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. 2013 Nov 20;8(11):e79756. doi: 10.1371/journal.pone.0079756

Table 3. Pre and post imputation descriptives of all study variables.

Variable Pre imputation Post imputation (N = 288)1 NA2 (%)
Mean (SD) N (%) Mean (SD) N (%)
Age3 (years) 9.59 (1.93) 9.59 (1.92) 0
Hg (µg/g) 0.13 (0.11) 0.13 (0.10) 36.1
Sex: 0
Male 156 (54.2) 156 (54.2)
Female 132 (45.8) 132 (45.8)
Mother in contact withHg during pregnancy: 12.5
No 176 (69.8) 197 (68.4)
Yes 76 (30.2) 91 (31.6)
Father’s occupation3: 18.8
Industrial gold mine 9 (3.8) 19 (6.6)
Industrial copper mine 42 (17.9) 54 (18.9)
Traditional gold mining 44 (18.8) 55 (19.0)
Outside mining 139 (59.4) 160 (55.6)
Hg exposure in householdand child playing inside: 17.7
No 211 (89.0) 253 (87.8)
Yes 26 (11.0) 35 (12.2)
Fish consumption: 4.2
<1 times/week 85 (30.8) 89 (30.9)
1–4 times/week 131 (47.5) 136 (47.2)
>4 times/week 60 (21.74) 63 (21.9)
Number of siblings3: 5.9
0 26 (9.6) 29 (10.1)
1–2 170 (62.7) 176 (61.1)
>2 75 (27.7) 83 (28.8)
Hours spent indoors3: 22.2
<3 hours/day 23 (10.3) 33 (11.8)
3–6 hours/day 49 (21.9) 67 (26.7)
>6 hours/day 152 (67.8) 189 (61.5)
Mother employed3: 8.3
No 191 (72.4) 209 (72.6)
Yes 73 (27.6) 79 (27.4)
Father employed3: 13.5
No 23 (9.2) 30 (10.4)
Yes 226 (90.8) 258 (89.6)
Somebody smoking in household3: 10.1
No 188 (72.6) 209 (72.6)
Yes 71 (27.4) 79 (27.4)
1

Descriptives for variables post imputation were calculated using Rubin’s rules.

2

NA = missing value. Column displays percentage of missing values in variable.

3

Variable additionally included in imputation model to improve missing at random assumption.