Volume 201, Issue 1 , Pages 58.e1-58.e8, July 2009
Associations of diet and physical activity during pregnancy with risk for excessive gestational weight gain
Article Outline
Objective
We sought to identify modifiable risk factors for excessive gestational weight gain (GWG).
Study Design
We assessed associations of diet and physical activity with excessive GWG among 1388 women from the Project Viva cohort study.
Results
Three hundred seventy-nine women (27%) were overweight (body mass index ≥ 26 kg/m2) and 703 (51%) experienced excessive GWG, according to Institute of Medicine guidelines. In multivariable logistic regression models, we found that intake of total energy (odds ratio [OR], 1.10; 95% confidence interval [CI], 1.00-1.22, per 500 kcal/d), dairy (OR, 1.08; 95% CI, 1.00-1.17, per serving per day), and fried foods (OR, 3.47; 95% CI, 0.91-13.24, per serving per day) were directly associated with excessive GWG. First trimester vegetarian diet (OR, 0.46; 95% CI, 0.28-0.78) and midpregnancy walking (OR, 0.92; 95% CI, 0.83-1.01, per 30 minutes per day) and vigorous physical activity (OR, 0.76; 95% CI, 0.60-0.97, per 30 minutes per day) were inversely associated with excessive GWG.
Conclusion
A healthful diet and greater physical activity are associated with reduced risk for excessive GWG.
Key words: diet, obesity, physical activity, pregnancy, weight gain
In the current era of epidemic obesity, excessive gestational weight gain (GWG) is emerging as an important predictor of maternal and offspring obesity and obstetric complications. Independent of their weight entering pregnancy, mothers who gain excessively during pregnancy are more likely to deliver by cesarean section,1, 2, 3, 4 have an unsuccessful trial of labor after cesarean section,5 develop preeclampsia,3 retain excessive weight after delivery,6 and become overweight or obese in later life.7, 8 Infants born to women who gain excessively during pregnancy are more likely to be born preterm,9 be macrosomic at birth (> 9 lbs),2, 10, 11 and become overweight or obese as toddlers,12 adolescents,13 and adults.14
Previously reported sociodemographic predictors of excessive GWG include nulliparity, prepregnancy overweight body mass index (BMI) low income, and young maternal age.15, 16, 17 Limited data are available, however, regarding modifiable predictors of excessive GWG. We therefore explored associations of diet and physical activity with excessive GWG in Project Viva, a prospective cohort study of maternal and child health.
Materials and Methods
Women were recruited for Project Viva at their first prenatal visit at 1 of 8 urban and suburban obstetric offices of a multispecialty group practice in eastern Massachusetts. To be eligible for the study, potential participants were required to be fluent in English, < 22 weeks' gestation at study entry, and have a singleton pregnancy; 65% of women who met these criteria agreed to participate in the study. All participants provided written informed consent. A human studies committee approved all procedures in accordance with ethical standards for human experimentation.
Of 2128 women who delivered a live singleton infant, 2083 delivered after 34 weeks. We excluded from our study those missing information on prepregnancy BMI and GWG (n = 31). Of the remaining 2052 women, we excluded those missing data on covariates associated with excessive GWG, including maternal age, race, first trimester nausea, household income, and smoking status (n = 226). Among the remaining 1826 women, 1388 provided data on both first- and second-trimester diet and on midpregnancy physical activity, making them eligible for inclusion in our analysis.
Compared with the 2052 women potentially eligible for our study, those for whom diet, physical activity, or covariate data were not available were more likely to be black (30% vs 10%) or Hispanic (11% vs 5%), < 25 years old (18% vs 5%), and multiparous (58% vs 50%) than women who were included in the analysis. They were also more likely to be obese (24% vs 15%). Rates of excessive GWG were similar in the 2 groups (50% vs 51%).
