Stock market fluctuation and stroke incidence: A time series study in Eastern China

Abstract

Objective: To explore the association between daily change of Shanghai Stock Exchange (SSE) Composite Index and stroke incidence in Zhejiang, China.

Methods: Data on daily stock index change and stroke incidence during 2009-2016 were collected to form the time series. Data were analyzed using distributed lag non-linear model (DLNM) with quasi-Poisson as link function, controlling for long-term and seasonal trends, day of the week, public holiday, meteorological factors, and economic conditions.

Results: Large changes in daily stock index were associated with increased risk of stroke. Rise of stock index was significantly related to higher stroke incidence without delay. The relative risks (RRs) of stroke on the lag0 day were 1.040 (95% CI 1.011-1.071) for 100 index increase, and 1.111 (95% CI 1.000-1.235) for 200 index increase. Additionally, fall of stock index was associated with higher stroke incidence at lag of 5 and 6 days. The relative risks (RRs) of stroke for -200 index decline on the lag5 and lag6 day were 1.058 (95% CI 1.025-1.093) and 1.061 (95% CI 1.019-1.104) respectively. The association was relatively consistent across subgroups stratified by the subtype of stroke, gender, and age groups.

Conclusion: Both rise and fall of stock index were associated with an elevated occurrence of stroke.

Keywords: Delayed effect; Non-linear; Stock market; Stroke.