Relationship between living arrangements and cognitive impairment among older adults in India: Findings from LASI-2017-18

doi:10.21203/rs.3.rs-6856596/v1

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Research Article

Relationship between living arrangements and cognitive impairment among older adults in India: Findings from LASI-2017-18

https://doi.org/10.21203/rs.3.rs-6856596/v1

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Objective

As a care and support system of older adults, living arrangements are associated with the older adult’s cognitive impairment. Such family arrangements play an important role in the wellbeing of the older adults with clear distinction across living with children and spouse with that of extended kin. The present study explores the association between living arrangements and cognitive impairment among older adults in India.

Design

Cross sectional study

Setting

For this study, we used the Longitudinal Ageing Study (LASI-2017-18) data, a nationally representative survey of 31,464 older people aged 60 years and above in India. Bivariate and multivariable regression analysis were performed to fulfil the study objective.

Results

We find that older women (20.03%) were more vulnerable to cognitive impairment as likelihood reported compared to older men (7.13%) in India. After controlling the variables separately for men and women, we find that cognitive impairment, among men and women, increases when age increases. Living with spouse older men (OR: 12.38) are more likely to be affected with the cognitive impairment than women (OR: 2.44). Further, less educated, difficulties with at least one ADL/IADL older adults have higher chances of getting affected with cognitive impairment. Cognitive impairment increases with decrease wealth that is lower quintile older adults are more likely to be cognitively impaired, especially women are the most affected.

Conclusion

Living arrangements play a vital role in the well-being of the older adults in India. Older adults who living with others, living with children and lives alone have higher prevalence of cognitive function, especially women are more vulnerable. Study suggests that policy interventions by the government would benefit for the living alone older women.

India has the second-largest and fastest-growing older population in the world, and they account for 8.6 per cent of the total population in the country (Office of the Registrar General and Census Commissioner & Affairs, 2011). United Nations has projected that it will increase to 19 per cent by 2050 (United Nations, Department of Economic and Social Affairs, 2015). Such a change in Indian age structure is simultaneously associated with changes in family structure, and concerns regarding economic challenges, medical expenditure, and long-term support for the older adults (Bloom et al., 2014). Studies have shown that cognitive impairments are increasing with an associated effect on the quality of life among the older adults (Singh & Govil, 2016). Therefore, worldwide economic and social costs are also increasing to both individuals and societies (Mazzuco et al., 2017; Roystonn et al., 2020) The living arrangement is associated with cognitive impairments and as a result, the older adults those who are living alone have poor cognitive functions. Similarly, social isolation, loneliness, and low engagement in social activities are also associated with poor cognitive function (Evans et al., 2019).

The cognitive functions of older adults measure multiple aspects of intellectual functions such as memory, concentration, decision making, ability to work, and social interactions (Roystonn et al., 2020). Studies suggest that higher risk of morbidity and mortality due to the lower cognitive functions and segregation of the older adults (Obisesan & Gillum, 2009). At the same time, cognitive functions are linked with the social fabric and living arrangements in the society. For instance, a higher level of psychological and psychiatric disorders corresponded to living alone (Kaisla et al., 2006). Concomitantly, the living arrangements play a role in several aspects of morbidity of the older adults. Having a partner and living with others are associated with higher levels of social interactions (Gelder et al., 2006). Living in multigenerational households tends to improve good health among the older adults in India (Samanta et al., 2015). Living arrangement and disability were moderated by gender status have shown that older adults living in two-generation with linear-linked arrangements (households with/without spouse, with married adult children and their children) have lower risk of disability. Whereas living in Single-generation with complex-linked (with/without spouse, and any adult children and grandchildren) arrangements have a higher level of disability. Further, throughout the living arrangement the older women, those who are living in linear-linked multigenerational arrangement have a higher risk of disability than older women who are living in a single generation or other types of arrangements. On the other hand, older men who live in multigenerational or two-generation households have a higher level of disability (Schatz et al., 2018). Similar types of study from China have found that living arrangement is associated with functional disability. That is married older adult living alone or children have better functional ability whereas, unmarried, widows, divorced and never-married older adult have higher prevalence of disability (H. Wang et al., 2013).

