The subjects for this study were participants in Project Viva, a prospective, observational cohort study of gestational factors, pregnancy outcomes, and offspring health. We recruited women who were attending their initial prenatal visit at eight urban and suburban obstetrical offices of a multispecialty group practice in eastern Massachusetts. Eligibility criteria included fluency in English, gestational age <22 weeks at the initial prenatal clinical appointment, and singleton pregnancy. Details of recruitment and retention procedures are available elsewhere (18).
Of the 2,128 women who delivered a live infant, 1,579 were eligible for 3-year follow-up by virtue of having completed prenatal nutritional assessments and consenting for their children to be followed up. We collected follow-up information on 1,397 (88% of 1579), including in-person examinations on 1,283 (81%). For this analysis, we excluded 20 of the 1,283 participants whose gestational age at birth was <34 weeks, 28 participants missing height or weight at 3 years, and 125 participants missing values for any of the four risk factors, leaving a cohort for analysis of 1,110 mother-child pairs.
After obtaining informed consent, we performed in-person study visits with the mother at the end of the first and second trimesters of pregnancy, and with both mother and child immediately after delivery and at 6 months and 3 years after birth. Mothers completed mailed questionnaires at 1 and 2 years after birth. We also obtained information from medical records. Institutional review boards of participating institutions approved the study. All procedures were in accordance with the ethical standards for human experimentation established by the Declaration of Helsinki.
Comparison of the 1,110 participants in this analysis with the 1,579 who were eligible for 3-year follow-up showed a higher proportion of maternal white race (76% vs. 69%), college or graduate education (74% vs. 68%), and annual household income exceeding $70,000 (66 vs. 62%), and slightly lower smoking rates during pregnancy (10% vs. 12%) but did not differ on mean maternal prepregnancy BMI, gestational weight gain, or infant birth weight.
Risk factors. We focused on factors during the prenatal period and infancy that have been associated with childhood overweight, are likely to be causal, and are potentially modifiable. Foregoing nuance for simplicity, we elected to use each of the four risk factors in dichotomous form. That decision limited the estimated probabilities to a tractable 16 combinations of the four risk factors.
Smoking during pregnancy. We asked mothers at both first and second trimester visits about their cigarette smoking habits before and during pregnancy. In Project Viva (2) and other cohort studies (3,4,5), smoking during pregnancy is associated with increased risk of overweight during childhood. A meta-analysis of 14 studies shows that the adjusted odds ratio for overweight among children of women who smoked during pregnancy was 1.50 (95% confidence interval (CI) 1.36–1.65) (19). In this analysis, we compared women who smoked during pregnancy with those who never smoked or quit before becoming pregnant.
Gestational weight gain. At the first trimester study visit, we asked mothers to report their weights just before they became pregnant. From medical records, we collected all weights measured during prenatal visits. We calculated total weight gain by subtracting pre-pregnancy weight from the last prenatal weight. In the Project Viva cohort, we have recently shown that excessive weight gain during pregnancy is associated with increased risk of overweight at age 3; compared with inadequate gain, the odds ratio for BMI exceeding the 95th percentile (vs. <50th percentile) was 4.35 (95% CI 1.69, 11.24) (7). Other preliminary data support this association (6,8–10). In this analysis, we expressed gestational weight gain in categories based on the 1990 recommendations of the Institute of Medicine (20), which advise less weight gain for mothers with higher pre-pregnancy BMI. For example, for a woman of normal weight BMI (19.8–26.0 kg/m2), the Institute of Medicine guidelines recommend a total weight gain during pregnancy of 11.5–16 kg, whereas for a woman with high BMI (26.1–29.0 kg/m2) the recommended gain is 7–11.5 kg. We used this same range, 7–11.5 kg, for obese women (>29.0 kg/m2). In this analysis, we compared excessive maternal weight gain with adequate or inadequate gain, and to be consistent across all variables we defined normal childhood weight as BMI 5th–85th percentile rather than <50th percentile.
