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 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 4  |  Issue : 4  |  Page : 142-148

Functional disability among middle-aged adults in India: Prevalence and correlates of a national study


Department of Research Administration and Development, University of Limpopo, Turfloop, South Africa; Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan

Date of Submission22-Jun-2021
Date of Decision25-Aug-2021
Date of Acceptance29-Aug-2021
Date of Web Publication29-Sep-2021

Correspondence Address:
Karl Peltzer
Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan.

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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/shb.shb_43_21

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  Abstract 


Introduction: There is a lack of research in investigating functional disability (FD) among middle-aged populations. The aim of the study was to estimate the prevalence and correlates of FD among middle-aged persons in India. Methods: The national cross-sectional sample consisted of 34,098 persons (45–59 years) from the Longitudinal Aging Study in India Wave 1 in 2017–2018. FD was assessed with difficulties of six items in activities in daily living (ADL) and seven items in instrumental activities in daily living (IADL). Results: The prevalence of 0 ADL/IADL was 70.7%, 1 ADL/IADL 10.4%, and 2 or more ADL/IADL 18.9%. The overall prevalence of ADL difficulty was 9.9% and IADL difficulty 26.5%. In the adjusted logistic regression analysis, older age (55–59 years) (adjusted relative risk ratio: 1.45, 95% confidence interval [CI] 1.23–1.70), having no education (adjusted odds ratio [AOR]: 1.79, 95% CI: 1.54–2.07), poor or fair self-rated health status (AOR: 2.06, 95% CI: 1.81–2.34), 2 or more chronic conditions (AOR: 1.67, 95% CI: 1.39–2.01), insomnia symptoms (AOR: 1.86, 95% CI: 1.57–2.20), major depressive disorder (AOR: 1.66, 95% CI: 1.39–1.99), physical pain (AOR: 1.42, 95% CI: 1.22–1.65), poor distant vision (AOR: 1.37, 95% CI: 1.17–1.62), hearing or ear problem (AOR: 1.39, 95% CI: 1.10–1.74), falls (AOR: 1.34, 95% CI: 1.15–1.55), and poor word recall (AOR: 1.60, 95% CI: 1.30–1.97) were positively associated with 2 or more ADL/IADL. In addition, male sex (AOR: 0.37, 95% CI: 0.31–0.45), and urban residence (AOR: 0.70, 95% CI: 0.58-0.84) were negatively associated with 2 or more ADL/IADL. Conclusion: Almost two in five middle-aged adults in India had 2 or more ADL/IADL and several associated factors were identified.

Keywords: Functional disability, India, middle-aged adults


How to cite this article:
Peltzer K. Functional disability among middle-aged adults in India: Prevalence and correlates of a national study. Asian J Soc Health Behav 2021;4:142-8

How to cite this URL:
Peltzer K. Functional disability among middle-aged adults in India: Prevalence and correlates of a national study. Asian J Soc Health Behav [serial online] 2021 [cited 2021 Oct 24];4:142-8. Available from: http://www.healthandbehavior.com/text.asp?2021/4/4/142/326955




  Introduction Top


As with an increasing aging population and accompanying chronic diseases as well as poor lifestyle choices, physical functional limitations, and disability may be common among middle-aged adults[1] (defined as 40–59 years).[2] “Disability and physical functioning limitations are measured in many different ways, guided by theoretical models of disablement, yet both concepts are reflective of one's functional ability to carry out tasks necessary for independent living and engagement in society.”[1],[3],[4] “Measures of functional disability (FD) typically contain items that reflect limitations in performing activities of daily living (ADLs) or instrumental activities of daily living (IADLs). Combining IADL and ADL items together on the same scale would provide enhanced range and sensitivity of the measurement.[5] In a multi-country study, the prevalence of FD was 27.3% among women and 15.0% among women aged 50–54 years,[6] and among 50–59-year-old in six low resourced countries, the prevalence of ADL difficulty was 16.8%.[7] In a study among community-dwelling middle-aged adults (55–64 years) in England, 15% had difficulty in performing basic daily activities,[8] and in a study among 50–64-year-old in the USA, the prevalence of ADL difficulty was 15%, and IADL difficulty was 17%.[9] In a recent US Health and Retirement Study (HRS) almost a quarter of participants developed ADL difficulty during middle age.[10] In a study among 553 community-dwelling men (45–59 years) from Pune, India, the prevalence of FD (8 items on daily activities) was 55.2%.[11] There is a lack of national data on the prevalence and correlates of FD among middle-aged persons in India. A better understanding of the prevalence and pattern of FD among middle-aged persons would help in improving policy and management response in India.