Measures of gestational weight gain
We determined GWG by calculating the difference between self-reported prepregnancy weight and the last weight recorded before delivery. Self-reported prepregnancy weight has been previously validated in our cohort.12
We defined excessive GWG as gain greater than the upper limit for each woman's prepregnancy BMI category by the Institute of Medicine guidelines.18 The guidelines recommend that women with a BMI < 19.8 kg/m2 should gain 12.5-18 kg; those with a BMI of 19.8-26.0 kg/m2 should gain 11.5-16 kg; those with a BMI of 26.0-29.0 kg/m2 should gain 7-11.5 kg; and those with a BMI > 29.0 kg/m2 should gain at least 6.8 kg. We used an upper limit of 11.5 kg for women in this high BMI group.
Assessment of exposures
We assessed dietary exposures with semiquantitative food frequency questionnaires (FFQ) administered in the first and second trimesters of pregnancy. The 166-item questionnaires were modified slightly from the extensively validated FFQ used in the Nurses' Health Studies and several other large cohort studies. At a mean of 11.7 weeks of gestation, participants completed the first questionnaire, which covered diet since the last menstrual period, and at a mean of 29.2 weeks of gestation, they completed the second questionnaire, which covered the previous 3 months. The Project Viva FFQ has been biochemically calibrated in a pilot study of 72 black and 132 white pregnant women.19 Because we have previously shown little change between intakes of most first- and second-trimester foods and nutrients in our cohort,19 we used the mean of first- and second-trimester intake for our primary analysis. As a secondary analysis, we tested whether a change in intake from the first to second trimester was associated with excess weight gain.
We estimated servings per day of several foods, including sugar-sweetened beverages, fried foods, dairy, fruits and vegetables, red and processed meats, and whole grains. Whole-milk dairy included servings per day of whole-milk yogurt, cottage cheese, cream cheese, other cheese, whole milk, ice cream, and milk shakes. We also estimated the intake of total energy and several nutrients, including fiber, glycemic index, and glycemic load. We used the nutrient residual method to energy-adjust fiber, glycemic index, and glycemic load, and we modeled dietary fat, proteins, and carbohydrates using energy density.
During interviews in the first and second trimesters, participants were asked, “Since you learned you were pregnant, have you been eating a vegetarian diet (a diet that excludes certain animal products)?” We examined the association between vegetarian diet in each trimester and excessive gain separately because some women reported adhering to a vegetarian diet in 1 trimester but not the other (31 in the first but not the second trimester, 19 in the second but not the first trimester).
We assessed physical activity using a questionnaire modified from the Physical Activity Scale for the Elderly.20 At 26-28 weeks' gestation, participants reported hours per week of television watching, walking, light-to-moderate activities, (excluding walking), and vigorous activity during the previous 3 months. We calculated hours per week of total activity by summing walking, light-to-moderate, and vigorous activity. We defined sedentary lifestyle as < 2.5 hours per week, or < 22 minutes per day, of total activity.
Covariates
We used participant interviews and questionnaires to collect data on parity (0, 1, 2, or 3+), age (14-20, 20-25, 25-30, 30-35, 35-40, or ≥ 40 years), race (white, black, Hispanic, Asian, or other), employment status (student, employed < 35 hours per week, employed > 35 hours per week, unemployed and not looking for work, unemployed and looking for work, or on maternity leave), work-related physical activity (low level of physical work vs moderate or high level of physical work), household income (≤ $10,000, $10,001-20,000, $20,001-40,000, $40,001-70,000, ≥ $70,000, or do not know), maternal education (< high school, high school diploma, some college, BA or BS, or graduate degree), pregnancy-associated nausea and vomiting (yes or no), dietary cravings (yes or no), and depressive symptoms, measured by Edinburgh Postnatal Depression Scale in midpregnancy (≥ 15, 13-14, or < 13).21 Smoking status was coded as never, former, or current if the participant reported smoking at any time during pregnancy.
Analysis
We examined bivariate associations between outcome and exposures using t tests for normally distributed continuous exposures, Wilcoxon rank sum tests for nonnormally distributed continuous exposures, and χ2 tests for categorical exposures. We constructed our multivariable model in 3 steps: first, we identified demographic and psychosocial variables that were independently associated with excess weight gain, and included these variables in our model. Second, we examined associations between diet or physical activity and excessive weight gain, adjusting for these independent predictors. Finally, for those behaviors that were associated with excessive weight gain, we tested for confounding by sociodemographic variables.