Breastfeeding duration. At 6, 12, and 24 months, we asked mothers whether they were still breastfeeding at all. If they had stopped, we asked them the children's age at cessation. Although the magnitude of the association between breastfeeding and later overweight is still controversial (21,22,23), the only meta-analysis examining duration of breastfeeding demonstrated a substantial decrease in odds (4% (95% CI 2–6%)) of later overweight for each additional month of breastfeeding (11). In this analysis, we compared any breastfeeding duration of <12 months with at least 12 months, which is recommended by the American Academy of Pediatrics (24).
Daily sleep during infancy. At 6 and 12 months postpartum, we asked mothers to quantify the average amount of daily sleep their children obtained over the past month. The questions prompted them to include morning and afternoon naps in addition to nighttime sleep. Using these questions, we have recently shown in the Project Viva cohort that average daily sleep duration from 6 to 24 months is inversely associated with overweight at 3 years (16). In that analysis, comparing average daily sleep duration of <12 with at least 12 h/day, the odds ratio for overweight was 2.04 (95% CI 1.07, 3.91). Here, we limited the sleep variable to 6 and 12 months because we were interested in the first year after birth. We used the mean of 6-month and 12-month sleep among the 914 participants with data at both timepoints; in the remainder of participants one time point was missing, so we used the nonmissing value to represent the mean. In this analysis, we compared daily sleep duration of <12 h with at least 12 h, as in our published work (16).
Outcome measures. At 3 years, we measured weight using a calibrated scale (Seca model 881; Seca, Hanover, MD) and length using a calibrated stadiometer (Shorr Productions, Olney, MD), and we calculated age- and sex-specific BMI z-scores using US national reference data (25). We defined overweight as BMI ≥95th percentile for age and sex, and used BMI 5th–85th percentile as the comparison.
Other measures. Using a combination of self-administered questionnaires and interviews, we collected information about maternal pre-pregnancy weight, height, age, education, and parity, father's weight and height, child's age, sex, and race/ethnicity, and household income. We calculated birth weight for gestational age z-score as a measure of fetal growth (26). As a measure of infant weight gain, we calculated the difference between weight-for-age z-scores at 6 months and at birth (25). Both fetal growth and rapid early infancy weight gain are directly associated with later BMI in childhood or adulthood (12,13,14,15,27). In this analysis, we considered fetal growth and infant weight gain to be “nonmodifiable” factors that might be intermediates in the causal pathways between the four risk factors and childhood obesity. At age 3, we estimated energy intake from a validated food frequency questionnaire (28), a weighted average of hours of television watched on weekdays and weekend days, and physical activity by asking mothers to report whether their children were less active, more active, or about the same as other children. As these three variables reflect energy intake and expenditure, we also considered them to be potential mediators.
To obtain estimates of the independent association of each risk factor with the outcome, we used logistic regression models that included all four modifiable risk factors as well as the four “nonmodifiable” determinants maternal prepregnancy BMI and education, child race/ethnicity, and household income. Here, we consider these four factors nonmodifiable because usually they are fixed from the few months before pregnancy through 1 year after pregnancy. In preliminary modeling, we also included six additional potential confounding variables, namely maternal age and parity, paternal BMI, duration of gestation, and child sex and exact age. Because their inclusion did not materially change the effect estimates for the four risk factors, we left them out of the final model. Note that child age and sex are de facto in the final model because the BMI percentile calculation includes them.
Using parameter estimates from the multivariate logistic models, we estimated the predicted probability of overweight for each of the 16 combinations of the four risk factor variables. To estimate predicted probabilities, we needed to choose fixed values for the nonmodifiable determinants, and we selected a “typical” participant. By typical, we mean an individual with the modal values of race/ethnicity, education, and income, and the mean value of BMI, i.e, one who was white, and who had a mother with a bachelor's degree and a BMI of 24.5 kg/m2, and a household income between $40,000 and $70,000. In this article, we show estimates for the 16 combinations of the four risk factors. In secondary analyses, we additionally adjusted for the two potentially mediating variables fetal growth and infant weight gain from birth to 6 months. We conducted all analyses using SAS, version 9.1 (Cary, NC).