Various factors associated with FD among adults have been identified previously,[1],[12],[13],[14] including sociodemographic factors (age, sex, social, and economic status), poor mental health, physical chronic conditions, sensory loss, and health risk behaviors, such as smoking and physical inactivity. This study aimed to assess the prevalence and correlates of FD among middle-aged persons in India in 2017–2018.


  Methods Top


This study used cross-sectional national secondary data from the Longitudinal Ageing Study in India Wave 1, 2017–2018; “the overall individual response rate was 87%.”[15] In a household survey, “interview, physical measurement and biomarker data were collected from individuals aged 45 and above and their spouses, regardless of age.”[15] Inclusion criteria were, “A person who has lived at the place of enumeration (this house) for 6 months or more during the last year or intends to live there for at least 6 months in the next year.” and exclusion criteria were “A person who has neither lived at the place of enumeration for 6 months during the last year nor intends to live there for at least 6 months in future, and people living in institutions such as old age homes, mental asylums, ashrams, and religious homes, and incarcerated people (prison inmates).”[15] We restricted our analyses to participants aged 45–59 years. The study was approved by the “Indian Council of Medical Research Ethics Committee and written informed consent was obtained from the participants.”[15]

Measures

Dependent variable

FD was assessed with a 6-item ADL and a 7-item IADL measure (yes/no)[16],[17] (Cronbach alpha was 0.84); these measures have shown acceptable validity in the Indian population.[18]

Covariates

Social and demographic information: Education, age group (45–49, 50–54 and 55–59 years), sex (male, female), residence and marital status, health insurance and 7 items on social participation (ranging from 0 to 7, and trichotomized into 0–1 = 1, 2–3 = 2, and 4–7 = 3).[15]

Health indicators

Self-rated health status was defined as “0 = excellent, very good, good, and 1 = fair, or poor.”[15]

Chronic conditions were assessed with the question, “Has any health professional ever told you that you have…?”: (1) “ Hypertension or high blood pressure (Yes/No); (2) Diabetes or high blood sugar; (3) Cancer or malignant tumor; (4) Chronic lung disease such as asthma, chronic obstructive pulmonary disease/chronic bronchitis or other chronic lung problems; (5) Chronic heart diseases such as Coronary heart disease (heart attack or Myocardial Infarction), congestive heart failure, or other chronic heart problems; (6) Stroke; (7) Arthritis or rheumatism, Osteoporosis or other bone/joint diseases, and (8) High cholesterol (Yes/No).”[15] Responses were summed and grouped into “0, 1, or 2 or more chronic conditions.”

Insomnia symptoms were defined as frequently having any of four items, e.g., “How often do you have trouble falling asleep?” “Responses options were “never, rarely (1–2 nights per week), occasionally (3–4 nights per week), and frequently (5 or more nights per week);”[15],[19] (Cronbach α was 0.87 in this study).

Major depressive disorder (MDD) was assessed with the “HRS Composite International Diagnostic Interview short form,”[20],[21] following the “Diagnostic and Statistical Manual of Mental Disorders.”[22]

Anthropometry: “Height and weight of adults were measured using the Seca 803 digital scale.”[15] “Body Mass Index = BMI underweight was defined as <18.5 kg/m2.[23]

Physical pain was classified as “troubled by pain and required some form of medication or treatment for relief of pain.”[15]

Distant vision was assessed with the question, “How good is your eyesight for seeing things at a distance, like recognizing a person across the street (or 20 meters away), whether or not you wear glasses, contacts, or corrective lenses?”[15] Poor far vision was defined as “poor or very poor.”

