In the United States, approximately two-thirds of childbearing age women are either overweight or obese (24). There is increased risk of adverse maternal and fetal health outcomes, such as gestational diabetes, gestational hypertension or preeclampsia, and labor/delivery complications among overweight and obese pregnant women (37). Excessive gestational weight gain (GWG) is another concern in the field of maternal and child health. Excessive GWG can be particularly concerning for overweight and obese women due to their already increased risk for adverse pregnancy outcomes. In addition, maternal obesity and GWG are two of the main causes of giving birth to large-for-gestational-age infants (birth weight ≥90th percentile) (19). The influence of maternal obesity on offspring obesity may be sustained into adulthood (35).
Healthy eating habits and regular physical activity (PA) are two modifiable targets in managing and preventing weight gain. These behaviors should be encouraged among pregnant women. In recent years, PA during pregnancy has been viewed as an important part of reproductive health. The risks of moderate-intensity PA (MPA) performed by healthy women during pregnancy are very low and do not appear to increase the risk of low birth weight, preterm delivery, or early miscarriage (7). In addition, observational studies have supported the role of PA in helping pregnant women to minimize excessive GWG (13,20,29).
According to the American College of Obstetrics and Gynecology 2002 guidelines, in the absence of either medical or obstetric complications, pregnant women are encouraged to accumulate 30 min or more of MPA on most, if not all days of the week (1). More recently, the U.S. Department of Health and Human Services issued the first-ever PA guidelines for Americans (PAG) in 2008, which included recommendations for healthy pregnant women and suggested a total of 150 min of MPA per week (spread throughout the week) during pregnancy (34). Despite these recommendations, the evidence of U.S. pregnant women meeting PA guidelines is low (9,10). According to NHANES 2003–2006 data, pregnant women only participated in an average of 12.0 ± 0.86 min·d−1 of MPA and 0.3 ± 0.08 min·d−1 of vigorous activity when their PA participation was objectively measured by an ActiGraph accelerometer (10). With the higher risk of adverse maternal and fetal health outcomes along with an increased possibility of gaining excessive weight during gestation, it is imperative that strategies to promote MPA during pregnancy be identified.
Walking is a common and popular PA choice during pregnancy because of its lower intensity and higher accessibility (15,22), and walking at a brisk pace has been shown to reduce the risk of gestational diabetes (38), preeclampsia (26), excessive GWG (29), and macrosomia (21). Few studies have investigated the use of walking among overweight and obese pregnant women as a strategy for meeting the PA recommendations during pregnancy. Therefore, we conducted a pilot randomized controlled trial (RCT) to evaluate the feasibility of increasing MPA participation of previously nonexercising, overweight, and obese pregnant women by walking. The objectives of this study were 1) to promote MPA participation among previously nonexercising, overweight, and obese pregnant women via walking; 2) and to evaluate the effect of the intervention on pregnancy and birth outcomes. The hypotheses of the current study were that previously nonexercising, overweight, and obese women could increase MPA participation during pregnancy via a walking intervention, and those who participated in the intervention would have more favorable pregnancy and birth outcomes.
The study was approved by the institutional review board of the Iowa State University. Recruitment for participants occurred through mass e-mail service provided by the Iowa State University to the students, staff, and faculty on campus, online advertisement (i.e., Craigslist), and flyers posted throughout the community (i.e., restaurants, public libraries, and grocery stores) as well as our partnership with local hospitals and obstetric clinics. Each participant was provided with an informed consent document for review, which was signed before participation. Mothers provided informed consent for each infant.
All participants were recruited before week 15 of gestation. Gestational age was calculated based on the self-reported date of the patients’ last normal menstrual cycle or medical provider ultrasound. Forty-six pregnant women enrolled in the study, and the final number of women who completed the study was 37 (n = 18 in intervention group and n = 19 in control group; Fig. 1). Participants met the following criteria: maternal age between 18 and 45 yr, singleton pregnancy, nonsmoker, self-reported overweight (body mass index [BMI] ≥ 25.0 kg·m−2) or obese (BMI ≥ 30.0 kg·m−2) before pregnancy, no prior history of chronic diseases (including type 1 diabetes, cardiovascular disease, thyroid, or lung disorder), and no prior history of gestational diabetes. In addition, only women who engaged in less than three 30-min bouts of leisure PA for 6 months preceding enrollment were recruited. Prepregnancy PA participation was self-reported, and leisure PA was defined as activities beyond normal daily routines.
