where there is a rapid shift from the traditional joint family to nuclear family system.[38]

Domain named social security included the responses on financial management, feeling of safety outside home, and neglect at home. A possible hypothesis could be that a person who is financially independent would have stronger support from family members, thereby improving safety, or the person can opt for a safe and secure atmosphere even outside his/her home due to affordability.

Elder abuse, both physical and mental, is increasingly becoming pertinent to elderly healthcare and to society. According to a survey conducted in 12 cities across India, 50% of elderly people experienced abuse.[38] Elder abuse can lead not only to physical injuries but also can cause long-lasting psychological consequences, including depression and anxiety.[38]

Health perception and life satisfaction were in the same domain (state of well-being), probably the most comprehensive and holistic parameters to explain the overall health of an individual. Being the surrogate marker of active aging, it would help us to understand the goal and future aspiration of older adults. As reported previously, life satisfaction is likely to decline with increasing age due to chronic diseases, functional inability, restriction of social contacts and involvements, decline in economic resources, and negative health perception.[39]

ICT-BRIEF would help not only in assessing the comprehensive health status of older adults but also in sensitizing community living elderly at the doorstep. This tool can be applied in multiple time frames on a single individual to determine the health trajectory throughout life course.

To apply in Indian settings, available tool such as EASYCare pose certain limitations as mentioned in introduction and the Brief Assessment Tool developed by Senn and Monod [40] focused on items related to geriatric syndrome. To the best of our knowledge, this is one of the first attempts at the national level to develop a comprehensive tool to assess domain-wise health care needs of older adults at doorstep.

Strengths and limitations of the study

The strengths of this study are (a) ICT-BRIEF is a comprehensive tool that covers all the domains to assess the health status of older adults in a holistic manner and (b) adoption of Likert scale provides freedom of a graded response rather than dichotomous response. Limitation of this study was that the findings of this cross-sectional study need to be validated by follow-up analysis to create risk score.


   Conclusion Top


ICT-BRIEF is a simple socioculturally appropriate, easy-to-use, self- or caregiver-assisted tool, created with psychometric assessment for older Indians in a diverse group of population, and takes only 15–20 min to complete. It would of great help in improving the health literacy and health-seeking behavior of older adults, thereby preventing frequent hospitalization and related cost. In addition, ICT-BRIEF may be used as an initial screening tool to assess the health status of older Indians in a community, thereby helping the individuals and their family members to prioritize care plan. The obvious next step would involve validation and creation of health risk score using ICT-BRIEF with a potential to upscale in a larger cohort.

Acknowledgment

The research group acknowledges, with thanks, the support rendered by the study participants, all the faculty and staff of the Department of Geriatric Medicine, Prof. Nand Kumar, Department of Psychiatry, Dr. Alka Mohan Chutani (Ex-Chief Dietician, Department of Dietetics) at AIIMS, New Delhi and Dr. Samiran Panda (Director, National AIDS Research Institute, Pune, Maharashtra, India). The travel expense of the volunteers was borne by Healthy Aging India.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Central Statistics Office. Ministry of Statistics and Programme Implementation. Government of India. Elderly Care. Available from: http://www.mospi.nic.in/sites/default/files/publication_reports/ElderlyinIndia_2016.pdf. [Last accessed on 2018 May 09].  Back to cited text no. 1
    
2.
UNPFA. Proceedings of the Conference on India's Elderly: Dignity, Health and Security. Available from: https://www.india.unfpa.org/sites/default/files/pub-pdf/AgeingConferenceReport.pdf. [Last accessed on 2018 May 09].  Back to cited text no. 2
    
3.
Extranet who int; 2018. Available from: https://extranet.who.int/agefriendlyworld/wp-content/uploads/2014/06/WHO-Active-Ageing-Framework.pdf. [Last accessed on 2018 May 09].  Back to cited text no. 3
    
4.
National Programme for Health Care of the Elderly. Ministry of Health and Family Welfare, GOI. Available from: https://mohfw.gov.in/major-programmes/other-national-health-programmes/national-programme-health-care-elderlynphce. [Last accessed on 2018 May 09].  Back to cited text no. 4
    