Hearing problem was sourced from the question. “Have you ever been diagnosed with any hearing or ear-related problem or condition?” (Yes/No).[15]

Falls were measured with asking about, “How many times have you fallen in the last 2 years?” (Number).[15]

Current tobacco use was assessed with two questions, 1) “Do you currently smoke any tobacco products (cigarettes, bidis, cigars, hookah, cheroot, etc.)? and 2) Do you use smokeless tobacco (such as chewing tobacco, gutka, pan masala, etc.)?”[15]

Vigorous physical activity: “For vigorous activity, respondents were asked about their involvement in running or jogging, swimming, going to a health center/gym, cycling, digging with a spade or shovel, heavy lifting, chopping, farm work, fast bicycling, and cycling with loads.”[15] Answers were trichotomized: “low: 1 = hardly ever/never, moderate: 2 = less than twice a week, and high: 3 = more than once a week.”[24]

“Verbal recall was based on memory functioning of a list of 10 words and defined as 7–10 words good, 4–7 words medium and 0–3 words poor.”[25]

Statistical analysis

Statistical analyses were conducted using STATA software version 15.0 (Stata Corporation, College Station, TX, USA), taking the complex study design into account. Multinomial logistic regression was utilized to assess the predictors of 1 and 2 or more ADL/IADL (with 0 ADL/AADL as reference category). Missing values were not included in the analyses, and P < 0.05 was considered significant.


  Results Top


Participant characteristics

The overall sample included 34,098, 45–59-year-old persons from India, 44.4% were male, 85.2% married, 55.3% had some education (≥1 year), and 33.5% lived in urban areas. More than one in ten of the participants (11.1%) had insomnia symptoms, 7.3% MDD, 16.3% were underweight, 30.6% used currently tobacco, and 13.8% had multiple (2 or more) chronic conditions. The prevalence of 0 ADL/IADL was 70.7%, 1 ADL/IADL 10.4%, and 2 or more ADL/IADL 18.9%. Further sample details are shown in [Table 1].
Table 1: Sample characteristics of mid-life adults (45-59 years) in India, 2016-2017

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Components of functional disability

[Table 2] shows an overview of FD by component. Apart from the ADL item dressing and the IADL item “preparing a hot meal,” the prevalence of all other functional limitations was higher in female than in male participants [Table 2].
Table 2: Distribution of responses to functional disability items

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Associations with functional disability

In the final regression model, older age (55–59 years) (adjusted relative risk ratio: 1.45, 95% confidence interval [CI] 1.23–1.70), having no education (AOR: 1.79, 95% CI: 1.54–2.07), poor or fair self-rated health status (AOR: 2.06, 95% CI: 1.81–2.34), 2 or more chronic conditions (AOR: 1.67, 95% CI: 1.39–2.01), insomnia symptoms (AOR: 1.86, 95% CI: 1.57–2.20), MDD (AOR: 1.66, 95% CI: 1.39–1.99), physical pain (AOR: 1.42, 95% CI: 1.22–1.65), poor distant vision (AOR: 1.37, 95% CI: 1.17–1.62), hearing or ear problem (AOR: 1.39, 95% CI: 1.10–1.74), falls (AOR: 1.34, 95% CI: 1.15–1.55), and poor word recall (AOR: 1.60, 95% CI: 1.30–1.97) were positively associated with 2 or more ADL/IADL. In addition, male sex (AOR: 0.37, 95% CI: 0.31–0.45), and urban residence (AOR: 0.70, 95% CI: 0.58–0.84) were negatively associated with 2 or more ADL/IADL.

