Stratified assessment for geriatric mental health using probabilistic graphical model: a cross-sectional observational study in India

BackgroundThe mental health among seniors presents a diverse set of challenges that can be attributed to a number of different causes, including social factors, economic factors, and psychological factors. Researchers are attempting to understand its complexity; however, there is a limited amount of systematic robust analysis that has been conducted. It is, therefore, critical to identify and quantify the driver characteristics or factors that are related to mental health and conduct age-specific stratified analysis in order to guide and provide tailor-made policy-level interventions. MethodsWe used "Longitudinal Ageing Study in India (LASI) wave-1 survey" data of 72250 (47% male and 53% female) carried out in April 2017 to December 2018 spanning over 35 states and union territories with socioeconomic, behavioural, psychological, and health-related indicators. We utilised a probabilistic graphical model named Bayesian Network to identify key factors of mental health variables. ResultsAgeism, social discrimination (the inferred conditional probability difference is [~]30% with 95% CI: [~]5%) and Food insecurity (>19% with a 95% CI of >3%) were found to negatively impact mental health in older adults, while connectedness with family and friends (9.34% with 95% CI: 1.41%) positively affected mental health. The sense of general dissatisfaction or discontentment with ones own life (17% with 95% of CI: [~]2.8%) is one of the factors that plays a significant role in mental health among elderly people. Additionally, multimorbidities of mental health problems in older adults, which were found to be arthritis, sleep disorders, and stroke. The incidence of multimorbidity due to mental issues were shown to be higher in older adults than younger adults, with sleep disorders being associated with mental health in older age groups. By incorporating age based stratification analysis, we also identified the specific age group when older people from India are most vulnerable to mental health issues. ConclusionThe prevalence of mental illness in senior citizens in India needs to be reduced, and one way to do this is through the development of targeted policies to combat food insecurity and social discrimination, as well as to improve communication of older people with their loved ones. In addition to this, the issue of arthritis must be tackled in a more in-depth manner given the result that it also has a severe impact on the mental health among elderly.