While living arrangements influence cognitive impairment, it also confluences with other sociodemographic dimensions leading to more vulnerablitiy among certain sections of the population. For instance, in USA, higher rate of cognitive impairment have been found among widowed older women, especially with regards to Alzheimer or dementia (Gibson & Richardson, 2017). Further, exploration of the influence of gender on cognitive impairment in the context of the Chinese oldest old found that women in low socioeconomic status and rural areas have high risk of cognitive impairment due to limited availability of health resources (J. Wang et al., 2020). Similarly, changing family structure lead to rising mental health among the Turkish older population, subsequently increasing their cognitive impairment (Sahin et al., 2007). In rural Bangladesh, older women face multi-morbidity led cognitive and functional Impairments due to changing lifestyles, living conditions, behaviours, and working status (Akter et al., 2011). A study based in Japan showed that both men and women who are living without a spouse have a higher risk of basic activity of daily living disability even as living with non-spousal cohabitants led to a higher risk of basic activity of daily living disability (Saito et al., 2017). Another study based in South Korea found that living alone physically disable older adults have poor quality of life satisfaction compared to older adults living with spouses or children (Kim et al., 2015).

Much of the research has identified that living with children and others directly benefit to the older adults physical and psychological health. Because older adults receive physical, emotional and social support from their children. On the other hand, living alone or living with non-immediate kin often lead to increasing the risk of mortality and cognitive impairment (Macknight et al., 2002; Roystonn et al., 2020). In the context of India, very limited studies have looked at the association between living arrangements and cognitive impairment. While there has been some evidence that living in multigenerational household with spouse and/or children and grandchildren increased the likelihood of wellbeing and higher physical health benefit for the older adults (Samanta et al., 2015) in India. To our knowledge, limited evidence exist in assessing the impact of living arrangements on cognitive impairment among the older adults in India using nationally representative longitudinal data.

Study design and setting

The Longitudinal Ageing Study in India (LASI) is the first longitudinal nationally representative biannual panel survey of the older adult’s age 45 years and above conducted in 2017-18 by International Institute for Population Sciences (IIPS), Harvard T.H.Chan School of Public Health (HSPH) and University of Southern California (USC) in India. LASI data represents entire country (except Sikkim). The LASI Wave 1 was financially supported by the National Institute on Ageing (NIA/NIH), USA, United Nations Population Fund (UNFPA), India, and Ministry of Health and Family Welfare (MoHFW), Government of India. The technical support provided by International Technical Advisor Committee and ethical guidelines were approved by the Indian Council of Medical Research (ICMR). The detailed explanations of the sampling technique are available in the LASI Wave-1 report. The LASI data contains older adult’s related information of 72,250 respondents from the 42,949 households based on multistage stratified area probability cluster sampling design. A total of 31,464 older adult aged 60 and above, who lived more than 6 months in sample households in the last year, are included for the analysis in this study.

Dependent variable

To analyse the impact of cognitive impairment among older adults, this study considered cognitive impairment (whether physical or mental impairment or both) as an outcome variable. The outcome variable is dichotomous (0, 1), i.e. if older person has cognitive impairment = 1, otherwise = 0.

Explanatory variables

The explanatory variables used in this analysis are categorical variables. They are as follows. Age is a category variable which are grouped into three such as 60–69, 70–79, 80 + years. While sex is a dummy variable which has two category male and female, whereas marital status are coded into two category such as currently in union (i.e. currently married) and not in union (i.e. either widowed or divorced or separated or never married). Education is another important variable included in the analysis which has three categories such as no-education/primary, secondary, and higher. The variable Working status is categorised into four such as never worked, not working, working, and retired. Whereas self-rated health variable is coded into two categories as good (including excellent, very good, and good) and poor (including fair and poor). The variable Activity of Daily Living and Instrumental Activity of Daily Living consists of a series of activities such as dressing, walking, bathing, eating, getting in or out of bed, toilet, preparing a meal, shopping, telephone, medication, workaround, managing money and getting around. For the analysis, these activities are grouped into two as high ADL/IADL (represents no difficulty in ADL/IADL) and low ADL/IADL (represents difficulty with at least one ADL/IADL). While wealth quantile variable is coded into five categories such as poorest, poorer, middle, richest, and richest. The variable religion of the older person consists of three groups such as Hindu, Muslim, and others. Similarly, the social group category consists of three dummy variables as Schedule Caste/Schedule Tribe (SC/ST), Other Backward Caste (OBC), and others. The dummy variable respondent’s place of residence consists of rural and urban categories.