Furthermore, in unadjusted analyses, underweight and current tobacco use were positively associated with 1 and/or 2 or more ADL/IADL, and married, social participation, and physical activity were negatively associated with 1 and/or 2 or more ADL/IADL [Table 3].
Table 3: Multinominal logistic regression with functional disability

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  Discussion Top


In this national study of middle-aged adults (45–59 years) in India, the prevalence of ADL/IADL difficulty (29.3%), ADL difficulty (9.9%), and IADL difficulty (26.5%) is lower than among 553 community-dwelling men (45–59 years) from Pune, India (55.2%, 8 items functional daily activities limitation),[11] in six low- and middle-income countries (ADL difficulty: 16.8%, 50–59 years),[7] in the USA (ADL difficulty: 15%, 50–64 years),[9] and in England (ADL difficulty: 15%, 55–64 years),[8] but higher than in USA (IADL difficulty: 17%, 50–64 years).[9] Some of the differences in the prevalence of FD in the different studies may be explained by a different age range and differences in the length and response options (yes/no or Likert scale) of the ADL or IADL measurements. This survey showed that FD is a major problem in middle-aged Indians, and therefore, routine assessment of functional ability in middle age is indicated,[9] and “anti-aging measures are to be practiced during middle age which are likely to prevent disease-related disability, cognitive impairment, and depression in late life.”[26]

In agreement with former research,[27],[28] this study showed that residing in rural areas was associated with FD, which may be related to a larger proportion who had no education in rural areas (53.9%, compared to 26.4% urban areas), poor cognitive functioning (15.0% vs. 8.7%), poor distant vision (10.1% vs 5.8%), physical pain (13.5% vs. 7.5%), and insomnia symptoms (12.1% vs 9.1%). Furthermore, former studies,[6],[12],[28],[29] found an association between lower education, older age, female sex, and FD, which concurs with our results. Higher FD among women may be related to their lower educational and socioeconomic status, which, in turn, decreases cognitive functioning, reduces access to health care and good nutrition.[13]

Consistent with previous research,[8],[9],[11],[12],[13] this survey found that physical conditions, pain, and sensory deficits were associated with FD. Chronic physical conditions and sensory deficits may increasingly develop with aging and negatively impact on various components of physical functioning.[11] Pain may lead to bone deterioration, weak muscle strength, and poor physical functioning.[11] Thus, evaluation and management of physical conditions, pain, and sensory deficits should become an essential component of health care management in an effort to reduce FD.[11] In addition, we found in agreement with previous findings,[14],[30],[31],[32] that poor mental health (insomnia symptoms and MDD) increased the odds of FD. However, it is also possible that the relationship between poor mental health and FD is bidirectional, meaning that FD leads to poor mental health and vice versa.[12] Nevertheless, findings emphasize the need to address mental health problems to reduce their effects.[12] The finding that poor memory function was associated with FD calls for the early management of cognitive functioning.[12] Some previous studies that found an association between not married,[29] underweight[33], tobacco use,[34] and FD, while in this study we only a significant association between not married, underweight, current tobacco use, and ADL/IADL difficulty in unadjusted analysis. People with underweight may have a reduced muscle mass impacting negatively on their muscle strength and on ADL/IADL.[33] In addition, middle-aged participants who are not married are more likely widowed and more likely older than other participants, and older age may increase the risk of having more chronic conditions, which in turn may lead to more FD.

Limitations

A study strength was the large representative sample of middle-aged person in India, and the use of standardized measures from the HRS. The study had its limitations due to the self-report of some of the data and the cross-sectional nature of the survey. Some variables were not assessed in this study. The occupational environment of the participants was not measured in this study, which could have shown the possible impact of adverse working conditions on developing FD.


  Conclusions Top


Almost two in five middle-aged adults in India had 2 or more ADL/IADL. Factors associated with FD included women, no education, older middle-age, rural residence, physical conditions, physical pain, poor mental health, sensory deficit, and poor cognitive functioning.

Acknowledgments

“The Longitudinal Aging Study in India Project is funded by the Ministry of Health and Family Welfare, Government of India, the National Institute on Aging (R01 AG042778, R01 AG030153), and United Nations Population Fund, India.”