During the enrollment, participants filled out a medical history questionnaire and provided their medical providers’ contact information. Height and weight of the women were measured by a trained staff member. All participants were approved by their medical providers to join the study. After the initial enrollment, participants were randomly assigned to the intervention or control group using a computer-based random number generator (Microsoft Excel 2010, WA). All participants and research staff were blinded to the group allocation. Group assignment was revealed to participants at the baseline data collection visit by the study coordinator. Anthropometric and objective PA data were collected for 1-wk periods at each of the following gestational time points: weeks 10–14 (V1, which served as baseline), weeks 17–19 (V2), weeks 27–29 (V3), and weeks 34–36 (V4) of gestation. All participants filled out a postpartum questionnaire regarding the infant’s delivery and birth outcomes.
Intervention: unsupervised walking program
The intervention in this study was an unsupervised walking program. Following V1, intervention group participants attended a training session. The instructions and safety of using a treadmill was discussed. Participants were verbally given the 2008 U.S. physical activity guidelines (accumulate a minimum of 150 min·wk−1 of moderate PA during pregnancy) and were advised to spread their walking throughout the week, such as 30 min of walking 5 d·wk−1 (1). Participants were also given permission to walk in shorter bouts; however, they were advised to keep the bouts to at least 10 min (36). Walking could occur in any setting, but treadmills were also provided for intervention women for home use during the study and were returned at the end of the walking program. Treadmills were provided to eliminate some of the prenatal PA barriers pregnant women faced such as lack of childcare support and weather-related concerns (8). A total of 16 treadmills were provided to women in the intervention group. Two women had their own treadmills at home; therefore, they requested not to be sent a treadmill. The treadmill manuals of these two participants were reviewed by the study coordinator to ensure user’s safety. Participants were provided with logs to report the location and duration of their walks. The intensity of walks was not reported by the participants. They were encouraged to turn in their logs at each time point visit. Participants in the control group were also given PA logs, which they were asked to report any leisure-time PA performed during pregnancy. However, because of the inconsistency, with PA logs returned at each time point visit, the self-reported leisure-time PA of the control group was not analyzed.
The unsupervised walking program began no earlier than week 12 and no later than week 15 of gestation and lasted until at least week 35. Depending on the length of each participant’s pregnancy, all the intervention participants were able to complete at least 20 wk. The first 2 wk of the intervention program served as an acclimation period whereby participants were asked to walk for 50 min in week 1, followed by 100 min in week 2. By the third week, all participants were encouraged to be at their walking goal of 30 min most days of the week for an overall total of at least 150 min of weekly MPA. Women in the control group were not provided with PA recommendations, but they were not restricted from PA participation during pregnancy.
Anthropometric and demographic data
Height was measured during enrollment, and weight was measured at each visit, with shoes removed and light clothing. Height was measured to the nearest 0.1 cm (Ayrton 226 Hite-Rite Precision Mechanical Stadiometer; Quick Medical GS, Snoqualmie, WA), and weight was measured to the nearest 0.1 kg (Detecto Model 6855 Cardinal Scale, Manufacturing Co., Webb City, MO). Prepregnancy BMI was determined by using height measured at enrollment and women’s self-reported weight before conception. Total GWG was calculated by subtracting weight measured at V4 from self-reported prepregnancy weight. This value was used to determine whether participants met the 2009 Institute of Medicine (IOM) recommendation after adjusting for their weeks of gestation at V4. The rate of GWG was determined by dividing the weight difference between two time points with the total weeks between the time points. Four different rates of GWG were calculated for the study: weight gain per week before baseline data collection at V1 (considered as the rate of weight gain before the intervention), weight gain per week between V1 and V2 (rate V1–V2), weight gain per week between V2 and V3 (rate V2–V3), and weight gain per week between V3 and V4 (rate V3–V4). Participants reported their age, education level, employment, race, marital status, income level, and parity. Infant birth weights and sex were obtained from the postpartum questionnaire. To maintain consistency, account for sex differences, and enable comparison of effect sizes, birth weights were adjusted to gestational age and sex-specific z-score (birth weight z-score) using U.S. reference data (18).
Objective PA data: StepWatch™ Activity Monitor
PA was monitored using the StepWatch™ Activity Monitor (SAM), an ankle-worn accelerometer-based measurement tool. A previous study has reported high accuracy and precision of SAM in measuring walking steps in lean and obese individuals (12). In the current study, it was worn on the ankle 24 h·d−1 for 1 wk. The SAM contains a microprocessor that uses a combination of acceleration, position, and timing to detect steps; therefore, the outputs of the SAM are based on the amount, rate, and pattern of walking. It is calibrated to the individual’s height. PA participation was determined using step data (counts) from the SAM. Instructions regarding the proper use (especially orientation) of the monitor were given to participants.
