The association between polluted fuel use and self-reported insomnia symptoms among middle-aged and elderly Indian adults: a cross-sectional study based on LASI, wave 1

Abstract

BackgroundInsomnia predisposes the aging population to reduced quality of life and poor mental and physical health. Evidence of the association between polluted fuel use and insomnia symptoms is limited and is non-existent for the Indian population. Our study aimed to explore the link between polluted fuel use and insomnia symptoms in middle-aged and older (≥ 45 years) Indian populations.MethodsWe utilized data from nationally representative Longitudinal Aging Study in India (LASI) Wave 1. Participants with complete information on fuel use, insomnia symptoms, and covariates were included. Insomnia symptoms were indicated by the presence of at least one of three symptoms: difficulty in initiating sleep (DIS), difficulty in maintaining sleep (DMS), or early morning awakening (EMA), ≥ 5 times/week. Survey-weighted multivariable logistic regression analyses were conducted to evaluate the association between polluted fuel use and insomnia symptoms. We also assessed the interaction of association in subgroups of age, gender, BMI, drinking, and smoking status.ResultsSixty thousand five hundred fifteen participants met the eligibility criteria. Twenty-eight thousand two hundred thirty-six (weighted percentage 48.04%) used polluted fuel and 5461 (weighted percentage 9.90%) reported insomnia symptoms. After full adjustment, polluted fuel use was associated with insomnia symptoms (OR 1.16; 95%CI 1.08–1.24) and was linked with DIS, DMS, and EMA (OR 1.14; 95%CI 1.05–1.24, OR 1.12; 95%CI 1.03–1.22, and OR 1.15; 95%CI 1.06–1.25, respectively). No significant interactions for polluted fuel use and insomnia symptoms were observed for analyses stratified by age, sex, BMI, drinking, or smoking.ConclusionsPolluted fuel use was positively related to insomnia symptoms among middle-aged and older Indians. Suggestions are offered within this article for further studies to confirm our results, to explore underlying mechanisms, and to inform intervention strategies.