Skip to main content

Table 1 Results of the linear spline analysis on the change of hospitalization rates due to Salmonella infection before and after HACCP* by the nine Census divisions

From: Geographic variations and temporal trends of Salmonella-associated hospitalization in the U.S. elderly, 1991-2004: A time series analysis of the impact of HACCP regulation

Division Intercept 95% CI β1 95% CI β2 95% CI p-value for slope change
New England 0.27 (0.14, 0.40) -0.0009 (-0.0017, -0.0002) -0.0020 (-0.0026, -0.0013) 0.12
Middle Atlantic 0.12 (-0.02, 0.26) -0.0015 (-0.0023, -0.0008) -0.0021 (-0.0028, -0.0013) 0.46
East North Central 0.08 (-0.06, 0.22) -0.0002 (-0.0011, 0.0007) -0.0011 (-0.0018, -0.0004) 0.20
West North Central -0.04 (-0.19, 0.1) -0.0008 (-0.0017, 0.0001) -0.0004 (-0.0011, 0.0003) 0.59
South Atlantic 0.10 (-0.03, 0.23) -0.0012 (-0.0020, -0.0004) -0.0003 (-0.0009, 0.0003) 0.15
East South Central 0.15 (0.03, 0.28) -0.0017 (-0.0024, -0.001) 0.0004 (-0.0001, 0.0010) <0.001
West South Central 0.27 (0.15, 0.39) -0.0008 (-0.0015, 0) 0 (-0.0006, 0.0005) 0.21
Mountain 0.04 (-0.10, 0.19) -0.0003 (-0.0012, 0.0006) -0.0015 (-0.0022, -0.0007) 0.10
Pacific† 0.03 (-0.12, 0.18) -0.0002 (-0.0011, 0.0007) -0.0022 (-0.0030, -0.0014) 0.01
Contiguous U.S. 0.10 (-0.03, 0.24) -0.0009 (-0.0018, -0.0001) -0.0009 (-0.0015, -0.0002) 0.92
  1. Outcome: weekly hospitalization rate (cases per 1,000,000) modelled with Poisson distribution
  2. Predictors: time before HACCP (β 1), time after HACCP (β 2), controlled for annual oscillation
  3. Regression model: log [Y t ] = β 0 + β 1(t <1997) + β 2 (t ≥ 1997) + β 3sin(2πωt) + β 4 cos(2πωt) + ε t
  4. * Hazard Analysis and Critical Control Points Systems
  5. † Excluding HI & AK