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Table 2 Descriptive characteristics of parous and nulliparous women (IOW and ELEMENT)

From: Assessing the effect of childbearing on blood DNA methylation through comparison of parous and nulliparous females

Discovery Cohort: IOW

Replication Cohort: ELEMENT

Characteristics

Parous

( n  = 28)

Nulliparous

( n  = 61)

Test Stat ( p -value)

Characteristics

Parous

( n  = 23)

Nulliparous

( n  = 31)

Test Stat ( p -value)

Age at T1: Mean (SD)

18 (0)

18 (0)

-

Age at T1: Mean (SD)

16.30 (1.44)

16.11 (1.14)

-0.55 (0.59)

Age at T2: Mean (SD)

26 (0)

26 (0)

-

Age at T2: Mean (SD)

20.04 (1.15)

18.63 (1.02)

-4.77 (< .0001)

BMI change (T1 to T2): Mean (SD)

2.98 (3.21)

2.69 (3.61)

0.89 (.3752)

BMI change (T1 to T2): Mean (SD)

1.61 (5.52)

0.82 (1.75)

0.75 (.4568)

Smoking Clusterb at T1:

N (%)

Smoking Cluster b at T1:

N (%)

1—non active and non-passive smokers at T1

3 (10.71%)

18 (29.51%)

7.28 (.0634)

1—non active and non-passive smokers at T1

19 (86.36%)

22 (91.67%)

0.33 (.5638)a

2—passive and non-active smokers at T1

15 (53.57%)

33 (54.10%)

2—passive and non-active smokers at T1

0

0

3—active and non-passive smokers at T1

1 (3.57%)

0 (0.0%)

3—active and non-passive smokers at T1

0

0

4—active and passive smokers at T1

9 (32.14%)

10 (16.39%)

4—active and passive smokers at T1

3 (13.64%)

4 (9.34%)

Household SES at T1: N (%)

10.86 (.0125)

Household SES at T1: N (%)

8.15 (.0170)

1—high income, median housing, low education

5 (17.86%)

25 (40.98%)

1: AMAI Score A/B (highest)

0 (0.00%)

0 (0.00%)

2—median income, high housing, high education

11 (39.29%)

28 (45.90%)

2: AMAI Score C

9 (39.13%)

24 (77.42%)

3—low income, low housing, median education

10 (35.71%)

7 (11.48%)

3: AMAI Score D

10 (43.48%)

5 (16.13%)

   

4: AMAI Score E/F (lowest)

4 (17.39%)

2 (6.45%)

  1. aThe two smoking categories with no subjects were excluded from the chi-square test
  2. bSmoking clusters were generated from passive and active smoking categories at T1 using K-mean clustering analysis (see “Confounding variables” in Method section for more details)