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Karvonen-Gutierrez CA, Strotmeyer ES. The urgent need for disability studies among midlife adults. Womens Midlife Health 2020;6:8.  Back to cited text no. 1
    
2.
Ogden CL, Carroll MD, Fryar CD, Flegal KM. Prevalence of obesity among adults and youth: United States, 2011-2014. NCHS Data Brief 2015;219:1-8.  Back to cited text no. 2
    
3.
Karvonen-Gutierrez CA. The importance of disability as a health issue for mid-life women. Womens Midlife Health 2015;1:10.  Back to cited text no. 3
    
4.
Painter P, Stewart AL, Carey S. Physical functioning: Definitions, measurement, and expectations. Adv Ren Replace Ther 1999;6:110-23.  Back to cited text no. 4
    
5.
Spector WD, Fleishman JA. Combining activities of daily living with instrumental activities of daily living to measure functional disability. J Gerontol B Psychol Sci Soc Sci 1998;53:S46-57.  Back to cited text no. 5
    
6.
Hosseinpoor AR, Williams JS, Jann B, Kowal P, Officer A, Posarac A, et al. Social determinants of sex differences in disability among older adults: A multi-country decomposition analysis using the World Health Survey. Int J Equity Health 2012;11:52.  Back to cited text no. 6
    
7.
Arokiasamy P, Uttamacharya U, Jain K, Biritwum RB, Yawson AE, Wu F, et al. The impact of multimorbidity on adult physical and mental health in low- and middle-income countries: What does the study on global ageing and adult health (SAGE) reveal? BMC Med 2015;13:178.  Back to cited text no. 7
    
8.
Gardener EA, Huppert FA, Guralnik JM, Melzer D. Middle-aged and mobility-limited: Prevalence of disability and symptom attributions in a national survey. J Gen Intern Med 2006;21:1091-6.  Back to cited text no. 8
    
9.
Bowling CB, Deng L, Sakhuja S, Morey MC, Jaeger BC, Muntner P. Prevalence of activity limitations and association with multimorbidity among US adults 50 to 64 years old. J Gen Intern Med 2019;34:2390-6.  Back to cited text no. 9
    
10.
Brown RT, Diaz-Ramirez LG, Boscardin WJ, Lee SJ, Steinman MA. Functional impairment and decline in middle age: A cohort study. Ann Intern Med 2017;167:761-8.  Back to cited text no. 10
    
11.
Nagarkar A, Gadkari R, Kulkarni S. Correlates of functional limitations in midlife: A cross-sectional study in middle-aged men (45-59 years) from Pune. J Midlife Health 2020;11:144-8.  Back to cited text no. 11
    
12.
Connolly D, Garvey J, McKee G. Factors associated with ADL/IADL disability in community dwelling older adults in the Irish longitudinal study on ageing (TILDA). Disabil Rehabil 2017;39:809-16.  Back to cited text no. 12
    
13.
Phaswana-Mafuya N, Peltzer K, Ramlagan S, Chirinda W, Kose Z. Social and health determinants of gender differences in disability amongst older adults in South Africa. Health SA Gesondheid 2013;18:9.  Back to cited text no. 13
    
14.
Whitney DG, Hurvitz EA, Peterson MD. Cardiometabolic disease, depressive symptoms, and sleep disorders in middle-aged adults with functional disabilities: NHANES 2007-2014. Disabil Rehabil 2020;42:2186-91.  Back to cited text no. 14
    
15.
International Institute for Population Sciences (IIPS), NPHCE, MoHFW, Harvard TH. Chan School of Public Health (HSPH) and the University of Southern California (USC). Longitudinal Ageing Study in India (LASI) Wave 1, 2017-18, India Report, International Institute for Population Sciences, Mumbai; 2020.  Back to cited text no. 15
    
16.
Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The Index of ADL: A standardized measure of biological and psychosocial function. JAMA 1963;185:914-9.  Back to cited text no. 16
    
17.
Lawton MP, Brody EM. Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 1969;9:179-86.  Back to cited text no. 17
    
18.
Singh S, Multani S, Verma N. Development and validation of geriatric assessment tools: A preliminary report from Indian population. JESP 2007;3:103-10.  Back to cited text no. 18
    