SAM measured step data in 1-min epochs (number of steps taken by the participants for each minute). The sample rate of the SAM is preset, and there are no options to change the sampling settings. Individual primary SAM files were examined visually by graphing the data to detect nonwear time. There is no known existing guideline to distinguish nonwear from wear time for SAM. Because time spent sitting and lying down does not produce steps, it was decided that data were excluded for a day if the participant did not wear the monitor (no steps or improper placement) for ≥300 consecutive minutes during typical waking hours (i.e., 7:00 a.m. to 10:00 p.m. for most participants). Step count data were collected during 24-h periods for seven consecutive days. In adults, at least 3 d of monitoring using accelerometry is required to provide a reliable estimation of habitual PA (30); therefore, at each time point, women who provided at least three valid days of step counts were included. The raw step data were smoothed using an exponential smoother (R: Moving averages, R Foundation for Statistical Computing, Vienna, Austria) to determine cadence (steps per minute) and bouts of walking among the participants. The weight used in the smoother formula was 1/10. The goal of smoothing was to help account for random stops (i.e., waiting at a stop light) during bouts of walking.
Meaningful walk determination
To determine the intensity of the walks, the number of steps taken per minute (cadence) was used. For a nonpregnant population, approximately 100 steps per minute equals a cadence of 3 METs of task with a walking range between 2.4 and 3 mph (32); however, this value was reported in laboratory conditions and was commonly measured using treadmills. It has been reported that the MET value of pregnant women (10–14 wk of gestation) who walked at 2 mph at 0% incline was 3.12 ± 0.32 METs (4). Therefore, in this study, a cadence ≥80 steps per minute was defined as moderate intensity walking for pregnant women under free-living conditions with the assumption that women might also walk outdoors (i.e., parks and walking trails). Accumulated short bouts of brisk walking can improve aerobic fitness and physiological outcomes and that these bouts should be continuous activities for ≥10 min in duration in the nonpregnant population (36). In addition to the use of cadence ≥80 steps per minute as the moderate activity cut point, slowing down from a walk and/or brief rest during a walk was accounted for; therefore, the definition of meaningful walk in this study would be any steps taken at moderately intense cadence (≥80 steps per minute) and must also be in bouts of at least 8 min. Using these definitions, meaningful walks include walking that should be counted toward meeting the PA guidelines, which include total time, bouts, and intensity.
All participants completed a postpartum questionnaire. The questionnaire included pregnancy risks and labor procedures (i.e., use of epidural and C-section delivery) as well as infant’s birth outcomes (sex, anthropometric data, and Apgar [appearance, pulse, grimace, activity, respiration] scores).
Demographic data were analyzed by descriptive analysis. Multivariate ANOVA was conducted to examine differences in demographic variables (age, height, prepregnancy weight, prepregnancy BMI, education, employment, race, marital status, total household income, and parity) between the groups. Two-way ANOVA was used to determine the differences in total steps per day (average steps per day), average minutes of meaningful walk (min·wk−1), total GWG (kg), birth weight (g), gestational length at delivery (wk), birth weight z-score, and Apgar score (min) by treatment group and prepregnancy BMI category. Absolute difference (diff) between groups was reported when there was significant difference. Pairwise comparison tests (all pairs Tukey–Kramer P = 0.05) were then performed to further determine the differences among overweight women in the intervention group (Int-OW), overweight women in the control group (Con-OW), obese women in the intervention group (Int-OB), and obese women in the control group (Con-OB) on the aforementioned variables. Fisher’s exact tests were used to analyze differences in meeting 2009 IOM GWG recommendations, pregnancy complications, and infant outcomes among Int-OW, Con-OW, Int-OB, and Con-OB women. All moderately intense cadences (≥80 steps per minute) taken by participants for any bout length at each time point were visualized graphically (Matlab, Mathworks, Natick, MA). The Kolmogorov–Smirnov test was used to compare the probability distribution of the bouts of moderately intense cadence between the intervention and the control groups by prepregnancy BMI category. A Pearson correlation coefficient analysis was also conducted to examine the association between prepregnancy BMI and rates of GWG at different time points across pregnancy. Significance was defined as P < 0.05. Results are presented as mean ± SD. Data analyses were conducted using JMP, Version 7 (SAS Institute Inc., Cary, NC).