To identify independent predictors, we began with the variables that were associated with excessive gain in bivariate analyses, and we sequentially added these risk factors to our model. We retained those risk factors that were independently associated with excess weight gain (type 3 analysis of effects P < .05). Because excessive gain varies considerably with BMI, we explored several approaches to modeling baseline BMI, including linear BMI, linear + quadratic BMI, BMI deciles, and BMI divided into 5 percentile categories. We compared models associating prepregnancy BMI with excess weight gain using the likelihood ratio test, and we retained the more complex model if the P value was < .05. Because our model with 5 percentile categories was superior to our model that used BMI deciles (likelihood ratio P = .01), we used this more complex model to adjust for prepregnancy BMI.
We then related diet and lifestyle factors with excessive GWG, using multivariable logistic regression to model the continuous relation between each exposure and odds of excessive GWG vs adequate or inadequate gain, adjusting for independent predictors of excessive gain. We used a multivariable nutrient density model to examine macronutrient composition.22 In this model, we simultaneously entered total energy intake, as well as percentage of energy from protein, monounsaturated fat, polyunsaturated fat, saturated fat, and trans fat, into the model. The odds ratios (ORs) in this model estimate the effect of intake of the macronutrient compared with an equivalent amount of energy from carbohydrates.
We then tested for confounding by additional demographic and psychosocial factors to our models, retaining those factors that changed the odds of excessive weight gain for a modifiable exposure by > 10%. In a sensitivity analysis, we tested whether using only women with adequate gain, rather than women with inadequate or adequate gain, as our reference group, altered our results. In a secondary analysis, we used multivariable linear regression to examine the relation between modifiable behaviors and total weight gain, adjusted for gestational age at delivery.
Finally, we selected those dietary and physical activity exposures that were independently associated with excessive weight gain, total weight gain, or both, and we included them in a single multivariable model. For these models, we assessed both odds of excessive weight gain, using logistic regression, and total gain, using linear regression. We further adjusted these models for total energy intake, to test whether the caloric contribution of specific foods mediated the observed associations.
The purpose of our study was to investigate the strength and direction of potential associations, rather than test a specific null hypothesis. We therefore reported OR or effect estimates and 95% confidence intervals (CIs), rather than P values, for multivariable analyses.
Results
A total of 1388 women met criteria for inclusion in our study, among whom 379 (27%) were overweight (BMI ≥ 26 kg/m2) entering pregnancy and 703 (51%) experienced excessive GWG.
In bivariate analyses (Table 1), excessive weight gain was slightly more common among women who were 25-30 years old, and less common among women who were ≥ 35 years old. We also found somewhat higher rates of excessive gain among women who were nulliparous, did not experience first-trimester nausea, were overweight (BMI 26-29 kg/m2) before pregnancy, or who were past or current smokers.
TABLE 1. Participant characteristics according to category of GWG, by Institute of Medicine guidelines
| Characteristic | GWG inadequate or adequate, n (%) | GWG excessive, n (%) | P |
|---|---|---|---|
| Age (y) | .05 | ||
 < 25 | 39(51.3) | 37(48.7) | |
| 25 to < 30 | 127(44.1) | 161(55.9) | |
| 30 to < 35 | 299(48.2) | 321(51.8) | |
| ≥ 35 | 220(54.5) | 184(45.5) | |
