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Table 2 Risk ratios (RR) and 95 % confidence intervals (CI) for incidence of acute myocardial infarction on the first 3 days and the first week after clock shift

From: Are daylight saving time transitions associated with changes in myocardial infarction incidence? Results from the German MONICA/KORA Myocardial Infarction Registry

 

Spring transition

Autumn transition

 

3 days

1 week

3 days

1 week

Model description

RR

[95 % CIs]

RR

[95 % CIs]

RR

[95 % CIs]

RR

[95 % CIs]

Unadjusted model, whole year

1.103

[0.979;1.243]

1.110

[1.014;1.215]

0.940

[0.826;1.069]

0.996

[0.906;1.096]

Unadjusted model, reduced to months around time shifta

1.065

[0.946;1.199]

1.074

[0.980;1.178]

0.969

[0.850;1.104]

1.030

[0.934;1.136]

Main confounder model, whole yearb

1.071

[0.948;1.209]

1.081

[0.985;1.185]

0.947

[0.833;1.078]

1.004

[0.913;1.105]

Main confounder model, reduced to months around time shifta,b

1.080

[0.954;1.222]

1.069

[0.973;1.174]

0.984

[0.862;1.124]

1.038

[0.94;1.145]

Optimized confounder model for months around time shiftc

1.102

[0.972;1.250]

1.077

[0.981;1.182]

0.981

[0.858;1.121]

1.025

[0.928;1.133]

S1: Year as categorical variable instead of trend

1.072

[0.949;1.211]

1.082

[0.987;1.187]

0.947

[0.832;1.078]

1.004

[0.912;1.104]

S2: Trend as p-spline

1.070

[0.948;1.209]

1.08

[0.985;1.185]

0.947

[0.832;1.078]

1.004

[0.913;1.105]

S3: Trend and meteorology as p-spline

1.070

[0.947;1.209]

1.079

[0.984;1.184]

0.946

[0.831;1.076]

1.003

[0.912;1.103]

S4a: Trend and meteorology as p-spline, indicators for month and holiday

1.071

[0.943;1.216]

1.071

[0.972;1.181]

0.969

[0.849;1.106]

1.029

[0.931;1.136]

S4b: Trend and meteorology as p-spline, indicators for month and holiday, reduced to months around time shifta

1.097

[0.966;1.246]

1.072

[0.975;1.18]

0.968

[0.847;1.108]

1.019

[0.921;1.127]

  1. aMarch and April for spring transition and September to November for autumn transition
  2. bModel adjusted for time trend and previous two day mean relative humidity as regression splines with four and two degrees of freedom, respectively, previous two day mean temperature as a linear term and day of the week as categorical variables
  3. cSpring model adjusted for time trend and same day mean relative humidity as regression splines with six and three degrees of freedom, same day mean temperature as a linear term, and month and weekday as categorical variables. Autumn model adjusted for time trend and same day mean temperature as linear terms, same day mean relative humidity as regression spline with three degrees of freedom, and month and weekday as categorical variables