Data for this study was utilized from recent release of Longitudinal Ageing Study in India (LASI) wave 1 (39). LASI is a full-scale national survey of scientific investigation of the health, economic, and social determinants and consequences of population aging in India, conducted in 2017-18 (39). The LASI is a nationally representative survey over 72000 older adults age 45 and above across all states and union territories of India (39). The main objective of the survey is to study the health status and the social and economic well-being of older adults in India. LASI adopted a multistage stratified area probability cluster sampling design to arrive at the eventual units of observation: older adults age 45 and above and their spouses irrespective of age. The survey adopted a three-stage sampling design in rural areas and a four-stage sampling design in urban areas. In each state/UT, the first stage involved the selection of Primary Sampling Units (PSUs), that is, sub-districts (Tehsils/Talukas), and the second stage involved the selection of villages in rural areas and wards in urban areas in the selected PSUs. In rural areas, households were selected from selected villages in the third stage (39). However, sampling in urban areas involved an additional stage. Specifically, in the third stage, one Census Enumeration Block (CEB) was randomly selected in each in urban area (39). In the fourth stage, households were selected from this CEB. The detailed methodology, with the complete information on the survey design and data collection, was published in the survey report. The present study is conducted on the eligible respondent’s age 60 years and above. The total sample size for the present study is 31,464 older adults aged 60 years and above (Male-15,068; Female-16,366).
All methods were carried out in accordance with guidelines. We confirm that all experimental protocols were approved by institutional committee and the ethical clearance was provided by Indian Council of Medical Research (ICMR), India.
Cognitive impairment was measured through five broad domains (memory, orientation, arithmetic function, executive function, and object naming). Memory was measured using immediate word recall, delayed word recall; orientation was measured using time and place measure, arithmetic function was measured through backward counting, serial seven, and computation method; executive function was measured through paper folding and pentagon drawing method, and object naming was lastly done to measure the cognitive impairment among older adults (39). A composite score of 0-43 was computed using the domain-wise measure. The lowest 10th percentile is used as a proxy measure of poor cognitive functioning (39).
Main explanatory variable
The main explanatory variable was migration status among older adult. The variable was assessed using the question “How many years have you been living (continuously) in this area?” If the respondent responded that they were living in this area since birth than he/she was coded as 0 “Non-migrant” and otherwise 1 “Migrant”.
Other explanatory variables
Age was coded as young old (60-69 years), old-old (70-79 years), and oldest-old (80+ years). Sex was coded as male and female. Educational status was coded as no education/primary not completed, primary, secondary and higher. Working status was coded as never worked, currently working, currently not working and retired. Marital status was coded as currently married, widowed, and others. Others included divorced/separated/never married. Social participation was coded as no and yes. Respondents were said to be socially engaged if they participate in the following activities. Eat out of house (Restaurant/Hotel); Go to park/beach for relaxing/entertainment; Play cards or indoor games; Play out door games/sports/exercise/jog/yoga; Visit relatives /friends; Attend cultural performances /shows/Cinema; Attend religious functions /events such as bhajan/satsang/prayer; Attend political/community/organization group meetings; Read books/newspapers/magazines; Watch television/listen radio and Use a computer for e-mail/net surfing etc. If the respondent was involved in any of the above activity, then the respondent was defined to be socially engaged. Physical activity status was coded as frequent (every day), rare (more than once a week, once a week, one to three times in a month), and never. The question through which physical activity was assessed was “How often do you take part in sports or vigorous activities, such as running or jogging, swimming, going to a health center or gym, cycling, or digging with a spade or shovel, heavy lifting, chopping, farm work, fast bicycling, cycling with loads”? (39)
The probable major depression among the older adults with symptoms of dysphoria, calculated using the CIDI-SF (Short Form Composite International Diagnostic Interview) score of 3 or more. This scale estimates a probable psychiatric diagnosis of major depression and has been validated in field settings and widely used in population-based health surveys (39). The lowest 10th percentile is used as a proxy measure for major depression among older adults. Self-rated health was coded as good which includes excellent, very good, and good whereas poor includes fair and poor (40). Difficulty in ADL (Activities of Daily Living) was coded as no and yes. Activities of Daily Living (ADL) is a term used to refer to normal daily self-care activities (such as movement in bed, changing position from sitting to standing, feeding, bathing, dressing, grooming, personal hygiene, etc.) The ability or inability to perform ADLs is used to measure a person’s functional status, especially in the case of people with disabilities and the ones in their older ages (41). Difficulty in IADL (Instrumental Activities of Daily Living) was coded as no and yes. Activities of daily living that are not necessarily related to the fundamental functioning of a person, but they let an individual live independently in a community. These tasks are necessary for independent functioning in the community. Respondents were asked if they were having any difficulties that were expected to last more than three months, such as preparing a hot meal, shopping for groceries, making a telephone call, taking medications, doing work around the house or garden, managing money (such as paying bills and keeping track of expenses), and getting around or finding an address in unfamiliar places (41).
The monthly per capita consumption expenditure (MPCE) quintile was assessed using household consumption data (39). Sets of 11 and 29 questions on the expenditures on food and non-food items, respectively, were used to canvas the sample households (39). Food expenditure was collected based on a reference period of seven days, and non-food expenditure was collected based on reference periods of 30 days and 365 days (39). Food and non-food expenditures have been standardized to the 30-day reference period (39). The monthly per capita consumption expenditure (MPCE) is computed and used as the summary measure of consumption. The variable was then divided into five quintiles i.e., from poorest to richest (39). Religion was coded as Hindu, Muslim, Christian, and Others. Caste was recoded as Scheduled Tribe, Scheduled Caste, Other Backward Classes (OBC), and others. The Scheduled Castes include the population that is socially segregated and financially/economically weak by their low status as per Hindu caste hierarchy. The Scheduled Tribes (STs) and Scheduled Castes (SCs) are among the most disadvantaged and discriminated socio-economic groups in India (42). The OBC is the group of people who were identified as “educationally, economically and socially backward” (42). The OBC’s are considered low in the traditional caste hierarchy but are higher in status than Scheduled Castes. The “other” caste category is identified as having higher social status, mostly belong to upper caste Hindus (43). Place of residence was coded as rural and urban. The regions of India were coded as North, Central, East, Northeast, West, and South.
The study used univariate, bivariate and multivariate analysis to fulfil the aim of the objective. Descriptive analysis is used to show the sample profile of the respondents. Further, bivariate analysis was carried out to estimate the prevalence of cognitive impairment among older adults (male-female separately) by selected variables. Further, a proportion test (44) was done to see the difference between male and female older adults in the prevalence of cognitive impairment. The VIF factor was estimated to check multicollinearity and no evidence of multicollinearity was found. Logistic regression (45) was done to compare migrants and non-migrants in cognitive impairment in both the ways unadjusted and adjusted odds ratio by selected background characteristics. Adjusted odds ratios are reported in the study with the form of an adjusted odds ratio (AOR) with a 95% confidence interval (CI).