Objective | Hypothesis | Outcome measure (type of outcome: B = binary or C = continuous) | Methods of analysis |
---|---|---|---|
1. Primary | An experimental combined Nutrition + Exercise intervention will increase the percentage of pregnant women who achieve GWG within current recommendations when compared with standard care provided in the primary care community setting | Proportion of women who are within the BMI appropriate GWG according to the IOM guideline for GWGs (B) | Logistic regression |
2. Secondary | An experimental combined Nutrition + Exercise intervention will lead to better maternal and child bone health outcomes when compared to standard care | • Maternal and cord blood circulating bone markers (C) ○ Bone biomarkers: PINP, CTX-I, IGF-1, 25(OH)D, 1,25(OH)2D • Maternal bone status at 6 months postpartum (C) ○ Whole body bone mineral content, whole body BMD, lumbar spine bone mineral density by DXA scan • Maternal fat mass (C) • Maternal blood glucose, lipid profile, leptin, and adiponectin • Maternal blood pressure (C) ○ Diastolic BP ○ Systolic BP • Maternal pregnancy outcomes (B) ○ Gestational diabetes ○ Pre-eclampsia • Infant bone status at 6 months of age (C) ○ Whole body minus the head bone mineral content by DXA scan • Infant outcomes ○ Birth weight z-score(C) ○ Body fat mass (B) | Regression analysis *We will use logistic regression for binary outcomes and linear regression for continuous outcomes |
3. Subgroup analyses | The percentage of women within each of the normal, overweight, and obese BMI categories will be similar with respect to being with the IOM target GWG for each category | Proportion of women in each BMI category who reach appropriate GWG according to the IOM guideline for GWGs | Regression analysis including the interaction term of BMI group X Intervention group |
4. Sensitivity analyses | Combined Nutrition + Exercise Intervention leads to a greater percentage of women who achieve GWG within current recommendations when compared to standard care | Primary outcome only | • Generalized estimating equations • Random-effects model |