Background: Comorbidities, any other coexisting diseases in patients with a particular index disease, are known to increase the mortality of a stroke. However, the association of pre-existing comorbidities with stroke risk has not been fully studied. Methods: This study included 16,246 adults from a prospective community-based cohort with a baseline survey conducted in 2013 in China. Participants were followed up with hospitalization records and the Cause of Death Registry. The association of eight pre-existing comorbidities (coronary heart disease, hyperlipidemia, hypertension, diabetes, previous stroke, chronic obstructive pulmonary disease, nephropathy, and cancer) with stroke risk was analyzed using the Cox proportional hazard model in 2020. Results: At a median follow-up of 5.5 years, a total of 449 participants (206 men and 243 women) developed a stroke. Four pre-existing comorbidities (hypertension, congenital heart disease, previous stroke, and diabetes) were independently and positively associated with the risk for all types of stroke. The adjusted hazard ratios for participants with only 1 and ≥ 2 pre-existing comorbidities compared with those without pre-existing conditions were 1.96 (95% CI: 1.44, 2.67; P < 0.001) and 2.87 (95% CI; 2.09, 3.94; P < 0.001) for total stroke, respectively. Moreover, male and female participants with a combination of increased age and a higher number of pre-existing comorbidities experienced the greatest risk of stroke. Conclusions: The number of pre-existing comorbidities was independently associated with an increased risk of stroke. There was a synergic effect between increased age and a higher number of pre-existing comorbidities on stroke occurrence. Our novel findings emphasize the importance and potential application of pre-existing comorbidities as a risk indicator in stroke prevention.
CITATION STYLE
Zhang, Y., Wang, C., Liu, D., Zhou, Z., Gu, S., & Zuo, H. (2021). Association of total pre-existing comorbidities with stroke risk: a large-scale community-based cohort study from China. BMC Public Health, 21(1). https://doi.org/10.1186/s12889-021-12002-1
Mendeley helps you to discover research relevant for your work.