Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Description
2.2.1. IHD Data
2.2.2. Population Data
2.2.3. Spatial District Data and General Hospital Data
2.3. Methodology
2.3.1. Incidence Rate and Standardized Ratio Calculation
2.3.2. Spatio-temporal Variation Analysis
2.3.3. Prediction Analysis
3. Results and Discussion
3.1. Spatio-temporal Distribution
3.2. Spatio-temporal Clusters
3.3. Spatio-temporal Change Analysis
3.4. Predicting the Results of IHD and the Corresponding Medical Burden
Districts | Prediction Value | S1 | S2 | c | p | Degree | ||
---|---|---|---|---|---|---|---|---|
2013 | 2014 | 2015 | ||||||
Baoan | 1.23 | 1.44 | 1.67 | 0.2509 | 0.0757 | 0.301714 | 1 | excellent |
Dapeng | 1.96 | 2.22 | 2.51 | 0.3704 | 0.1053 | 0.284287 | 1 | excellent |
Futian | 3.2 | 3.48 | 3.78 | 0.4803 | 0.1176 | 0.244847 | 1 | excellent |
Guangming | 1.3 | 1.5 | 1.74 | 0.2585 | 0.059 | 0.22824 | 1 | excellent |
Longgang | 1.66 | 1.95 | 2.28 | 0.3451 | 0.112 | 0.324544 | 1 | excellent |
Longhua | 0.56 | 0.6 | 0.66 | 0.0938 | 0.0373 | 0.397655 | 0.8889 | good |
Luohu | 2.65 | 3 | 3.4 | 0.4903 | 0.1273 | 0.259637 | 1 | excellent |
Nanshan | 1.79 | 1.97 | 2.18 | 0.3005 | 0.1163 | 0.387022 | 0.8889 | good |
Pingshan | 1.13 | 1.22 | 1.33 | 0.1775 | 0.0729 | 0.410704 | 0.8889 | good |
Yantian | 1.58 | 1.91 | 2.3 | 0.341 | 0.0802 | 0.235191 | 1 | excellent |
Districts | Prediction Value | S1 | S2 | c | p | Degree | ||
---|---|---|---|---|---|---|---|---|
2013 | 2014 | 2015 | ||||||
Baoan | 3,532 | 4,197 | 4,988 | 739.5386 | 157.6849 | 0.213221 | 1 | excellent |
Dapeng | 263 | 300 | 343 | 51.1903 | 12.7783 | 0.249623 | 1 | excellent |
Futian | 4,461 | 4,970 | 5,537 | 773.7296 | 164.6242 | 0.212767 | 1 | excellent |
Guangming | 670 | 807 | 972 | 144.2794 | 35.003 | 0.242606 | 1 | excellent |
Longgang | 3,498 | 4,264 | 5,196 | 762.7598 | 168.6213 | 0.221067 | 1 | excellent |
Longhua | 862 | 1,032 | 1,237 | 182.3981 | 37.1975 | 0.203936 | 1 | excellent |
Luohu | 2,540 | 2,923 | 3,364 | 492.6384 | 112.5286 | 0.22842 | 1 | excellent |
Nanshan | 2,157 | 2,477 | 2,843 | 415.7689 | 85.9678 | 0.206768 | 1 | excellent |
Pingshan | 396 | 467 | 551 | 81.8777 | 17.2176 | 0.210284 | 1 | excellent |
Yantian | 342 | 416 | 506 | 73.9185 | 16.0493 | 0.217122 | 1 | excellent |
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Wang, Y.; Du, Q.; Ren, F.; Liang, S.; Lin, D.-n.; Tian, Q.; Chen, Y.; Li, J.-j. Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China. Int. J. Environ. Res. Public Health 2014, 11, 4799-4824. https://doi.org/10.3390/ijerph110504799
Wang Y, Du Q, Ren F, Liang S, Lin D-n, Tian Q, Chen Y, Li J-j. Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China. International Journal of Environmental Research and Public Health. 2014; 11(5):4799-4824. https://doi.org/10.3390/ijerph110504799
Chicago/Turabian StyleWang, Yanxia, Qingyun Du, Fu Ren, Shi Liang, De-nan Lin, Qin Tian, Yan Chen, and Jia-jia Li. 2014. "Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China" International Journal of Environmental Research and Public Health 11, no. 5: 4799-4824. https://doi.org/10.3390/ijerph110504799