Presentation Schedule
Loneliness and Its Determinants Among Older Adults in India: Evidence from the Longitudinal Ageing Study in India (LASI) (103106)
Session Chair: Kumudinei Dissanayake
Thursday, 26 March 2026 12:10
Session: Session 2
Room: Room 707 (7F)
Presentation Type: Oral Presentation
Loneliness is an emerging public health concern among India’s ageing population, with implications for mental and physical well-being. Using data from the Longitudinal Ageing Study in India (LASI, Wave 1, 2017–18), this study examines the prevalence and correlates of loneliness among 72,250 adults aged 45 years and above across all states and union territories. Loneliness was assessed through self-reported measures of social isolation, and multivariable logistic regression was used to identify significant predictors. Findings indicate that 18% of older adults reported feeling lonely, with higher prevalence among women (20%) than men (15%). Loneliness increased with age, affecting 27% of those aged 75 years and above. It was most common among widowed individuals (32%), those living alone (41%), and those reporting depressive symptoms (46%) or multiple chronic conditions (30%). Rural residents and individuals from lower socioeconomic groups experienced significantly greater loneliness. Regression results showed that living alone (AOR = 2.8), depressive symptoms (AOR = 2.4), poor self-rated health (AOR = 1.9), and multimorbidity (AOR = 1.6) were strong predictors of loneliness. Conversely, social participation and higher education were protective factors. The findings highlight that nearly one in five older Indians experience loneliness, reflecting weakening social ties and limited mental health support. Addressing loneliness through community-based programs, intergenerational engagement, and integrated mental health care is essential to promote healthy and active ageing in India.
Authors:
Jagriti Gupta, Ahmedabad University, India
About the Presenter(s)
Dr. Jagriti Gupta, Biostatistician at Ahmedabad University, applies Bayesian and multilevel models to study fertility, data quality, and maternal health in India.
See this presentation on the full schedule – Thursday Schedule





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