Cardiovascular hospitalization dynamics in Iran's second-largest city: A spatial and temporal perspective.

Area of Science:

• Public Health
• Epidemiology
• Spatial Analysis

Background:

• Cardiovascular disease (CVD) is a major global cause of death, with a significant impact in developing nations like Iran.
• Understanding geographic and time-based patterns of CVD hospitalizations is vital for effective public health strategies.

Purpose of the Study:

• To conduct the first comprehensive spatial and temporal analysis of CVD hospitalizations in Mashhad, Iran.
• To identify high-risk areas and temporal trends to guide targeted public health interventions.

Main Methods:

• Utilized hospitalization data from 2016-2020, classifying cases by ICD-10 codes.
• Employed classical decomposition, ARIMA, and Joinpoint regression for temporal trend analysis.
• Applied spatial autocorrelation, hotspot analysis, and Flexible Spatial Scan Statistics (FSSS) for spatial cluster detection.

Main Results:

• Identified a rising trend in CVD hospitalizations, with significant increases for both males (1.69%/month) and females (1.99%/month) until November 2019.
• Revealed significant spatial autocorrelation, with central Mashhad identified as a high-risk zone.
• FSSS detected a primary cluster in the city center with a nearly 10-fold increased relative risk for CVD hospitalizations.

Conclusions:

• This study highlights critical high-risk areas for CVD hospitalizations in Mashhad, necessitating focused public health interventions.
• Addressing identified spatial disparities is essential for improving cardiovascular health outcomes and population resilience.