Statistical analysis

This study used both descriptive statistics as well as econometric methods. Descriptive analysis is used to assess the frequency and percentage distribution of the elderly by various background characteristics of the elderly population. Differences in cognitive impairment across socioeconomic groups is analysed using bivariate estimation. The relationship between living arrangements and cognitive impairment is measured using logistic regression with separate models for males and females. A multivariable logistic regression model with adjusted odds ratio is used to control the predictor variables associated with outcome variables in our study. The results are reported at 95 per cent confidence intervals (CIs) and p-values considered for the statistically significant results are p < 0.05, p < 0.01, p < 0.001.

The socioeconomic and demographic characteristics of the study participants are presented in Table 1. A proportion of 5.68 per cent of older adults lived alone, among them 2.52 per cent are men and 8.53 per cent are women. The older persons living with their spouse and children were around 41 per cent and their corresponding figure for men and women were 54 per cent and 28 per cent, respectively. A proportion of 11.2 per cent of respondents were aged 80 + years. The proportion of older men who were currently in union is nearly double (81 per cent) in comparison to older women (44 per cent). Around 56 per cent of women and only 19 per cent of men were not in marital union. In case of education level, more women (86 per cent) compared to men (61 per cent) had no education. A proportion of 74 per cent of older adults had no education/primary or had primary level of education and only 8 per cent had reported higher education.

Table 1
Socio-economic profile of the study participants
Variable group	Variables	Total (N = 31,464)		Male (N = 14,931)		Female (N = 16,533)
Variable group	Variables	%	N	%	N	%	N
Living arrangements	Living alone	5.68	1,787	2.52	380	8.53	1,397
	Living with spouse	20.33	6,397	26.03	3929	15.19	2,485
	Living with spouse and children	40.62	12,779	54.39	8211	28.18	4,612
	Living with children	27.64	8,696	13.21	1994	40.67	6,656
	Living with others	5.74	1,805	3.86	583	7.43	1,216
Age	60–69 years	58.51	18,410	57.82	9,678	59.13	9,678
	70–79 years	30.20	9,501	31.14	4,803	29.35	4,803
	80 + years	11.29	3,553	11.04	1,886	11.52	1,886
Marital status	Currently in union	61.63	19,391	81.09	12,242	44.06	7,211
Marital status	Not in union	38.37	12,073	18.91	2,856	55.94	9,155
Education	No/primary	74.02	23,289	60.95	9,202	85.82	14,046
	Secondary	18.24	5,741	26.22	3,958	11.04	1,808
	Higher	7.74	2,434	12.83	1,937	3.13	513
Work status	Never worked	26.43	8,315	3.83	578	46.84	7665
	Not working	36.45	11,470	40.88	6,173	32.45	5,311
	Working	29.87	9,397	42.05	6,348	18.87	3,088
	Retired	7.25	2,282	13.24	1,999	1.84	302
SRH*	Good	75.79	23,341	77.75	11,490	74.03	11,860
SRH*	Poor	24.21	7,457	22.25	3,288	25.97	4,160
ADL*	High	76.23	23,887	79.13	11,881	73.64	12,019
ADL*	Low	23.77	7,448	20.87	3,133	26.36	4,303
IADL*	High	51.64	16,162	61.16	9,175	43.14	7,029
IADL*	Low	48.36	15,133	38.84	5,827	56.86	9,264
MPCE quintile	Poorest	21.70	6,829	20.83	3,145	22.49	3,681
	Poorer	21.71	6,831	21.32	3,219	22.06	3,611
	Middle	20.95	6,590	21.60	3,262	20.35	3,331
	Richer	19.19	6,038	19.22	2,902	19.16	3,136
	Richest	16.45	5,176	17.02	2,570	15.93	2,607
Religion	Hindu	82.20	25,871	82.04	12,386	82.39	13,484
	Muslim	11.30	3,548	11.72	1,769	10.88	1,781
	Others	6.50	2,045	6.25	943	6.73	1,101
Caste	SC/ST	27.10	8,505	26.50	4,001	27.50	4,501
	OBC	45.20	14,231	45.86	6,925	44.66	7,308
	Others	27.70	8,728	27.63	4,172	27.84	4,556
Place of residence	Urban	29.45	22,196	27.95	4,219	30.82	5,044
Place of residence	Rural	70.55	9,268	72.05	10,879	69.18	11,322
*Sample size may differ due to missing cases; MPCE: Monthly per capita consumption expenditure; ADL: Activities of daily living; IADL: Instrumental activities of daily living

