TABLE 5.
Multiple linear regression analysis of allocation group as a predictor of log fat mass index in girls only, adjusted for maternal and newborn characteristics (per protocol sample)
| Model 1, N = 438 | Model 2, N = 317 | |||||
|---|---|---|---|---|---|---|
| Exposure | Linear regression coefficient | 95% CIs | P value | Linear regression coefficient | 95% CIs | P value |
| Maternal | ||||||
| Allocation group (control = 0, intervention = 1) | 0.1041 | 0.037, 0.170 | 0.003 | 0.0851 | 0.004, 0.167 | 0.04 |
| Age, y | –0.009 | –0.018, –0.000 | 0.05 | –0.016 | –0.028, –0.005 | 0.005 |
| BMI, kg/m2 | 0.025 | 0.016, 0.034 | <0.001 | 0.024 | 0.013, 0.036 | <0.001 |
| Height, cm | –0.004 | –0.010, 0.002 | 0.20 | –0.005 | –0.012, 0.002 | 0.18 |
| Parity – primiparous | –0.059 | –0.139, 0.020 | 0.15 | –0.054 | –0.158, 0.050 | 0.31 |
| Parity – multiparous | –0.112 | –0.218, –0.005 | 0.04 | –0.115 | –0.243, 0.014 | 0.08 |
| Socioeconomic status score | –0.000 | –0.007, 0.006 | 0.91 | –0.003 | –0.010, 0.005 | 0.49 |
| Child | ||||||
| Age, y | 0.053 | 0.006, 0.0101 | 0.03 | 0.032 | –0.029, 0.093 | 0.31 |
| Birth weight, kg | — | — | — | 0.128 | 0.111, 0.245 | 0.03 |
| Gestational age, weeks | — | — | — | –0.012 | –0.035, 0.010 | 0.29 |
1
For allocation group, the regression coefficient represents the difference in log fat mass between the intervention and control groups. To translate this into a more meaningful value the coefficient is antilogged (exponentiated: values become 1.11 for Model 1 and 1.09 for Model 2) and this value indicates the multiplicative difference between control and intervention groups; for example: an exponentiated value of 1.11 means that fat mass index was 11% higher in the intervention group than in the control group.