Among the 46 overweight and obese women enrolled in the program, 9 of them dropped out due to schedule conflicts and non–study-related medical complication such as miscarriages (19.6% dropout rate) (Fig. 1). The characteristics of the remaining 37 participants are shown in Table 1 by treatment and BMI category. Multivariate ANOVA showed there were no significant differences between groups for age, height, gestational length at V1, education, employment, race, marital status, total household income, and parity. Prepregnancy weight and prepregnancy BMI were significantly different between overweight and obese participants. Overall, participants in the study were predominantly married, educated, and Caucasian.
Objectively Measured Step Counts Using StepWatch™
Participants in this study were compliant in wearing the PA monitor. The number of participants who provided at least three valid days of data at each gestational time point was V1 (n = 31), V2 (n = 36), V3 (n = 35), and V4 (n = 35). SAM data that were not included in the final analysis were mainly due to missing data and misplacement of the monitor. Participants’ files, which were included in the final PA analysis, had on average 6 d of data at each time point. Statistical analysis showed that there was no significant difference in participant’s compliance among the groups. The treadmills, both provided through the research program and owned by the participants, had a 33.8% usage according to the self-reported walking logs among women in the intervention group. Other reported locations of walks included outdoors, malls, and stores.
Walking amount: total steps per day
At V1 (baseline) and V2, there was no significant difference between the treatment groups, prepregnancy BMI category, or interaction effect in total steps per day (F = 1.049, P = 0.387 for V1; F = 0.834, P = 0.485 for V2). At V3, there was a significant difference between the prepregnancy BMI category (OW = 10,016 steps, OB = 7931 steps, diff = 2130 steps, P = 0.011), but not the treatment groups or interaction effect in total steps per day (F = 3.227, P = 0.036). Similar patterns were observed at V4 with significant difference between the prepregnancy BMI category (OW = 8703 steps, OB = 7036, diff = 1667, P = 0.025) but not the treatment groups or interaction effect in total steps per day (F = 2.519, P = 0.076). Pairwise comparison tests showed that only Int-OW versus Int-OB at V3 was significantly different, but not for other visits among the groups (Table 2).
Walking intensity: moderately intense cadence
The walking intensity characteristics of the women were determined using cadence (steps per minute). Cadence ≥80 steps per minute was considered a moderately intense cadence; therefore, any wear times that had ≥80 steps per minute were extracted. Figure 2 shows the length of time spent walking at cadence ≥80 steps per minute, shown by color intensity, separated into bouts of lengths given on the x-axis. This demonstrates the patterning of lengths of bouts of all women walking at moderate intensity achieved while under observation. At V1, the Kolmogorov–Smirnov test showed no significant difference between the distributions of cadence ≥80 steps per minute among the intervention and the control groups for obese women, but there was a trend of more moderate walking between intervention and control group for the overweight women (P = 0.062). At V2, there was a significantly higher amount of cadence ≥80 steps per minute in the intervention group for both overweight (P < 0.0001) and obese (P < 0.025) women. At V3, overweight women in the intervention group had significantly more cadence ≥80 steps per minute than the control group (P < 0.0001), and a trend of significance was observed among obese women (P = 0.072). At V4, there were significantly higher amounts of cadence ≥80 steps per minute in the intervention group for both overweight (P < 0.0001) and obese (P < 0.025) women. In addition, overweight women in the intervention group at V3 (P < 0.01) and V4 (P < 0.005) had a significantly higher amount of cadence ≥80 steps per minute than obese women in the same treatment.
Meaningful walks: moderately intense cadence for at least 8 min
Any moderately intense cadences taken for at least 8 min in length of bout were further extracted to identify the amount of time (minutes) participants spent in meaningful walks. In other words, any time spent walking at cadence ≥80 steps per minute after the 8-min mark on Figure 2 would be considered meaningful walks. Generally, there were higher percentages of overweight and obese women in the control group who had 0 min of meaningful walks across pregnancy (Table 2). When the average of minutes of meaningful walks was examined using a two-way ANOVA, there was no significant difference between the treatment groups, prepregnancy BMI category, or interaction effect at V1 (F = 0.954, P = 0.428). At V2, there were strong trends of significance between treatment groups (Int = 52.8 min, Con = 20.2 min, diff = 32.6, P = 0.054) and interaction effect (P = 0.066), but not prepregnancy BMI categories (F = 2.983, P = 0.046). At V3, significant differences were observed between the treatment groups (Int = 44.9 min, Con = 7.8 min, diff = 37.1 min, P = 0.01), prepregnancy BMI (OW = 45.8 min, OB = 6.9 min, diff = 38.9 min, P = 0.007), and interaction effect (P = 0.002) (F = 7.556, P < 0.001). At V4, treatment groups (Int = 42.1 min, Con = 6.7 min, diff = 35.4 min, P = 0.014) and prepregnancy BMI categories (OW = 41.7 min, OB = 7.1 min, diff = 34.6 min, P = 0.016) were significantly different, but there was no interaction effect (F = 5.341, P = 0.004). Table 2 shows the pairwise comparison tests for all groups of participants at each time point. Int-OW participants had significantly higher amounts (minutes) of meaningful walks compared with Con-OW participants at V2 (diff = 62.1 min, P = 0.046), V3 (diff = 78.1 min, P = 0.002), and V4 (diff = 65.1 min, P = 0.010).