The prevalence estimates of cognitive impairment among older adults are presented in Table 2. Cognitive impairment was higher among older adults who were living with children, living with others, and living alone, whereas it was lowest among those who lived with spouse or lived with spouse and children. The prevalence of cognitive impairment was higher among women (20.03 per cent) than men (7.14 per cent). Further, the prevalence was higher in those women who lived with others (28.2 per cent) than those who lived with others only (10.6 per cent). Similarly, older women who lived with children (23.8 per cent), lived alone (22.8 per cent), lived with spouse (17.3), lived with spouse and children (14.2) were having higher cognitive impairments.

Table 2
Bivariate estimates for cognitive impairment by background characteristics
Variable group	Variables	Total	Male	Female	p-value
Variable group	Variables	%	%	%	p-value
Living arrangements	Living alone	19.07	5.7	22.83	0.001
	Living with spouse	11.92	8.35	17.28
	Living with spouse and children	8.67	5.62	14.18
	Living with children	20.59	10.74	23.78
	Living with others	21.93	10.57	28.24
Sex	Male	7.14			0.001
Sex	Female	20.03			0.001
Age	60–69 years	10.03	5.15	14.61	0.001
	70–79 years	16.77	8.33	25.43
	80 + years	27.76	15.67	40.87
Marital status	Currently in union	9.68	6.42	15.23	0.001
Marital status	Not in union	20.77	10.34	24.29	0.001
Education	No/primary education	18.79	11.41	23.9	0.001
	Secondary	1.05	1.25	0.65
	Higher	0.42	0.41	0.43
Work status	Never worked	16.4	8.64	16.99	0.001
	Not working	17.6	9.78	27.25
	Working	9.98	6.46	17.53
	Retired	2.24	1.59	6.76
SRH	Good	12.2	6.38	18.11	0.001
SRH	Poor	18.62	9.96	26.08	0.001
ADL	High	11.24	5.99	16.73	0.001
ADL	Low	22.32	11.99	30.26	0.001
IADL	High	8.43	4.7	13.56	0.001
IADL	Low	19.88	11.4	25.38	0.001
MPCE quintile	Poorest	18.55	9.81	26.56	0.001
	Poorer	15.75	8.53	22.74
	Middle	12.46	5.97	18.97
	Richer	10.88	6.06	15.66
	Richest	9.81	5.05	14.66
Religion	Hindu	13.37	6.89	19.66	0.107
	Muslim	14.62	7.53	22.09
	Others	15.72	9.61	21.4
Caste	SC/ST	19.74	11.53	27.73	0.001
	OBC	12.03	5.85	18.12
	Others	10.8	5.24	16.17
Place of residence	Urban	6.69	2.4	10.3
Place of residence	Rural	16.67	8.97	24.7
	Total	13.66
%: Per cent; ADL: Activities of daily living; IADL: Instrumental activities of daily living; MPCE: Monthly per capita consumption expenditure

The multivariable logistic regression estimates are provided in Table 3. The general the respondents living with spouse (OR 3.11), living with spouse and children (OR 2.35), living with children (OR 1.22), and living with others (OR 1.27) were less likely to have cognitive impairment than respondents living alone. The risk of cognitive impairment was three times more likely among older men living with spouse only (OR 12.38) compared to their living alone counterparts. Higher odds of cognitive impairment were observed among older men who lived with spouse and children (OR 9.049). On the other hand, older adults living with children and living with others had higher odds of cognitive impairment compared to their living alone counterparts. Whereas, older women had higher odds of cognitive impairment (OR 2.368) compared to men.

