I did a statistical analysis to see the effect of lifestyle factors (physical activity, dietary intake and other covariates) on longitudinal weight gain among women using linear mixed models. The data were collected at seven surveys from the same individual (n=12,000), followed up for 19 years.
Given sensible results for most covariates, I found a very small effect size with significant p-values for some diet variables (like carbohydrates: coef.=0.0000664, 95%CI=0.000132, 0.000264, P-value<0.0001 and fat intake coef=0.00005, 95%CI=0.00003, 0.00007, P-value<0.0001, total energy is also similar).
I am not sure about this? can anyone help me to interpret this? Is it because the sample size is large enough that small differences are statistically significant?
Is it important to report a very small beta effect because it’s significant?
May be pointless to report a very small effect size even if significant?
Many thanks in advance