| Race | .02 | ||
| White | 503(47.7) | 551(52.3) | |
| Black | 71(51.4) | 67(48.6) | |
| Hispanic | 42(56.0) | 33(44.0) | |
| Asian | 49(66.2) | 25(33.8) | |
| Other | 20(42.6) | 27(57.4) | |
| Parity | .16 | ||
| 0 | 328(46.8) | 373(53.2) | |
| 1 | 255(51.8) | 237(48.2) | |
| 2 | 80(54.8) | 66(45.2) | |
| 3+ | 22(44.9) | 27(55.1) | |
| Smoking | .002 | ||
| Past | 140(44.6) | 174(55.4) | |
| Current | 58(39.2) | 90(60.8) | |
| Never | 487(52.6) | 439(47.4) | |
| First-trimester nausea | .002 | ||
| Yes | 611(51.0) | 587(49.0) | |
| No | 74(38.9) | 116(61.1) | |
| BMI (kg/m2) | <.001 | ||
| < 26 | 565(56.0) | 444(44.0) | |
| 26-29 | 35(21.2) | 130(78.8) | |
| > 29 | 85(39.7) | 129(60.3) | |
| Gestational age at delivery, median (IQR) | 39.7(38.7-40.6) | 40.0(39.0-40.9) | <.001 |
When we examined these risk factors for excessive weight gain using multivariable logistic regression, we found that prepregnancy BMI, race, maternal age, smoking status, gestational age at delivery, and nausea in the first trimester were independently related to excessive weight gain. Overweight women (BMI 26-29 kg/m2) had the highest risk of excessive gain, although obese women were also more likely than normal weight women to gain excessively. Women of Asian, black, or Hispanic race/ethnicity had a lower risk of excessive gain than white women. Those women who were 25-30 years of age were at higher risk of excess gain than younger or older women. We found several factors associated with lower risk of excessive gain, including first-trimester nausea vs no first-trimester nausea, never-smoking status vs current or past smoking status, and earlier gestational age at delivery vs later gestational age at delivery. We included these factors as covariates in our multivariable-adjusted models. Other potential predictors, including parity, employment, and work-related physical activity, Edinburgh Postnatal Depression Scale score, maternal education, household income, and dietary cravings were not independently associated with excessive weight gain, and we therefore did not include them in our model.
In unadjusted comparisons of diet and physical activity between women with and without excessive weight gain (Table 2), we found that total energy intake was higher among women with excessive gain, whereas walking, vigorous activity, total activity, and prevalence of vegetarian diet were lower among women with excessive gain. Sedentary lifestyle (< 2.5 hours per week of total activity) was also somewhat more common among women with excessive gain. For intake of fried foods, we found that the median and interquartile range for servings per day did not differ, but the 90th percentile for intake among women with excessive gain was higher than for women without excessive gain. This difference in distribution of intake was statistically significant (Wilcoxon rank sum P = .007).
TABLE 2. Levels of dietary intake and physical activity among 1388 women enrolled in Project Viva, comparing those with and without excessive weight gain
| Variable | GWG inadequate or adequate (n = 685) | Excessive GWG (n = 703) | Bivariate P valuea | Multivariate adjusted odds of excessive GWGb | ||
|---|---|---|---|---|---|---|
| Mean or median | (SD) or [IQR] | Mean or median | (SD) or [IQR] | OR (95% CI) | ||
| FOOD AND FOOD GROUPS, SERVINGS/d | ||||||
| Sugar-sweetened beverages, median [IQR]c | 0.36 | [0.11-0.75] | 0.37 | [0.12-0.75] | .42d | 0.93(0.78-1.11) |
| Fried foods, median [IQR]c | 0.11 | [0.07-0.14] | 0.11 | [0.07-0.14] | .007d | 3.68(0.96-14.13) |
| Dairy | 2.90 | (1.52) | 3.04 | (1.49) | .08 | 1.08(1.00-1.17) |
| Low fat dairy | 1.49 | (1.31) | 1.59 | (1.34) | .17 | 1.08(0.98-1.18) |
| Whole milk dairy | 1.41 | (1.01) | 1.46 | (0.97) | .42 | 1.06(0.94-1.20) |
| Fruits and vegetables | 5.84 | (2.60) | 5.90 | (2.71) | .68 | 1.03(0.98-1.07) |