Gestational weight gain
There was no significant difference in total GWG (F = 0.253, P = 0.859) among the women in the intervention group compared with women in the control group for both prepregnancy BMI categories (Table 3). However, it appeared that overweight women in the intervention group were more likely to gain within the 2009 IOM recommendations compared with the control group, according to the Fisher’s exact test (P = 0.163). Table 4 is a correlation matrix, which demonstrates the association between prepregnancy BMI and rates of GWG at different time points during pregnancy. The rate of GWG between V1 and V2 (rate V1–V2) was significantly correlated with the rate of weight gain before the women joined the study (r = 0.49, P < 0.01), rate V2–V3 was significantly correlated with rate V1–V2 (0.46, P < 0.01), rate V3–V4 was significantly correlated with rate V1–V2 (0.36, P < 0.05), and rate V2–V3 (0.47, P < 0.01).
Pregnancy Complications and Infant Outcomes
There were no significant differences in pregnancy complications and infant outcomes among groups (Table 3); however, lower birth weight z-scores and lower risk of macrosomia were observed among obese women who were in the intervention group compared with the control group according to pairwise comparison test (birth weight z-score: Int-OB = 0.46 ± 0.99, Con-OB = 1.09 ± 1.19, P = 0.239; macrosomia risk: Int-OB = 22.2%, Con-OB 55.6%, P = 0.335).
One of the hypotheses of the current study was that participation in the walking intervention would help previously nonexercising, overweight, and obese women to increase their MPA during pregnancy. The results showed that women in the intervention group were able to significantly increase their moderately intense walking cadence, especially among the overweight women. In fact, there were overweight women in the intervention group who met the minimum recommendation of 150 min·wk−1 of MPA (n = 2 at V2, n = 3 at V3, and n = 2 at V4); however, none of the overweight women in the control group met the recommendation. In addition, when at least 8-min bouts of walking were examined for meaningful walk, women in the intervention group had more minutes of meaningful walks than those in the control group. In comparison, more than 50% of the overweight and obese women in the control group had 0 min of meaningful walks across pregnancy. Perhaps, the current intervention was successful in helping pregnant women increased their MPA participation during pregnancy, particularly the overweight women. These women walked at a higher intensity and, most importantly, were able to sustain these habits until late pregnancy.
Overall, the amount of MPA engaged in by the overweight and obese women in the current intervention was substantially higher than other reported PA trends among pregnant and nonpregnant populations. When prenatal PA participation was objectively measured using an ActiGraph accelerometer in the NHANES 2003–2006 cross-sectional data (n = 359) (10), the results showed that pregnant women only participated in an average of 12.0 ± 0.86 min·d−1 of moderate activity and 0.3 ± 0.08 min·d−1 of vigorous activity. When a cadence of nonpregnant populations were examined by Tudor Locke et al. (31) using the 2005–2006 NHANES data (n = 1963 females), women only accumulated 12.78 min·d−1 of cadence ≥ 80 steps per minute. Furthermore, it has been well documented that PA participation decreases as pregnancy progresses (23). It was reported by Evenson and Wen (10) that U.S. pregnant women spent 11.5 min·d−1 during the first trimester, 14.3 min·d−1 during the second trimester, and 7.6 min·d−1 during the third trimester in moderate to vigorous PA. In the current study, overweight women in the intervention group successfully maintained their duration of moderately intense walking throughout pregnancy, even during the late third trimester.