Table 3
Logistic regression estimates of cognitive impairment (AOR) by socioeconomic and health characteristics
Variable group	Variables	Total	Male	Female
Variable group	Variables	AOR (95% CI)	AOR (95% CI)	AOR (95% CI)
Living arrangements	Living alone (Ref.)
	Living with spouse	3.114*** (1.425–6.803)	12.38*** (2.281–67.21)	2.444** (1.015–5.887)
	Living with spouse and children	2.349** (1.083–5.097)	9.049** (1.679–48.78)	1.856 (0.774–4.452)
	Living with children	1.224* (0.965–1.554)	1.978** (1.014–3.856)	1.155 (0.891–1.498)
	Living with others	1.271 (0.939–1.721)	1.824 (0.805–4.136)	1.246 (0.894–1.737)
Sex	Male (Ref.)
Sex	Female	2.368*** (2.019–2.778)	-	-
Age	60–69 (Ref.)
	70–79	1.554*** (1.321–1.828)	1.373** (1.019–1.851)	1.611*** (1.334–1.946)
	80+	2.537*** (2.074–3.103)	2.200*** (1.579–3.067)	2.765*** (2.145–3.565)
Marital status	Currently in union (Ref.)
Marital status	Not in union	2.837*** (1.357–5.931)	6.535** (1.416–30.15)	2.384** (1.038–5.478)
Education	No/primary (Ref.)
	Secondary	0.0948*** (0.0651–0.138)	0.149*** (0.0970–0.229)	0.0364*** (0.0180–0.0736)
	Higher	0.0627*** (0.0261–0.151)	0.0773*** (0.0277–0.216)	0.0371*** (0.00858–0.161)
Work status	Never worked (Ref.)
	Not working	1.176* (0.991–1.395)	0.919 (0.499–1.694)	1.229** (1.022–1.478)
	Working	0.965 (0.799–1.165)	0.864 (0.458–1.632)	0.886 (0.719–1.091)
	Retired	0.615* (0.377–1.003)	0.440** (0.198–0.975)	0.740 (0.294–1.866)
SRH	Good (Ref.)
SRH	Poor	1.129* (0.979–1.302)	1.167 (0.902–1.509)	1.108 (0.934–1.315)
ADL	High (Ref.)
ADL	Low	1.450*** (1.226–1.714)	1.371** (1.001–1.877)	1.473*** (1.209–1.796)
IADL	High (Ref.)
IADL	Low	1.441*** (1.259–1.650)	1.524*** (1.164–1.997)	1.422*** (1.220–1.658)
MPCE	Poorest (Ref.)
	Poor	0.908 (0.761–1.084)	0.931 (0.674–1.286)	0.903 (0.731–1.116)
	Middle	0.709*** (0.594–0.846)	0.721* (0.517–1.005)	0.702*** (0.568–0.867)
	Rich	0.645*** (0.531–0.784)	0.718* (0.492–1.048)	0.617*** (0.495–0.769)
	Richest	0.667*** (0.509–0.875)	0.763 (0.494–1.179)	0.635*** (0.454–0.887)
Religion	Hindu (Ref.)
	Muslim	1.277** (1.020–1.598)	1.161 (0.689–1.958)	1.318** (1.057–1.642)
	Others	1.135 (0.918–1.402)	1.154 (0.765–1.741)	1.131 (0.886–1.444)
Caste	SC/ST (Ref.)
	OBC	0.630*** (0.542–0.732)	0.551*** (0.420–0.722)	0.666*** (0.557–0.797)
	Others	0.726*** (0.611–0.863)	0.771 (0.547–1.088)	0.714*** (0.587–0.868)
Place of residence	Urban (Ref.)
Place of residence	Rural	1.982*** (1.613–2.436)	2.047*** (1.384–3.027)	1.944*** (1.530–2.470)
if p < 0.05, if p < 0.01, **if p < 0.001; AOR: Adjusted Odds Ratio; CI: Confidence Interval; ADL: Activities of daily living; IADL: Instrumental activities of daily living; MPCE: Monthly per capita consumption expenditure

