Spatial Analysis of the Distribution, Risk Factors and Access to Medical Resources of Patients with Hepatitis B in Shenzhen, China
Abstract
:1. Introduction
2. Data and Methods
2.1. Study Area
2.2. Study Data
- Basic geographic data: Administrative data for the division of Shenzhen were obtained from the Urban Planning, Land and Resources Commission of the Shenzhen Municipality [9].
- Demographic data: These data, for all 57 different sub-district administrative regions, were obtained from the 6th national population census [28].
- Hepatitis B case data: Data from the Shenzhen Centre for Health Information (SCHI), an institute directly administered by the Health, Population and Family Planning Commission of Shenzhen Municipality, were obtained from hospitalized patients’ medical records including the patients’ home addresses, ages, sexes, etc. in 2010.
- Medical facility data: These data were also obtained from the Shenzhen Centre for Health Information with addresses and service levels for most hospitals.
- Service facility data: Certain service facilities may promote hepatitis B infection. Address data were obtained by searching electronic maps on the Internet.
2.3. Study Methods
2.3.1. Spatial Interpolation
2.3.2. Correlation Analysis of Spatial Risk Factors
Correlation | Pearson Correlation Coefficient (Positive) | Pearson Correlation Coefficient (Negative) |
---|---|---|
Irrelevant | 0 to 0.09 | −0.09 to 0 |
Weak correlation | 0.1 to 0.3 | −0.3 to −0.1 |
Medium correlation | 0.3 to 0.5 | −0.5 to −0.3 |
Strong correlation | 0.5 to 1.0 | −1.0 to −0.5 |
2.3.3. Analysis of Spatial Access
- (a)
- The search radius value can be set by the service level and capacity of each hospital. Hospitals are divided into three levels, with higher service levels, indicating a greater search radius value.
- (b)
- To set a more accurate hospital service radius, a group gradient search radius value can be set at the same hospital level. Each level has three search radius values.
- (c)
- Based on the requirements of the hospital, which mainly depend on the number of beds and the number of health technical personnel, each hospital’s service capacity can be calculated.
3. Results and Discussion
3.1. Spatial Distribution of Hepatitis B Morbidity in Shenzhen
3.1.1. Hepatitis B Data Processing
Sub-District Name | Number of Cases | Sub-District Name | Number of Cases | Sub-District Name | Number of Cases |
---|---|---|---|---|---|
Shekou (N) | 7 | Dalang | 7 | Huangbei | 21 |
Shekou (S) | 39 | Haishan | 1 | Liantang | 12 |
Zhaoshang | 17 | Shatoujiao | 17 | Dongxiao | 6 |
Nanshan | 9 | Meisha | 3 | Qingshuihe | 8 |
Shahe | 21 | Yantian | 13 | Donghu | 37 |
Nantou | 1443 | Shatou | 14 | Dapeng | 5 |
Taoyuan | 4 | Nanyuan | 22 | Nanwan | 22 |