| Red and processed meats | 0.53 | (0.40) | 0.56 | (0.39) | .19 | 1.00(0.74-1.34) |
| Whole grains | 1.25 | (1.03) | 1.27 | (1.04) | .63 | 1.06(0.95-1.19) |
| NUTRIENTS AND DIETARY PATTERNS, g | ||||||
| Kcal/d | 2060.01 | (593.76) | 2131.40 | (570.36) | .02 | 1.11(1.00-1.23) |
| Fiber (g/d) | 19.97 | (5.75) | 19.50 | (5.04) | .10 | 0.98(0.87-1.09) |
| Glycemic index | 754.24 | (120.92) | 746.08 | (115.09) | .20 | 0.98(0.88-1.08) |
| Glycemic load | 14,597.52 | (1940.93) | 14,516.26 | (1930.13) | .43 | 1.00(0.88-1.13) |
| VEGETARIAN DIET | ||||||
| First trimester, n (%) | 55 | (8.0) | 27 | (3.9) | .001e | 0.45(0.27-0.76) |
| Second trimester, n (%) | 42 | (6.2) | 28 | (4.0) | .06e | 0.70(0.40-1.20) |
| MACRONUTRIENT COMPOSITION (% energy) | ORf | |||||
| Carbohydrates | 54.95 | (6.41) | 54.67 | (6.30) | .41 | 1.0(ref) |
| Protein | 17.53 | (2.56) | 17.62 | (2.46) | .53 | 1.10(0.86-1.42) |
| Total fat | 28.94 | (5.12) | 29.16 | (4.93) | .41 | |
| Monounsaturated fat | 10.96 | (2.33) | 10.98 | (2.22) | .87 | 0.63(0.40-0.99) |
| Polyunsaturated fat | 6.18 | (1.40) | 6.25 | (1.41) | .40 | 1.32(0.80-2.18) |
| Saturated fat | 10.78 | (2.32) | 10.94 | (2.21) | .20 | 1.33(0.87-2.02) |
| Trans fat | 0.97 | (0.29) | 0.99 | (0.28) | .13 | 1.27(0.39-4.13) |
| PHYSICAL ACTIVITY, min/dc | OR per 30 min/d | |||||
| Walking | 34 | [17-60] | 34 | [17-43] | .03d | 0.92(0.83-1.01) |
| Moderate activity | 0 | [0-17] | 0 | [0-17] | .53d | 1.00(0.85-1.17) |
| Vigorous activity | 0 | [0-9] | 0 | [0-0] | .005d | 0.76(0.60-0.96) |
| Total activity | 34 | [17-60] | 34 | [17-43] | .03d | 0.95(0.89-1.01) |
| TV watching | 86 | [43-129] | 86 | [51-129] | .11d | 0.98(0.93-1.02) |
| Sedentary lifestyle (< 2.5 h/wk total activity), n (%) | 132 | (19.3) | 165 | (23.5) | .06a | 1.26(0.95-1.69) |
at test with equal variance, not excessive vs excessive gain; |
badjusted for prepregnancy body mass index (in 5 percentile categories), maternal age (14-20, 20-25, 25-30, 30-35, 35-40, 40+ y) race/ethnicity, smoking status, gestational age at delivery (wks), and nausea in the first trimester of pregnancy; |
cmedian and interquartile range presented for exposures that were not normally distributed; |
dWilcoxon rank sum test, not excessive vs excessive gain; |
eχ2 test; |
fmultivariate nutrient density model. Total energy intake and percent energy from protein, monounsaturated fat, polyunsaturated fat, saturated fat, and trans fat were entered simultaneously into the model, so OR estimates the effect of intake of the macronutrient compared with an equivalent amount of energy from carbohydrates. We present OR per 2% energy for trans fat, per 5% for all other macronutrients; g. We present OR for energy intake per 500 kcal/d; fiber per 5 g/d; glycemic index per 100 u/d; glycemic load per 2000 u/d. |
We found similar results for multivariable-adjusted logistic regression models (Table 2). Total energy intake (OR, 1.11; 95% CI, 1.00-1.23 per 500 kcal/d) and total dairy consumption (OR, 1.08; 95% CI, 1.00-1.17 per serving per day) were directly associated with excessive GWG. This association did not appear to be entirely related to whole-milk dairy intake, because both low-fat and whole-milk dairy were associated with increased excessive gain. We also found a trend toward increased risk with fried food intake (OR, 3.68; 95% CI, 0.96-14.13 per serving per day). Vegetarian diet in the first trimester was inversely associated with excessive gain (OR, 0.45; 95% CI, 0.27-0.76). We did not find an association between second-trimester vegetarian diet and excessive gain. Sugar-sweetened beverage intake, trans fat intake, glycemic index, and glycemic load were not associated with excessive gain (Table 2). When we assessed the relation of change in intake of foods and nutrients from the first to second trimester with excessive gain, we found no associations (data not shown).