5.
Kumar T, Pal P, Kaur P. Health seeking behaviour and health awareness among rural and urban adolescents in Dehradun district, Uttarakhand, India. Int J Adolesc Med Health 2017;29. pii:/j/ijamh. 2017.29.issue-2/ijamh-2015-0046/ijamh-2015-0046.xml.  Back to cited text no. 5
    
6.
Mitchell-Fearon K, Waldron N, Laws H, James K, Holder-Nevins D, Willie-Tyndale D, et al. Non-communicable diseases in an older, aging population: A developing country perspective (Jamaica). J Health Care Poor Underserved 2015;26:475-87.  Back to cited text no. 6
    
7.
Zaman MJ, Patel A, Jan S, Hillis GS, Raju PK, Neal B, et al. Socio-economic distribution of cardiovascular risk factors and knowledge in rural India. Int J Epidemiol 2012;41:1302-14.  Back to cited text no. 7
    
8.
Inouye SK, Studenski S, Tinetti ME, Kuchel GA. Geriatric syndromes: Clinical, research, and policy implications of a core geriatric concept. J Am Geriatr Soc 2007;55:780-91.  Back to cited text no. 8
    
9.
Henchoz Y, Meylan L, Goy R, Guessous I, Bula C, Demont M, et al. Domains of importance to the quality of life of older people from two Swiss regions. Age Ageing 2015;44:979-85.  Back to cited text no. 9
    
10.
CGA Toolkit Plus – Comprehensive Geriatric Assessment in Primary Care. CGA Toolkit Plus – Comprehensive Geriatric Assessment in Primary Care. Available from: https://www.cgakit.com/s-1-easy-care-standard-2010. [Last accessed on 2018 May 09].  Back to cited text no. 10
    
11.
Slaets JP. Vulnerability in the elderly: Frailty. Med Clin North Am 2006;90:593-601.  Back to cited text no. 11
    
12.
Ishii H, Shimatsu A, Okimura Y, Tanaka T, Hizuka N, Kaji H, et al. Development and validation of a new questionnaire assessing quality of life in adults with hypopituitarism: Adult hypopituitarism questionnaire (AHQ). PLoS One 2012;7:e44304.  Back to cited text no. 12
    
13.
Losbe J, Wetmore A. CDC Coffee Break: Using Likert Scales in Evaluation Survey Work. Available from: https://www.cdc.gov/dhdsp/pubs/docs/cb_february_14_2012.pdf. [Last accessed on 2018 May 09].  Back to cited text no. 13
    
14.
Rubaish AA, Wosornu L, Dwivedi SN. Item reduction in 'course evaluation survey' questionnaire: some exploratory analysis and empirical evidence. Int J Bio Eng Neuro Sci Technol 2012;2:1-11.  Back to cited text no. 14
    
15.
Fayers PM, Machin D. Quality of Life: The Assessment, Analysis and Interpretation of Patient-Reported Outcomes. 2nd ed. West Sussex: John Wiley & Sons; 2007.  Back to cited text no. 15
    
16.
Habing B. Exploratory Factor Analysis. University of South Carolina; 2003. Available from: http://www.stat.sc.edu/~habing/courses/530EFA.pdf. [Last accessed on 2018 May 09].  Back to cited text no. 16
    
17.
Comrey AL, Lee HB. A First Course in Factor Analysis. Hillsdale, NJ: L. Erlbaum Associates; 1992.  Back to cited text no. 17
    
18.
Kaiser HF. The application of electronic computers to factor analysis. Educ Psychol Meas 1960;20:141-51.  Back to cited text no. 18
    
19.
Hutcheson G, Nick S. The Multivariate Social Scientist: Introductory Statistics Using Generalized Linear Models. Thousand Oaks, CA: Sage Publication; 1999.  Back to cited text no. 19
    
20.
World Health Organization. Visual Impairment and Blindness. Fact Sheet No 282. World Health Organization; August, c2014. Available from: http://www.who.int/mediacentre/factsheets/fs282/en/. [Last accessed on 2018 May 09].  Back to cited text no. 20
    
21.
Dhital A, Pey T, Stanford MR. Visual loss and falls: A review. Eye (Lond) 2010;24:1437-46.  Back to cited text no. 21
    
22.
Lin FR, Ferrucci L. Hearing loss and falls among older adults in the United States. Arch Intern Med 2012;172:369-71.  Back to cited text no. 22
    
