Figure 1
The spatial distribution of KD endemic areas.
Figure 2
The spatial distribution of the study population in KD endemic areas.
Figure 3
Global spatial autocorrelation analysis of CKD and LKD prevalence in China. A) CKD prevalence; B) LKD prevalence. The left side of the figure represents dispersed areas, the right side represents clustered areas, and the middle represents random areas.
Table 1
Clusters identified by local Moran’s I analysis for LKD prevalence by county in China.
| TYPE OF CLUSTERING | PROVINCE | COUNTY |
|---|---|---|
| H-H clustering | Shaanxi | Long, Baota, Zhidan, Fu, Luochuan, Yichuan, Huangling |
| Shanxi | Pu | |
| Inner Mongolia | Ningcheng | |
| Jilin | Huadian, Shulan | |
| Gansu | Kongtong, Li | |
| H-L clustering | Sichuan | Renhe, Hanyuan, Butuo |
| Yunnan | Yongshan, Lianghe | |
| Shaanxi | Qishan | |
| L-H clustering | Gansu | Qinzhou, Zhuanglang, Qingcheng, Huachi, Wudu, Cheng |
| Shanxi | Daning | |
| Shaanxi | Wangyi | |
| L-L clustering | Sichuan | Zhaojue, Yuexi |
| Chongqing | Dianjiang |
Figure 4
Clusters identified by local Moran’s I analysis for LKD prevalence by county in China. Red borders in the spatial thematic map represent KD-endemic areas.
Table 2
Clusters identified by Local Getis-Ord Gi* analysis for LKD prevalence by county in China.
| TYPE OF CLUSTERING | PROVINCE | COUNTY |
|---|---|---|
| Hot spot 99% CI | Shaanxi | Long, Zhidan, Fu, Yichuan |
| Gansu | Qinzhou, Kongtong, Zhuanglang, Huating, Qingcheng, Huachi, Heshui, Wudu, Cheng, Xihe, Li | |
| Shanxi | Ji, Daning, Pu | |
| Inner Mongolia | Ningcheng, | |
| Jilin | Huadian | |
| Hot spot 95% CI | Shaanxi | Changwu, Bin, Baota, Luochuan, Huangling |
| Gansu | Zhengning | |
| Jilin | Shulan | |
| Hot spot 90% CI | Shaanxi | Wangyi, Xunyi, Hua, Ansai, Ganquan, Huanglong |
| Jilin | Jiaohe, Panshi | |
| Inner Mongolia | Kelaqinqi |
Figure 5
Clusters identified by Local Getis-Ord Gi* analysis for LKD prevalence by county in China. Red borders in the spatial thematic map represent KD-endemic areas. Colors in the spatial thematic map represent hot spots and cold spots of spatial clustering with 90% CI, 95% CI, and 99% CI.
Figure 6
Spatial interpolation analysis of LKD prevalence in China. Red borders in the spatial thematic map represent KD-endemic areas. The blue to red colors in the spatial thematic map indicate gradual increases in LKD prevalence.
Table 3
Spatial regression analysis of LKD and CKD prevalence.
| CHARACTERISTIC | REGRESSION COEFFICIENTS | STANDARD DEVIATION | t | P VALUE |
|---|---|---|---|---|
| LKD | ||||
| Per capita disposable income | –0.0099 | 0.0023 | –4.36 | ＜0.0001 |
| CKD | ||||
| Per capita disposable income | –0.0006 | 0.0004 | –1.58 | 0.1170 |
[i] Note: LKD: R2 = 0.1205, Radj2 = 0.1085; CKD: R2 = 0.0252, Radj2 = 0.0118.