In our analysis of percentage of energy from macronutrients and total weight gain, we compared the effects of substituting 5% energy from protein and various types of fat with 5% energy from carbohydrates (Table 2). We found that percentage of energy from monounsaturated fat was inversely related with risk for excess GWG (OR, 0.63; 95% CI, 0.40-0.99), whereas percentage of energy from protein, saturated fat, polyunsaturated fat, and trans fat was directly associated with excess GWG; however, CIs for these macronutrients were wide.
Vigorous physical activity in the second trimester was inversely associated with excessive gain (OR, 0.76; 95% CI, 0.60-0.96 per 30 minutes per day) with a trend toward decreased risk for walking (OR, 0.92; 95% CI, 0.83-1.01 per 30 minutes per day) and total activity (OR, 0.95; 95% CI, 0.89-1.01 per 30 minutes per day). Sedentary lifestyle (< 2.5 hours per week total activity) was associated with a nonsignificant increased risk of excessive gain (OR, 1.26; 95% CI, 0.95-1.69). We did not find an association between television watching and excessive gain. Of note, television watching was not associated with sedentary lifestyle in our population, with similar patterns of television viewing among both active and sedentary women (median; interquartile range, 1.4; 0.9-2.1 vs 1.4; 0.7-2.1 hours per day; Wilcoxon P = .75).
We tested several demographic and psychosocial risk factors as potential confounders of the observed associations, including employment, marital status, maternal education, household size, household income, Edinburgh Postnatal Depression Scale score, perceived weight, and pregnancy-associated vomiting. None of these factors materially altered the multivariable-adjusted OR for the observed associations (data not shown).
When we examined significant predictors of excessive gain in a single model (Table 3), we found that fried food and dairy intake remained directly associated, whereas vegetarian diet, walking, and vigorous activity remained inversely associated with excessive gain. Adjustment for total energy intake slightly attenuated the associations with fried food intake and dairy intake, but did not change the associations with vegetarian diet, vigorous activity, and walking. These results suggest that excessive calorie intake mediates part of the associations of fried foods and dairy products with excessive GWG.
TABLE 3. Multivariate regression modelsa incorporating significant predictors of excessive weight gain or total weight gain
| Exposure | ORb for excessive GWG (95% CI) | Effect estimate for total weight gain (kg)c (95% CI) |
|---|---|---|
| Sugar sweetened beverages, per serving per day | 0.87(0.72-1.05) | -0.46(-0.87to-0.05) |
| Fried foods, per serving per day | 4.24(1.04-17.18) | 1.21(-1.93to4.34) |
| Dairy, per serving per day | 1.09(1.01-1.19) | 0.23(0.05-0.41) |
| Vegetarian diet, first trimester | 0.48(0.28-0.81) | -1.65(-2.79to-0.51) |
| Walking (30 min/d) | 0.94(0.85-1.05) | -0.20(-0.43to0.04) |
| Vigorous activity (30 min/d) | 0.78(0.61-1.00) | -0.37(-0.90to0.17) |
aAdjusted for prepregnancy body mass index (in 5 percentile categories), maternal age (14-20, 20-25, 25-30, 30-35, 35-40, ≥ 40 y) race/ethnicity, smoking status, gestational age at delivery (wks), and nausea in the first trimester of pregnancy; |
bmultivariate logistic regression model; |
cmultivariate linear regression model. |
In a sensitivity analysis, we similarly modeled risk factors for excess gain compared with adequate gain. Using this approach, we found a stronger association between fried food intake and excessive GWG (OR, 6.36; 95% CI, 1.34-30.31 per serving per day). Otherwise, our results were not materially changed.
