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Beyond National Averages: Spatial and Temporal Patterns in Type 2 Diabetes Dynamics in Romania-A 10-Year Time Series
Cristina Gena Dascalu1, Diana Tatarciuc2, Magda Ecaterina Antohe3
1Department of Medical Informatics and Biostatistics, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 16 Universității Street, 700115 Iasi, Romania.
Clinics and Practice
|July 27, 2026
Summary
Type 2 diabetes prevalence in Romania shows cyclical patterns within counties and distinct regional synchronization dynamics over a decade. Time series analysis reveals varied epidemiological trends across regions, aiding public health planning.
Area of Science:
- Epidemiology
- Public Health
- Time Series Analysis
Background:
- Analyzes the 10-year temporal and spatial evolution of type 2 diabetes prevalence in Romanian counties (2012-2021).
- Utilizes time series autocorrelation and cross-correlation coefficients to understand disease dynamics.
Purpose of the Study:
- To investigate the temporal and spatial patterns of type 2 diabetes prevalence across Romanian counties.
- To identify epidemiological patterns and regional synchronization using time series analysis.
Main Methods:
- Calculated within-county autocorrelation coefficients to identify internal temporal dependencies.
- Calculated cross-correlation coefficients across administrative regions to reveal epidemiological patterns.
Main Results:
- Most county prevalence rates exhibit autoregressive series with significant positive correlations at lag 1, indicating cyclical fluctuations.
- Cross-correlation analysis identified three regional patterns: highly synchronized (North-East, West), mixed synchronization with lags (South-East, South), and synchronized cores with isolated counties (Center, South-West, North-West).
- Specific counties like Cluj, Alba, Mehedinți, and Ialomița displayed atypical dynamics.
Conclusions:
- Time series analysis is valuable for understanding the specificities of diabetes prevalence data.
- Findings support the practical application of these methods for customizing public health interventions.
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