19.
Cho E, Chen TY. The bidirectional relationships between effort-reward imbalance and sleep problems among older workers. Sleep Health 2020;6:299-305.  Back to cited text no. 19
    
20.
Kessler RC, Andrews A, Mroczek D, Ustun B, Wittchen HU. The World Health Organization Composite International Diagnostic Interview Short-Form (CIDI-SF). Int J Methods Psychiatr Res 1998;7:171-85.  Back to cited text no. 20
    
21.
Steffick D. Documentation of Affective Functioning Measures in the Health and Retirement Study; 2000. Available from: http://hrsonline.isr.umich.edu/sitedocs/userg/dr-005.pdf. [Last accessed on 2021 Mar 03].  Back to cited text no. 21
    
22.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5). 5th ed. Washington, DC: American Psychiatric Publishing, 2013.  Back to cited text no. 22
    
23.
Wen CP, David Cheng TY, Tsai SP, Chan HT, Hsu HL, Hsu CC, et al. Are Asians at greater mortality risks for being overweight than Caucasians? Redefining obesity for Asians. Public Health Nutr 2009;12:497-506.  Back to cited text no. 23
    
24.
Lübs L, Peplies J, Drell C, Bammann K. Cross-sectional and longitudinal factors influencing physical activity of 65 to 75-year-olds: A pan European cohort study based on the survey of health, ageing and retirement in Europe (SHARE). BMC Geriatr 2018;18:94.  Back to cited text no. 24
    
25.
Kulkarni RS, Shinde RL. Depression and its associated factors in older Indians: A study based on study of Global Aging and Adult Health (SAGE)-2007. J Aging Health 2015;27:622-49.  Back to cited text no. 25
    
26.
Lalitha K. Health aspects of elderly: A global issue. JKIMSU 2012;1:1-3.  Back to cited text no. 26
    
27.
Stewart Williams J, Norström F, Ng N. Disability and ageing in China and India - decomposing the effects of gender and residence. Results from the WHO study on global AGEing and adult health (SAGE). BMC Geriatr 2017;17:197.  Back to cited text no. 27
    
28.
Ma L, Li Z, Tang Z, Sun F, Diao L, Li J, et al. Prevalence and socio-demographic characteristics of disability in older adults in China: Findings from China Comprehensive Geriatric Assessment Study. Arch Gerontol Geriatr 2017;73:199-203.  Back to cited text no. 28
    
29.
Gupta P, Mani K, Rai SK, Nongkynrih B, Gupta SK. Functional disability among elderly persons in a rural area of Haryana. Indian J Public Health 2014;58:11-6.  Back to cited text no. 29
[PUBMED]  [Full text]  
30.
Burman J, Sembiah S, Dasgupta A, Paul B, Pawar N, Roy A. Assessment of poor functional status and its predictors among the elderly in a Rural Area of West Bengal. J Midlife Health 2019;10:123-30.  Back to cited text no. 30
    
31.
Covinsky KE, Yaffe K, Lindquist K, Cherkasova E, Yelin E, Blazer DG. Depressive symptoms in middle age and the development of later-life functional limitations: The long-term effect of depressive symptoms. J Am Geriatr Soc 2010;58:551-6.  Back to cited text no. 31
    
32.
Geerlings SW, Beekman AT, Deeg DJ, Twisk JW, Van Tilburg W. The longitudinal effect of depression on functional limitations and disability in older adults: An eight-wave prospective community-based study. Psychol Med 2001;31:1361-71.  Back to cited text no. 32
    
33.
Vaish K, Patra S, Chhabra P. Functional disability among elderly: A community-based cross-sectional study. J Family Med Prim Care 2020;9:253-8.  Back to cited text no. 33
[PUBMED]  [Full text]  
34.
Medhi GK, Hazarika NC, Borah PK, Mahanta J. Health problems and disability of elderly individuals in two population groups from same geographical location. J Assoc Physicians India 2006;54:539-44.  Back to cited text no. 34
    



 
 
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