Predictors of total weight gain were similar to those of excessive gain. Using multivariable linear regression, we found that total dairy intake (OR, 0.21; 95% CI, 0.02-0.39 kg per serving per day) and low-fat dairy intake (OR, 0.23; 95% CI, 0.02-0.44 kg per serving per day) were associated with increased gain, whereas first-trimester vegetarian diet (OR, -1.75; 95% CI, -2.89 to -0.61) and sugar-sweetened beverages (OR, -0.39; 95% CI, -0.79 to 0.01 kg per serving per day) were associated with decreased gain. Whole-milk dairy intake was not associated with total weight gain (OR, 0.08; 95% CI, -0.20 to 0.36 kg per serving per day). Walking was inversely associated with total gain (OR, -0.25; 95% CI, -0.48 to -0.02 kg per 30 minutes per day), with a trend toward lower gain with total physical activity (OR, -0.48; 95% CI, -1.01 to 0.04 kg per 30 minutes per day) and moderate activity (OR, -0.12; 95% CI, -0.27 to 0.02 kg per 30 minutes per day).
Similar to results for excessive gain, total gain was directly associated with percentage of energy from protein, polyunsaturated fat, and saturated fat, whereas percentage of energy from monounsaturated fat was associated with lower gain; however, CIs were wide. We found no association between total weight gain and percentage of energy from trans fat (P = .94).
When we assessed the effects of predictors of total weight gain in a single multivariable model (Table 3), we found that sugar-sweetened beverages, vegetarian diet, and walking remained inversely associated with total gain, whereas dairy intake remained directly associated. Adding total energy intake to the model attenuated the association between dairy intake and total gain and strengthened the inverse association with sugar-sweetened beverages. Adjustment for total energy intake did not change the associations between vegetarian diet, walking, and weight gain.
Comment
In this prospective cohort study, total energy intake and the consumption of dairy and fried foods were directly associated with excessive weight gain, whereas an early pregnancy vegetarian diet was inversely associated with excessive GWG. Vigorous activity, walking, and total activity during pregnancy were inversely associated with excessive GWG. These findings suggest that moderating caloric intake, avoiding fried foods, and engaging in physical activity during pregnancy may reduce risk for excessive GWG.
Strengths of our study include prospective assessment of diet, use of a validated food frequency questionnaire, and assessment of physical activity of different intensities. In addition, the extensive demographic and psychosocial data collected in Project Viva allowed us to adjust for multiple independent predictors of excessive GWG.
Nevertheless, our findings must be interpreted within the context of the study design. All observational studies are subject to confounding, and it is possible that unmeasured health behaviors confound observed associations between diet, physical activity, and excessive GWG. However, adjusting for measured confounders did not materially alter our results. We examined multiple predictors of excessive GWG in our model, and it is possible that some of our findings are related to chance, but most were in hypothesized directions. Randomized trials of dietary advice and encouragement of leisure-time physical activity during pregnancy will be needed to establish a causal association.
Our data confirm and extend earlier work on modifiable risk factors for excessive GWG. Several authors have reported that higher energy intake during pregnancy is correlated with greater absolute weight GWG and/or increased risk of excessive GWG.23, 24, 25, 26 We also found that dairy consumption was associated with excessive GWG, consistent with findings in 2 other studies. This association did not appear to be wholly related to whole-milk dairy intake. Olafsdottir et al25 reported a higher risk of excessive weight gain among women who reported drinking more milk in later pregnancy, compared with intake before pregnancy. Olsen et al27 similarly reported greater weight gain, and higher birthweights, with higher levels of milk consumption. The authors suggest that higher levels of insulin-like growth factor-1 (IGF-1) associated with milk intake may drive this association. IGF-1 is present in both low-fat and whole-milk dairy products. We could not address whether the current recommendations for 3 servings of dairy products per day28 should be revised.
We found that intake of fried foods was directly related to a risk of excessive GWG. Some studies in nonpregnant populations have linked consumption of fried or fast food to weight gain.29, 30, 31 We did not observe any change in risk of excessive gain with consumption of fruits and vegetables, whole grains, or fiber. These findings are consistent with a recent clinic-based trial designed to reduce excessive GWG through increased consumption of fruits, vegetables, and high-fiber bread.32 In that trial, although women in the intervention group increased consumption of these foods, there was no reduction, and in fact a suggestion of an increase, in risk for excessive GWG (overall OR for excessive gain in intervention vs control clinics, 1.94; 95% CI, 0.97-4.34).