Xili | 39 | Huaqiang North | 21 | Kuiyong | 5 |
Yuehai | 74 | Xiangmihu | 15 | Buji | 73 |
Longhua | 66 | Lianhua | 88 | Bantian | 18 |
Xixiang | 57 | Yuanling | 10 | Henggang | 19 |
Fuyong | 9 | HuaFu | 11 | Pingshan | 57 |
Shiyan | 74 | Meilin | 40 | Pinghu | 48 |
Shajin | 30 | Fubao | 7 | Longgang | 7 |
Guangming (N) | 3 | Futian | 45 | Kengzi | 5 |
Guangming (S) | 11 | Nanhu | 29 | Pingdi | 37 |
Gongming | 50 | Guiyuan | 17 | Longcheng | 12 |
Songgang | 38 | Dongmen | 13 | Nan’ao | 8 |
Minzhi | 10 | Sungang | 8 | Xin’an | 15 |
Guanlan | 39 | Cuizhu | 15 |
Sub-District Name | Morbidity (104) | Sub-District Name | Morbidity (104) | Sub-District Name | Morbidity (104) | ||
---|---|---|---|---|---|---|---|
Shekou (N) | 1.56 | Dalang | 0.29 | Huangbei | 1.81 | ||
Shekou (S) | 7.53 | Haishan | 0.33 | Liantang | 1.40 | ||
Zhaoshang | 2.05 | Shatoujiao | 3.13 | Dongxiao | 0.67 | ||
Nanshan | 0.64 | Meisha | 1.56 | Qingshuihe | 0.85 | ||
Shahe | 1.70 | Yantian | 1.59 | Donghu | 4.06 | ||
Nantou | 88.40 | Shatou | 0.65 | Dapeng | 1.12 | ||
Taoyuan | 0.36 | Nanyuan | 1.97 | Nanwan | 1.13 | ||
Xili | 2.04 | Huaqiang North | 3.49 | Kuiyong | 0.90 | ||
Yuehai | 4.49 | Xiangmihu | 1.65 | Buji | 2.01 | ||
Longhua | 1.78 | Lianhua | 5.01 | Bantian | 0.84 | ||
Xixiang | 0.99 | Yuanling | 1.16 | Henggang | 0.64 | ||
Fuyong | 0.22 | HuaFu | 1.53 | Pingshan | 2.70 | ||
Shiyan | 2.92 | Meilin | 2.32 | Pinghu | 2.07 | ||
Shajin | 0.58 | Fubao | 0.72 | Longgang | 0.37 | ||
Guangming N) | 1.36 | Futian | 1.89 | Kengzi | 0.61 | ||
Guangming (S) | 2.28 | Nanhu | 3.02 | Pingdi | 3.66 | ||
Gongming | 1.21 | Guiyuan | 1.98 | Longcheng | 0.49 | ||
Songgang | 0.96 | Dongmen | 1.43 | Nan’ao | 3.28 | ||
Minzhi | 0.39 | Sungang | 1.27 | Xin’an | 0.39 | ||
Guanlan | 0.87 | Cuizhu | 1.36 |
3.1.2. The Spatial Distribution of Hepatitis B Morbidity
3.2. Spatial Risk Factor Analysis of the Spread of Hepatitis B
3.2.1. The Types of Risk Factors
3.2.2. Data Processing of Risk Factors
3.2.3. The Calculation and Explanation of the Pearson Correlation Coefficient
Bath Centres | Beauty Salons | Massage Parlours | Pedicure Parlours |
---|---|---|---|
0.566 | 0.515 | 0.626 | 0.538 |
3.3. Analysis of Spatial Access to Medical Resources
3.3.1. The Spatial Distribution of Medical Resources
3.3.2. The Calculation of Spatial Access
Sub-District Name | Spatial Access to Hospitals at Different Search Radiuses (103) | ||
---|---|---|---|
6, 3, 1.7 km | 9, 4, 2 km | 12, 5, 2.3 km | |
Shekou (N) | 22.23 | 26.52 | 29.97 |
Shekou (S) | 0.74 | 0.74 | 0.74 |
Zhaoshang | 6.02 | 8.35 | 10.32 |
Nanshan | 4.18 | 5.60 | 6.33 |
Shahe | 2.30 | 5.64 | 9.26 |
Nantou | 13.92 | 13.92 | 13.92 |
Taoyuan | 1.49 | 2.76 | 7.24 |
Xili | 0.67 | 4.09 | 4.77 |
Yuehai | 7.04 | 8.44 | 9.93 |
