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Table 2 Comparison of Parkinson’s disease characteristics between coffee drinkers and non-coffee drinkers

From: Gender-dependent effect of coffee consumption on tremor severity in de novo Parkinson’s disease

 

Coffee drinker

(n = 204)

Non-coffee drinker

(n = 80)

p-value

Adjusted

p-value

Demographic

 Age (years)

64.57 ± 9.83

68.79 ± 8.24

0.001

 

 Sex (female:male)

84:120

53:27

<  0.001

 

 Age at symptom onset (years)

62.84 ± 10.00

67.00 ± 8.15

0.001

 

 Disease duration (months)

21.08 ± 24.23

22.04 ± 22.65

NS

 

 Formal education (years)

8.54 ± 5.30

5.77 ± 4.28

<  0.001

 

Motor and ADL

 Modified H-Y stage

1.75 ± 0.80

1.89 ± 0.84

NS

 

 UPDRS motor score

19.46 ± 9.97

22.84 ± 12.04

0.020

NS*

 UPDRS ADL score

7.02 ± 5.24

8.22 ± 6.60

NS

 

Motor scores on UPDRS

 Tremor

2.48 ± 2.17

3.64 ± 2.90

0.002

<  0.001*†

 Rest tremor (Item 20)

1.49 ± 1.67

2.41 ± 2.23

0.001

0.001*†

 Action tremor (Item 21)

0.99 ± 1.25

1.23 ± 1.45

NS

NS*

 Bradykinesia

8.93 ± 5.36

10.83 ± 6.28

0.022

NS*

 Rigidity

4.60 ± 2.83

4.92 ± 2.99

NS

 

 Gait and Posture

0.78 ± 1.19

1.16 ± 1.27

0.022

NS*

Motor scores on subtypes

 Tremor score (Jankovic)

0.44 ± 0.32

0.61 ± 0.41

0.001

<  0.001*†

 PIGD score (Jankovic)

0.41 ± 0.47

0.47 ± 0.52

NS

 

 Tremor score (Kang)

0.62 ± 0.54

0.91 ± 0.72

0.002

<  0.001*†

 Akinetic-Rigid score (Kang)

0.90 ± 0.51

1.05 ± 0.59

NS

 

Non-motor symptoms

 MMSE

25.88 ± 3.71

24.38 ± 4.00

0.005

NS**

 MoCA

23.99 ± 4.63

22.31 ± 5.04

NS

 

 BDI

11.32 ± 8.35

15.47 ± 11.51

0.005

NS**

 Total NMSS score

48.80 ± 46.12

65.72 ± 46.24

0.007

NS**

  1. NS, statistically not significant
  2. * Adjusted p-values were calculated by ANCOVA after adjustment for age, sex, age at symptom onset, formal education period, MMSE, BDI and total NMSS score
  3. ** Adjusted p-values were calculated by ANCOVA after adjustment for age, sex, age at symptom onset, formal education period, and UPDRS motor score
  4. † Means statistically significant after correcting for multiple testing using the false discovery rate