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Table 2 Demographic and exposure factors of the hot spot (cluster) of diffuse gastric cancer cases

From: Geospatial analyses identify regional hot spots of diffuse gastric cancer in rural Central America

Characteristics Cluster, Diffuse Cluster, Intestinal Non-cluster, Diffuse Non-cluster, Intestinal
Geospatial methodsa, P-values
• Getis Ord Gi
• SaTScan
P < 0.0015,99%CI
P < 0.006
Referent Referent Referent
Cases (N) 52 32 139 155
Histology, signet ring 75% na 82% na
Age, mean (SD) 60.2 (16.5) 69.7 (9.9) 61.3 (14) 63 (13.1)
Age IQR 46–73 62–76 52–72 53–73
Age IQR 0–25% 21–46 53–62 23–52 30–53
P-values Referent p = 0.002 p = 0.61 p = 0.034
Gender
 Female N (%) 15 (28.9) 11 (34.4) 50 (36.0) 55 (35.5)
 Male N (%) 37 (71.1) 21 (65.6) 89 (64.0) 100 (64.5)
  P-values Referent p = 0.59 p = 0.36 p = 0.38
Family historya(N) 51 28 136 151
 Yes (%) 2 (3.9) 3 (10.7) 7 (5.2) 14 (9.3)
 No (%) 49 (96.1) 25 (89.3) 129 (94.9) 137 (90.7)
  P-values Referent p = 0.25 p = 0.73 p = 0.24
Alcohol history, ever (N) 50 31 134 148
 Yes (%) 13 (26) 10 (32.3) 25 (18.7) 31 (21)
 No (%) 37 (74) 21 (67.7) 109 (81.3) 117 (79)
 P-values Referent p = 0.54 p = 0.28 p = 0.46
Smoking history, ever (N) 50 31 134 149
 Yes (%) 13 (26) 13 (42) 34 (25.4) 37 (24.8)
 No (%) 37 (74) 18 (58) 100 (74.6) 112 (75.2)
  P-values Referent p = 0.14 p = 0.93 p = 0.87
H. pylori serodiagnosisa (N) 38 25 107 116
 Positive N (%) 31 (81.6) 20 (80) 96 (89.7) 104 (89.7)
 Negative N (%) 7 (18.4) 5 (20) 11 (10.3) 12 (10.3)
  P-values Referent p = 0.88 p = 0.20 p = 0.195
H. pylori Cag A antibodiesa (N) 38 25 107 116
 Positive (%) 33 (86.8) 22 (88) 100 (93.5) 112 (96.5)
 Negative (%) 5 (13.2) 3 (12) 7 (6.5) 4 (3.5)
  P-values Referent p = 0.89 p = 0.21 p = 0.039
  1. aTable 2 summarizes the demographic and exposure factors of the hot spot (cluster) of diffuse gastric cancer for the 378 patients for which village-level geocodes were available. In the initial study period, geocodes often limited to the municipality-level, without village-level data. H. pylori CagA multiplex serology data was available for 286 out of the 378 cases in geospatial analysis
  2. aThe cluster detection methods identify areas with high prevalence villages adjacent to other high prevalence villages. Therefore, while the prevalence is higher outside of the cluster, those patterns of higher incidence appear to be random