We further hypothesized that those participants who increased their MPA participation via the walking intervention would have more favorable GWG outcomes. Overall, the total GWG between intervention and control groups for both overweight and obese women was not significantly different. When percentage of participants meeting 2009 IOM GWG guidelines was examined at V4, a greater proportion of overweight women in the intervention group gained within the recommendations, although it was not statistically significant. The findings of the present study are supported by a meta-analysis conducted by Streuling et al. (28), which evaluated trials that only involved increased PA as the means to minimize GWG. Twelve RCT were included in this analysis with interventions varying by intensity, duration, and mode of activity. Seven of the trials reported a trend for lowering GWG in the intervention group, one trial showed significant reductions in GWG, and five trials showed no significant effect on GWG. When all RCT were combined, the overall meta-analysis finding demonstrated that PA modification resulted in significant GWG reduction (mean difference = −0.61, 95% confidence interval = −1.17 to −0.06, P = 0.03). The walking program of the current study significantly increased the moderately intense steps of women in the intervention group, especially the overweight women, during pregnancy; therefore, the trend of a higher percentage of women in Int-OW group meeting the GWG guidelines may be partly explained by the increased MPA during pregnancy.
The present study also suggests a “cascade effect” of weight gain throughout pregnancy. The rate of GWG at any point during pregnancy was significantly influenced by the preceding rate of weight gain. In this study, weight gain after enrollment into the walking intervention was affected strongly by the weight already gained before the start of the intervention. This observed effect could be especially discouraging to investigators who hope to introduce lifestyle modifications during pregnancy to prevent excessive GWG. One such example is the NELIP study conducted by Mottola et al. (16), a personalized walking program to reach 30% peak HR reserve of the participant. This program began between 16 and 20 wk of gestation, and walking was performed three to four times a week (40 min per session). The results of this intervention showed that 80% of the participants did not exceed 2009 IOM recommendations on NELIP and their average total weight gain on NELIP was only 6.8 ± 4.1 kg. Unfortunately, many women had gained excessive weight before they joined the program; therefore, their average total weight gain was 12.0 ± 5.7 kg, which exceeded the total GWG range recommended by IOM for both overweight and obese women.
Our final hypothesis was that those participants who increased their MPA participation via the walking intervention would have more favorable birth outcomes. The walking program in this study did not cause any adverse effects on labor/delivery complications and birth outcomes. In fact, there was a trend for obese women who participated in the walking program to have lower infant birth weight z-scores and decreased odds of fetal macrosomia compared with obese women in the control group. More recently, evidence shows that maternal PA helped reduce the risk of giving birth to large-for-gestational-age infants by not increasing the odds for an SGA infant (17). Thus, because the obese women in the intervention group significantly increased their moderately intense walking, the increase in favorable child outcomes may be due partly to the increase in MPA.
Little information is available about the feasibility and benefits of previously nonexercising overweight and obese pregnant women increasing their MPA via walking. Different from the NELIP study, the present intervention was a randomized controlled trial, and it was an unsupervised PA-only intervention. Diet counseling was not provided nor was caloric restriction emphasized in the study. Any positive maternal and child health outcomes observed in the study would be primarily attributed to the increased PA participation during pregnancy. Therefore, this intervention added unique contributions in the field of maternal and child health. This study objectively measured walking of pregnant women to evaluate MPA participation and patterns during pregnancy. Because walking is the most common activity practiced among pregnant women, being able to objectively measure step counts and use the cadence to determine activity intensity could provide further insight into the relationship between MPA participation during pregnancy and health outcomes of the mother and fetus. Studies reported the use of SAM for measuring walking in various populations (3,11,27); however, to the best of our knowledge, no study has reported the use of SAM among pregnant population. In recent years, the use of cadence in intervention and behavioral research has been promoted due to its easily interpretable results (33). Thus, SAM is an ideal research pedometer for pregnant population as it could provide step data in the form of cadence. In addition, the placement of SAM is on the ankle and pedometer tilt is minimized with the growing stomach among pregnant women using this device (5). Also, the current intervention was an unsupervised, free-living walking program. The women were provided with a treadmill for home use. Thus far, most successful interventions that have targeted overweight and obese pregnant women consist of fully or partially supervised activities (2,6,16). This type of intervention required trained staff members to supervise the workout sessions, which can be expensive, labor intensive, and time consuming. With positive results observed through our pilot study, a treadmill could be a relatively cost-effective intervention tool to help pregnant women to increase their PA to meet the current recommendations. Despite a low usage (33.8%) of the treadmill, by having a treadmill at home may have increased the participant’s self-efficacy to overcoming barriers, for instance lack of childcare support or weather-related concerns, during pregnancy to be physically active (14).