Longhua | 0.26 | 0.26 | 0.62 |
Xixiang | 2.35 | 2.68 | 2.91 |
Fuyong | 4.02 | 4.02 | 4.02 |
Shiyan | 3.06 | 3.24 | 4.31 |
Shajin | 4.35 | 4.35 | 4.35 |
Guangming (N) | 3.05 | 3.05 | 3.05 |
Guangming (S) | 6.02 | 6.02 | 6.02 |
Gongming | 0.19 | 0.19 | 0.19 |
Songgang | 0.43 | 0.43 | 0.43 |
Minzhi | 0.82 | 1.48 | 2.50 |
Guanlan | 0.70 | 0.70 | 0.70 |
Dalang | 0.28 | 0.28 | 0.28 |
Haishan | 11.34 | 11.34 | 13.46 |
Shatoujiao | 5.95 | 5.95 | 9.24 |
Meisha | 3.01 | 3.01 | 8.03 |
Yantian | 1.08 | 1.08 | 1.08 |
Shatou | 4.13 | 5.82 | 7.16 |
Nanyuan | 20.63 | 24.50 | 25.40 |
Huaqiang North | 51.10 | 58.86 | 60.84 |
Xiangmihu | 7.82 | 14.52 | 19.33 |
Lianhua | 30.58 | 31.72 | 31.72 |
Yuanling | 29.13 | 35.10 | 36.31 |
HuaFu | 54.17 | 57.96 | 58.23 |
Meilin | 10.12 | 10.26 | 11.30 |
Fubao | 9.60 | 12.30 | 12.30 |
Futian | 8.31 | 10.47 | 10.47 |
Nanhu | 42.56 | 46.43 | 47.67 |
Guiyuan | 31.86 | 36.20 | 36.20 |
Dongmen | 47.61 | 49.84 | 49.84 |
Sungang | 42.51 | 46.05 | 47.65 |
Cuizhu | 154.18 | 155.82 | 156.69 |
Huangbei | 16.49 | 20.47 | 21.82 |
Liantang | 3.51 | 3.51 | 7.98 |
Dongxiao | 16.23 | 21.64 | 23.67 |
Qingshuihe | 14.37 | 15.03 | 17.70 |
Donghu | 0.20 | 2.76 | 6.57 |
Dapeng | 0.13 | 0.13 | 0.13 |
Nanwan | 1.60 | 3.22 | 4.67 |
Kuiyong | 0.62 | 0.62 | 0.62 |
Buji | 2.01 | 3.15 | 4.10 |
Bantian | 0.38 | 1.58 | 2.89 |
Henggang | 1.85 | 1.85 | 1.85 |
Pingshan | 2.67 | 2.67 | 2.67 |
Pinghu | 11.06 | 11.06 | 11.48 |
Longgang | 1.77 | 2.82 | 2.82 |
Kengzi | 2.49 | 4.64 | 4.64 |
Pingdi | 24.79 | 26.83 | 26.83 |
Longcheng | 0.60 | 0.60 | 1.11 |
Nan’ao | 0.40 | 0.40 | 0.40 |
Xin’an | 10.16 | 10.16 | 10.16 |
3.3.3. The Distribution of Spatial Access
3.3.4. Relationship between Hepatitis B Morbidity and Spatial Access
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Share and Cite
Xi, Y.; Ren, F.; Liang, S.; Zhang, J.; Lin, D.-N. Spatial Analysis of the Distribution, Risk Factors and Access to Medical Resources of Patients with Hepatitis B in Shenzhen, China. Int. J. Environ. Res. Public Health 2014, 11, 11505-11527. https://doi.org/10.3390/ijerph111111505
Xi Y, Ren F, Liang S, Zhang J, Lin D-N. Spatial Analysis of the Distribution, Risk Factors and Access to Medical Resources of Patients with Hepatitis B in Shenzhen, China. International Journal of Environmental Research and Public Health. 2014; 11(11):11505-11527. https://doi.org/10.3390/ijerph111111505
Chicago/Turabian StyleXi, Yuliang, Fu Ren, Shi Liang, Jinghua Zhang, and De-Nan Lin. 2014. "Spatial Analysis of the Distribution, Risk Factors and Access to Medical Resources of Patients with Hepatitis B in Shenzhen, China" International Journal of Environmental Research and Public Health 11, no. 11: 11505-11527. https://doi.org/10.3390/ijerph111111505