Associations of serial negative income shock and all-cause mortality: a longitudinal study in China

Abstract

Introduction: With a precarious economic outlook and increasing income volatility in current times, understanding the association between negative income shock and health is crucial. However, few studies have examined such associations in developing countries. Using data from China, this study aimed to examine associations of both serial absolute income drops and relative income trajectory and mortality.

Methods: We included 4757 participants from the China Health and Nutrition Survey, a large prospective cohort study. Data between 1989 and 1997 were used to define income drops and relative income trajectories. We defined income drop as a decrease of ≥50% between two consecutive interviews and defined relative income trajectory using a latent class model. All-cause mortality between 2000 and 2015 was ascertained by participants' family members.

Results: A total of 2066 (43.43%) experienced 1 income drop and 477 (10.03%) experienced ≥2 income drops. A total of 535 deaths occurred (incidence rate 8.88 per 1000 person-years). Income drops were associated with a greater risk of mortality after adjusting for baseline income, comorbidities, sociodemographic and behavioural factors (HR 1.42 (95% CI 1.04 to 1.93) for ≥2 income drops vs no income drop). The downshift in relative income was also associated with increased mortality risk (HR 3.61 (95% CI 1.45 to 8.96) for always low; HR 3.36 (95% CI 1.36 to 8.32) for decreasing; HR 2.92 (95% CI 1.14 to 7.51) for increasing vs always high relative income). The associations between income drops and mortality were observed only among individuals with low wealth and low household income.

Conclusion: In a large sample of the Chinese population with repeated income measurement and over 14 years of follow-up, both serial absolute income drops and a downward relative income trajectory were associated with higher risks of mortality in China. Priority should be given to policies aimed at enhancing resilience against serial income shocks and financial burdens.

Keywords: education, medical; public health; sociodemographic factors.

Figure 1. Kaplan-Meier curves for all-cause mortality by the number of income drops (A) and by relative income trajectory groups (B).

Figure 2. Subgroup analysis of income drops and all-cause mortality. Model adjusted for 1989 age, gender, ethnicity, hukou status, completion of middle school education, health insurance status, occupation, logarithm of 1997 income, smoking status, alcohol consumption, physical activity, overweight status, reported history of myocardial infarction, stroke, diabetes and hypertension.