Data:
In this study, the first wave of the longitudinal study of ageing in India (LASI) was used as a data source which was conducted across all the 35 Indian states (exclude Sikkim) and union territories (UTs) in 2017-18. The study was funded by the Ministry of Health and Family Welfare (MoHFW), the Government of India, the National Institute on Aging (NIA), and the United Nations Population Fund, India (UNFPA). The nodal agencies of the survey were the International Institute for Population Sciences (IIPS), Harvard T.H. Chan School of Public Health (HSPH), and University of Southern California (USC), and several other national and international institutions.
The LASI is the latest survey that is well-positioned to assess the effect of changing policies on the behavioural outcomes of the elderly in India and considered the world’s most extensive and India’s first longitudinal study. The survey’s tools and protocols are harmonized with the Health and Retirement Study (HRS) in the United States and its sister surveys in Asia, Europe, and elsewhere.
The primary objective of the LASI is to contribute extensive scientific information on demographics, household economic status, chronic health conditions, symptom-based health status, functional health, mental health (cognition and depression), biomarkers, insurance, and healthcare utilization, family and social networks, social welfare programs, work and employment, retirement, satisfaction, and life expectancy.
The LASI survey instrument contains the Household Schedule (HH), Individual Schedule, biomarker survey, and community schedule. The HH schedule was surveyed with a selected vital informant in every household, where the individual and biomarker schedule was observed with each chosen respondent.
The LASI has applied a multistage stratified area probability cluster sampling to achieve the country’s representative sample. The survey has used a three-stage sampling design for rural areas and a four-stage sampling design for urban areas. The sampling frame has been adopted from the census of India (2011) to select sub-districts (Tehsils/Talukas) in the first stage of sampling. In the second stage, villages and wards were selected from sub-districts in rural and urban areas. The third stage involved selecting households from selected villages in rural areas, however, an additional stage was involved for urban areas. The list of census enumeration blocks (CEBs) was selected in the third stage in urban areas. To obtain the list of selected households in urban areas, mapping and listing of households have been done to reach out the final list of households from selected census enumeration blocks (CEBs).
The first wave of LASI included a sample of 72,250 individuals aged 45 years and above and their spouses, however, our study concerned 31,464 elderly aged 60 years and above, including 6,749 individuals aged 75 years above from 35 states and union territories.
Study Variables
Outcome variable
The outcome variable for this study is “depression,” which was self-reported. The question has been asked, “During the last 12 months, was there ever a time when you felt sad, blue, or depressed for two weeks or more in a row” and responses recorded in dichotomous for as “yes” and “no.” Another outcome variable for this study is ‘thinking’ or ‘perception’ about depression. The question has been asked for thinking of depression as “did you lose interest in most things?”, “did you ever feel more tired out or low in energy than is usual for you?”, “did you lose your appetite?”, During the same two-week period, did you have a lot more trouble concentrating than usual? “people sometimes feel down on themselves, and no good or worthless, during those two weeks, did you feel this way?”, “did you think a lot about death – either your own, someone else’s, or death in general – during those two weeks?” and “did you have more trouble falling asleep than you usually do during those two weeks?”. All this question has been asked in the form of either ‘yes’ or ‘no.’
Covariates
Covariates for this study considered as age (60-69 and 70 years and above), gender (male and female), marital status (currently married, never married, Divorced/Separated/Deserted/Widowhood), living arrangements (living alone, with spouse and with others), religion (Hindu, Muslim and others), education (No education, below primary, primary, secondary, and higher), place of residence (rural and urban), wealth index (poorest, poorer, middle, richer and richest), currently working (yes and no), self-rated health (poor and good), ), tobacco use (no and yes). Activity of daily diving (ADL) has been constructed using five parameters: bathing, dressing, mobility, feeding, and toileting. Similarly, instrumental activity of daily living (IADL) has created using seven parameters: preparing a hot meal (cooking and serving), shopping for groceries, making telephone calls, 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 an unfamiliar place. Further, ADL and IADL disability classified into “severe,” “moderate,” and “no disability.”
Statistical measures
Data were analyzed using STATA version 16. Bivariate analysis was used to understand the prevalence and thinking of depression among sociodemographic clusters. The prevalence of depression has presented separately for men and women for rural and urban areas, respectively. Fairly decomposition analysis has been done to measures rural-urban inequalities for depression among older men and women. Fairlie decomposition is a very simple technique used to estimate from a logit or probit model, first described by Fairlie in 1999 [21]. The decomposition results have been presented in terms of coefficient and percent contribution by a group of sociodemographic variables. The significance level is shown at 95% CI and 99% CI. The equation for fairlie decomposition can be written as:
Where NU and NR is the sample size for urban and rural respectively, and are the average probability of a binary outcome of interest for group urban and rural, F is the cumulative distribution function from the logistic distribution, distribution, and are the set of the average value of the independent variable and and are the coefficient estimates for the urban and rural respectively.