The impact of chronic disease diagnoses on smoking behavior change and maintenance: Evidence from China

Abstract

Introduction Managing chronic diseases and tobacco use is a formidable challenge in low- and middle-income countries (LMICs) with limited health literacy and access to quality healthcare. This study examines the empirical evidence from China, utilizing quasi-experimental approaches to assess the causal effect of chronic disease diagnoses on smoking behavior. Methods Employing the diagnosis of chronic disease in the older cohorts of the population as a natural experiment, this study utilizes recent advancements in difference-in-difference estimation methods (CS-DID) to investigate the effect of a diagnosis on smoking behavior. Self-reported new diagnoses of conditions ascertained chronic disease diagnoses. CS-DID was run using the study sample from the 2011 to 2018 waves of the China Health and Retirement Longitudinal Study, comparing results with traditional two-way fixed effects and event-study models. Results The average treatment effect (ATT) of CS-DID is slightly greater than the effects reported using conventional difference-in-difference methods. We found that diagnoses of cancer, heart disease, and stroke reduced smoking rates by 16% (95% CI: -24 – -8), smoking intensity by 0.31 (95% CI: -0.46 – -0.15), and had lasting impacts on smoking cessation behavior (one wave after diagnosis ATT= -0.17; 95% CI: -0.34 – -0.00, two waves after diagnosis ATT= -0.17; 95% CI: -0.37–0.03). A diagnosis of a mild chronic disease, such as hypertension, diabetes, asthma, chronic lung disease, liver disease, or gastric disease, had more negligible and transient effects on smoking behavior. Conclusions Efforts to enhance smoking cessation in middle-aged and elderly patients with chronic diseases are crucial to improving health outcomes. The ‘teachable moment’ of chronic disease diagnosis should be seized to provide smoking cessation assistance to achieve the goal of healthy ageing.

Keywords

• chronic disease diagnosis
• prevention
• smoking
• heterogeneous treatment effects
• lmics