Table 2.
Predictor variables | β-coefficient | P |
---|---|---|
Visit | ||
2 | Reference | |
3 | −0.132 | |
4 | −0.304 | |
5 | −0.410 | |
Village | < 0.0001 | |
A | Reference | |
F | −0.467 | |
N | 0.228 | |
P | −0.281 | |
Birth season | 0.002 | |
1 | Reference | |
2 | −0.077 | |
3 | 0.092 | |
WAZ* | 0.35 | |
≤ −1 | −0.075 | |
≥ −1 | −0.081 | |
Interaction village × passage | 0.008 | |
Fanaye, visit 3 | 0.019 | 0.10 |
Fanaye, visit 4 | 0.116 | |
Fanaye, visit 5 | 0.196 | |
Niandane, visit 3 | −0.034 | |
Niandane, visit 4 | 0.042 | |
Niandane, visit 5 | 0.162 | |
Pendao, visit 3 | −0.085 | |
Pendao, visit 4 | 0.154 | |
Pendao, visit 5 | 0.188 | |
Interaction village* WAZ ≤ −1 | 0.001 | |
Fanaye | −0.200 | |
Niandane | 0.164 | |
Pendao | −0.000 | |
Interaction birth season × WAZ ≥ −1 | 0.0002 | |
2 | 0.326 | |
3 | 0.141 | |
0.001 |
We used WAZ as a continuous variable representative of the nutritional status. The cutoff value of −1 was not set a priori but came as a result of the analysis: the model shows that there are different tendencies observed for WAZ ≤ −1 and ≥ −1. Bold indicates significant differences (P < 0.05).