Studies suggest that cognitive impairment is rising in India compared to other developing countries. Some studies report that cognitive impairment affects the quality of life of the elderly in India (Singh & Govil, 2016). Globally, studies have found that living alone is associated with the decline of cognitive functions due to older adult’s loneliness, social isolation, and less engagement in social activities (Evans et al., 2019). Whereas, social interaction and active participation in work reduce the risk of cognitive impairment of the older adults (Chanda, Srei, 2019). The factors that might influence cognitive functions among the older adults are socio-demographic characteristics such as age, occupation, living arrangement, and living in urban areas (Tripathi & Tiwari, 2013). In this context, using the nationally representative LASI survey, this study analysed the relationship between living arrangement and cognitive impairment among older adults in India.

Our study finds that living arrangements have a significant relationship with cognitive impairments. Living alone, living with children and living with others were found higher prevalence of cognitive impairment. In contrast, living with spouse and living with spouse and children were found lower risk of cognitive impairment. Even this association remain strong in multivariate regression for living with spouse. Our result supported by the others study have shown that the community-dwelling older adults in Singapore who living with spouse, children and others relatives have lower risk of cognitive impairment (Roystonn et al., 2020). In contrast, when a person living alone with cognitive impairment have the higher chances of get injury and health related symptoms (Gibson & Richardson, 2017).

The study also demonstrates that cognitive impairment is deteriorated by socio-demographic and health variables in India. Our result is corroborated with previous study found that living with children and with spouse older adults was more beneficial for good cognitive ability (Mazzuco et al., 2017). Further, we examined the role of living arrangements across gender and the result shows a greater risk of cognitive impairment among older women. The higher prevalence and likelihood of cognitive impairment were found among older woman, living with other, living alone, and living with children alone. But, when controlling the socio-demographic variables in multivariate analysis, we found that living with spouse and living with spouse and children older men has the higher risk of cognitive impairment than older women. This possible explanation is that living with a spouse was less beneficial for the older women because women were most of the time busy in cooking which is a sex-appropriate role for females (Koyano et al., 1988).

Our study also found that marital status is highly correlated with cognitive impairment. Respondents who are not in union (widowed, divorced, and separated) are affects more by cognitive impairment, especially women are the most vulnerable group. The present study, in line with previous study in old age marital status is associated with cognitive (Gelder et al., 2006). Being currently in the union leads to a good cognitive function in the older adults later life because not in the union have a less emotional bond, less feeling of support, and poor relationship (Evans et al., 2019; Holmen, 2000). However, wealth quintile, health, social groups, and place of residence were associated with cognitive impairment in our study which correlates with a study from China (Zhou et al., 2016). Our result finds that cognitive impairment is associated with increasing wealth with more prevalence in males. Interestingly, several health factors such as poor health, ADL, and IADL dependency associated with cognitive impairment, might be the greater contribution of cognitive impairment and more prevalence to females (J. Wang et al., 2020).

Additionally, a higher prevalence of cognitive impairment was varying culture, ethnicity, and socio-economic context (Chen & Zissimopoulos, 2018). Our result observed the high cognitive impairment differences between religious groups, caste groups, and rural and urban areas. Nevertheless, this study has limitations; we did not consider the communication from non-coresidence children to older people because the sample size is very small. In addition, our analysis is based on the national level cross-sectional perspective, but cognitive impairment may be differ by living arrangement across states.

The study finds that living arrangements played an important role in reducing the risk of cognitive impairment for older adults. We also find that older adults with lower socioeconomic status such as lower wealth quintile, less educated, difficulty with at least one ADL/IADL, poor self-rated health, female and currently not in union and growing of aged are more vulnerable to cognitive impairment. Therefore, cognitive impairment is an increasing public health threat for India. We suggest that the researchers and policymaker should take strategies through socio-economic pathways to reduce the cognitive impairment among the older person living in India, particularly among those who do not have familial support.

Funding

The authors have not declared grant for this research from any funding agency in the public, commercial or not-for-profit section.

Patient and Public involvement

No patient involved

Ethics approval statement

The Indian Council of Medical Research (ICMR) extended the necessary guidelines and ethics approval for undertaking the LASI survey.

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Relationship between living arrangements and cognitive impairment among older adults in India: Findings from LASI-2017-18

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