It is acknowledged that the present pilot study has some limitations. The study had a small sample size and high variability among the groups. These factors could potentially reduce the ability to detect statistically significant effects of the intervention. Second, there is no known study that has been conducted to measure the walking cadence/intensity of the pregnant population. As a result, the present study used the evidence in the literature to define the moderately intense cadence for pregnant women, which was a cadence ≥80 steps per minute of the participants. Further research in this area is needed. Third, self-reported prepregnancy BMI was used in the study, which could lead to inaccurate data because evidence has shown that overweight women are more likely to underreport their weight compared with normal or underweight women (25). Lastly, the StepWatch™ monitor may not have accounted for other activities the women participated in during the intervention period, such as running, biking, or swimming. Considering that the intervention was focused on walking, the StepWatch™ monitor was viewed as an acceptable measurement tool for quantifying the intervention effect.
In conclusion, this pilot unsupervised walking program significantly increased MPA among pregnant women, especially overweight women via walking to meet the current maternal PA recommendations. There was a nonsignificant trend for women in the intervention group to have more favorable pregnancy and birth outcomes compared with the control group. The findings of the present study provide important preliminary results in understanding walking patterns during pregnancy and health outcomes of mother and baby. Because the study of the relationship between cadence and one’s free-living patterns of ambulatory activity is a new and innovative area, future research is needed to examine the relationship between mother’s cadence intensity and pregnancy outcomes.
The authors sincerely thank all of the intervention participants and all of the individuals who helped to collect the data in Dr. Lorraine Lanningham-Foster and Dr. Christina Campbell’s laboratories. All of the data of this study were collected at the Nutritional and Wellness Research Center of Iowa State University.
The study was funded by the Department of Food Science and Human Nutrition and the Nutritional and Wellness Research Center of Iowa State University.
The authors report no conflict of interest.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
1. ACOG Committee Obstetric Practice. ACOG committee opinion: exercise during pregnancy and the postpartum period. Obstet Gynecol
. 2002; 99 (1): 171–3.
2. Artal R, Catanzaro RB, Gavard JA, Mostello DJ, Friganza JC. A lifestyle intervention of weight-gain restriction: diet and exercise in obese women with gestational diabetes mellitus. Appl Physiol Nutr Metab
. 2007; 32 (3): 596–601.
3. Bergman RJ, Bassett DR, Klein DA. Validity of 2 devices for measuring steps taken by older adults in assisted-living facilities. J Phys Act Health
. 2008; 5 (1 Suppl): S166–75.
4. Campbell CG, Foster RC, Lanningham-Foster LM, Smith KM. The modified obstetric metabolic equivalent (MET): finding a MET that fits in pregnancy. J Dev Orig Health Dis
. 2012; 3 (3): 159–65.
5. Connolly CP, Coe DP, Kendrick JM, Bassett DR, Thompson DL. Accuracy of physical activity monitors in pregnant women. Med Sci Sports Exerc
. 2011; 43 (6): 1100–5.
6. Davenport MH, Mottola MF, McManus R, Gratton R. A walking intervention improves capillary glucose control in women with gestational diabetes mellitus: a pilot study. Appl Physiol Nutr Metab
. 2008; 33 (3): 511–7.
7. Downs DS, Chasan-Taber L, Evenson KR, Leiferman J, Yeo S. Physical activity and pregnancy: past and present evidence and future recommendations. Res Q Exerc Sport
. 2012; 83 (4): 485–502.
8. Evenson KR, Moos M-K, Carrier K, Siega-Riz AM. Perceived barriers to physical activity among pregnant women. Matern Child Health J
. 2009; 13 (3): 364–75.
9. Evenson KR, Wen F. National trends in self-reported physical activity and sedentary behaviors among pregnant women: NHANES 1999–2006. Prev Med
. 2010; 50 (3): 123–8.
10. Evenson KR, Wen F. Prevalence and correlates of objectively measured physical activity and sedentary behavior among US pregnant women. Prev Med
. 2011; 53 (1–2): 39–43.
11. Feito Y, Bassett DR, Thompson DL. Evaluation of activity monitors in controlled and free-living environments. Med Sci Sports Exerc
. 2011; 44 (4): 733–41.
12. Foster RC, Lanningham-Foster LM, Manohar C, et al. Precision and accuracy of an ankle-worn accelerometer-based pedometer in step counting and energy expenditure. Prev Med
. 2005; 41 (3–4): 778–83.