23.
Falls in Older Persons: Risk Factors and Patient Kiel DP. Falls in Older Persons: Risk Factors and Patient Evaluation. Available from: http://www.uptodate.com/contents/falls-in-older-persons-risk-factors-and-patient-evaluation. [Last accessed on 2018 Sep 05].  Back to cited text no. 23
    
24.
Schimmel M, Katsoulis J, Genton L, Müller F. Masticatory function and nutrition in old age. Swiss Dent J 2015;125:449-54.  Back to cited text no. 24
    
25.
Savoca MR, Arcury TA, Leng X, Chen H, Bell RA, Anderson AM, et al. Impact of denture usage patterns on dietary quality and food avoidance among older adults. J Nutr Gerontol Geriatr 2011;30:86-102.  Back to cited text no. 25
    
26.
Di Francesco V, Fantin F, Omizzolo F, Residori L, Bissoli L, Bosello O, et al. The anorexia of aging. Dig Dis 2007;25:129-37.  Back to cited text no. 26
    
27.
Singh A, Sahai D, Mathur N. A study on prevailing malnourishment among elderly population of Lucknow city. Int J Agric Food Sci Technol 2014;5:35-40.  Back to cited text no. 27
    
28.
Shivraj M, Singh VB, Meena BL, Singh K, Meena N, Sharma D, et al. Study of nutritional status in elderly in Indian population. Int J Curr Res 2014;6:10253-7.  Back to cited text no. 28
    
29.
Berardelli M, De Rango F, Morelli M, Corsonello A, Mazzei B, Mari V, et al. Urinary incontinence in the elderly and in the oldest old: Correlation with frailty and mortality. Rejuvenation Res 2013;16:206-11.  Back to cited text no. 29
    
30.
Rister R. Treating Constipation: What Works, What Doesn't. Available from: https://www.steadyhealth.com/articles/treating-constipation-what-works-what-doesnt. [Last accessed on 2018 May 09].  Back to cited text no. 30
    
31.
Kulmala J, Nykänen I, Mänty M, Hartikainen S. Association between frailty and dementia: A population-based study. Gerontology 2014;60:16-21.  Back to cited text no. 31
    
32.
Portegijs E, Rantakokko M, Viljanen A, Sipilä S, Rantanen T. Is frailty associated with life-space mobility and perceived autonomy in participation outdoors? A longitudinal study. Age Ageing 2016;45:550-3.  Back to cited text no. 32
    
33.
Soysal P, Veronese N, Thompson T, Kahl KG, Fernandes BS, Prina AM, et al. Relationship between depression and frailty in older adults: A systematic review and meta-analysis. Ageing Res Rev 2017;36:78-87.  Back to cited text no. 33
    
34.
Koh Y, Fatimah BM, Li SC. Therapy related hospital admission in patients on polypharmacy in Singapore: A pilot study. Pharm World Sci 2003;25:135-7.  Back to cited text no. 34
    
35.
Moriguti JC, Moriguti EK, Ferriolli E, de Castilho Cação J, Iucif N Jr., Marchini JS, et al. Involuntary weight loss in elderly individuals: Assessment and treatment. Sao Paulo Med J 2001;119:72-7.  Back to cited text no. 35
    
36.
Murthy SV. Weightloss – A Practical Approach. Available from: http://www.apiindia.org/pdf/progress_in_medicine_2017/mu_65.pdf. [Last accessed on 2018 May 09].  Back to cited text no. 36
    
37.
Eriksson M, Lindström B. Antonovsky's sense of coherence scale and its relation with quality of life: A systematic review. J Epidemiol Community Health 2007;61:938-44.  Back to cited text no. 37
    
38.
Elder Abuse in India. Available from: https://www.helpageindia.org/images/df/state-elderly-india-2014.pdf. [Last accessed on 2018 May 09].  Back to cited text no. 38
    
39.
Ng ST, Tey NP, Asadullah MN. What matters for life satisfaction among the oldest-old? Evidence from China. PLoS One 2017;12:e0171799.  Back to cited text no. 39
    
40.
Senn N, Monod S. Development of a comprehensive approach for the early diagnosis of geriatric syndromes in general practice. Front Med (Lausanne) 2015;2:78.  Back to cited text no. 40
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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