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