13. Haakstad LAH, Voldner N, Henriksen T, Bø K. Physical activity level and weight gain in a cohort of pregnant Norwegian women. Acta Obstet Gynecol Scand
. 2007; 86 (5): 559–64.
14. Kong K. Early Prevention of Childhood Obesity: Impact of Maternal Physical Activity on Pregnancy and Child Outcomes
. Ames (IA): Iowa State University; 2013.
15. Mottola MF, Campbell MK. Activity patterns during pregnancy. Can J Appl Physiol
. 2003; 28 (4): 642–53.
16. Mottola MF, Giroux I, Gratton R, et al. Nutrition and exercise prevent excess weight gain in overweight pregnant women. Med Sci Sports Exerc
. 2010; 42 (2): 265–72.
17. Mudd LM, Pivarnik J, Holzman CB, Paneth N, Pfeiffer K, Chung H. Leisure-time physical activity in pregnancy and the birth weight distribution: where is the effect? J Phys Act Health
. 2012; 9 (8): 1168–77.
19. Oken E. Maternal and child obesity: the causal link. Obstet Gynecol Clin North Am
. 2009; 36 (2): 361–77.
20. Olson CM, Strawderman MS. Modifiable behavioral factors in a biopsychosocial model predict inadequate and excessive gestational weight gain. J Am Diet Assoc
. 2003; 103 (1): 48–54.
21. Owe K, Nystad W, Bo K. Association between regular exercise and excessive newborn birth weight. Obstet Gynecol
. 2009; 114 (4): 770–6.
22. Pereira MA, Rifas-Shiman SL, Kleinman KP, Rich-Edwards JW, Peterson KE, Gillman MW. Predictors of change in physical activity during and after pregnancy: Project Viva. Am J Prev Med
. 2007; 32 (4): 312–9.
23. Poudevigne S, Connor PJO. A review of physical activity patterns in pregnant women and their relationship to psychologial health. Sports Med
. 2006; 36 (1): 19–38.
24. Rasmussen K, Yaktine A, editors. Weight Gain During Pregnancy: Reexamining the Guidelines
. Washington (DC): Institute of Medicine and National Research Council; 2009.
25. Rowland ML. Self-reported and height. Am J Clin Nutr
. 1990; 52 (6): 1125–33.
26. Saftlas AF, Logsden-Sackett N, Wang W, Woolson R, Bracken MB. Work, leisure-time physical activity, and risk of preeclampsia and gestational hypertension. Am J Epidemiol
. 2004; 160 (8): 758–65.
27. Song KM, Bjornson KF, Cappello T, Coleman K. Use of the StepWatch Activity Monitor for characterization of normal activity levels of children. J Pediatr Orthop
. 2006; 26 (2): 245–9.
28. Streuling I, Beyerlein A, Rosenfeld E, Hofmann H, Schulz T, Von Kries R. Physical activity and gestational weight gain: a meta-analysis of intervention trials. BJOG
. 2011; 118 (3): 278–84.
29. 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 (1):58. e1–8.
30. Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc
. 2005; 37 (11 suppl): S531–43.
31. Tudor-Locke C, Camhi SM, Leonardi C, et al. Patterns of adult stepping cadence in the 2005–2006 NHANES. Prev Med
. 2011; 53 (3): 178–81.
32. Tudor-Locke C, Craig CL, Brown WJ, et al. How many steps/day are enough? For adults. Int J Behav Nutr Phys Act
. 2011; 8 (79): 1–17.
33. Tudor-Locke C, Rowe DA. Using cadence to study free-living ambulatory behaviour. Sports Med
. 2012; 42 (5): 381–98.
34. U.S. Department of Health and Human Services. Physical activity guidelines advisory committee report, 2008. To the Secretary of Health and Human Services. Part A: executive summary. Nutr Rev
. 2009; 67 (2): 114–20.
35. Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH. Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med
. 1997; 337 (13): 869–73.
36. Woolf-May K, Kearney EM, Owen A, Jones DW, Davison RC, Bird SR. The efficacy of accumulated short bouts versus single daily bouts of brisk walking in improving aerobic fitness and blood lipid profiles. Health Educ Res
. 1999; 14 (6): 803–15.
37. Yogev Y, Catalano P. Pregnancy and obesity. Obstet Gynecol Clin North Am
. 2009; 36 (2): 285–300.
38. Zhang C, Solomon CG, Manson JE, Hu FB. A prospective study of pregravid physical activity and sedentary behaviors in relation to the risk for gestational diabetes mellitus. Arch Intern Med
2006; 166 (5): 543–8.