In linear regression analysis, we found that greater sugar-sweetened beverage intake was associated with lower total GWG (OR, -0.39; 95% CI, -0.79 to -0.01 kg per serving per day). This result conflicts with data from nonpregnant populations linking sugar-sweetened beverage consumption with increased obesity risk.33 It is possible that reverse causation explains our results. If individuals who are already overweight or struggling with weight gain decrease their intake of sugar-sweetened beverages, it may give the appearance of an inverse association. Although we adjusted for prepregnancy BMI in our analysis, it is possible that residual confounding by BMI or tendency to gain weight explains the observed association. Alternately, differences in macronutrient intake may underlie our finding. Two previous studies have reported lower GWG among women with higher carbohydrate intake. Lagiou et al26 reported that energy-adjusted carbohydrate intake was inversely related with weight gain in the first 27 weeks of pregnancy, whereas energy-adjusted protein and animal fat was directly related with weight gain. Similarly, Olafsdottir et al25 reported that overweight women with excessive GWG consumed a higher proportion of calories from fat and a lower proportion from carbohydrates. In our analysis, we found a trend toward greater excessive GWG with greater percent energy intake from protein, saturated fat, polyunsaturated fat, and trans fat, compared with equivalent percentage of energy intake from carbohydrates. Further studies are needed to explore the effect of macronutrient composition intake on GWG.
We found a lower risk of excessive weight gain among women who reported adhering to a vegetarian diet in early pregnancy. This finding is consistent with results among nonpregnant women in the Oxford arm of the European Prospective Investigation into Cancer and Nutrition cohort, in which the vegetarian diet was associated with lower BMI,34 and reduced weight gain over time,35 compared with meat-eating diets. Differences in macronutrient intake, or residual confounding by other health behaviors, may underlie these associations. In our cohort, however, this association persisted with adjustment for physical activity and intake of fried foods and dairy products.
Our findings regarding physical activity and GWG are consistent with earlier work. We found that vigorous activity during pregnancy, as well as walking and total activity, was associated with a lower risk of excessive GWG. Olson and Strawderman16 found that decreased physical activity during pregnancy was associated with excessive GWG. In a study of obese women with gestational diabetes, Artal et al36 found that exercise combined with diet led to lower weight gain than diet alone. In our cohort, Oken et al37 found that walking after delivery was also associated with a reduced risk of weight retention postpartum.
Most women can safely engage in physical activity during pregnancy, and current guidelines for uncomplicated pregnancies recommend 30 minutes per day of moderate physical activity on most days of the week. Nevertheless, most women reduce their physical activity during pregnancy.20 Encouraging women to continue or increase their activity during pregnancy may reduce their risk of excessive GWG.
Oken et al37 further found that postpartum television viewing was directly associated with postpartum weight retention. We found no association between television watching and excessive GWG or total weight gain during pregnancy; however, duration of television viewing during pregnancy was not associated with sedentary lifestyle in our cohort.
In conclusion, we found that total energy intake, dairy consumption, and fried food consumption were directly related to excessive GWG. Vegetarian diet, physical activity, and an active lifestyle were linked to a lower risk. Future intervention studies should target these behaviors to see whether beneficial changes influence weight gains and, in turn, improve maternal and child health outcomes.
Acknowledgment
We thank Sheyl Rifas-Shiman for technical support.
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Supported by Grants from the US National Institutes of Health (HD 34568, HL 68041), Harvard Medical School, and the Harvard Pilgrim Health Care Foundation.
Cite this article as: Stuebe AM, Oken E, Gillman MW. Associations of diet and physical activity during pregnancy with risk for excessive gestational weight gain. Am J Obstet Gynecol 2009;201:58.e1-8.
PII: S0002-9378(09)00216-6
doi:10.1016/j.ajog.2009.02.025
© 2009 Mosby, Inc. All rights reserved.
Volume 201, Issue 1 , Pages 58.e1-58.e8, July 2009
