Next Article in Journal
Normal Alpha-Fetoprotein Hepatocellular Carcinoma: Are They Really Normal?
Next Article in Special Issue
Health in Preconception, Pregnancy and Postpartum Global Alliance: International Network Preconception Research Priorities for the Prevention of Maternal Obesity and Related Pregnancy and Long-Term Complications
Previous Article in Journal
Medication-Taking Habit and Outcome of Glucosamine Sulfate for Osteoarthritis Patients Influenced by National Health Insurance Regulations in Taiwan
Previous Article in Special Issue
Vaginal Birth after Cesarean Section in Taiwan: A Population-Based Study

J. Clin. Med. 2019, 8(10), 1735; https://doi.org/10.3390/jcm8101735

Article
Associations between Prenatal Physical Activity and Neonatal and Obstetric Outcomes—A Secondary Analysis of the Cluster-Randomized GeliS Trial
1
Else Kröner-Fresenius-Centre for Nutritional Medicine, Klinikum rechts der Isar, Technical University of Munich, Georg-Brauchle-Ring 62, 80992 Munich, Germany
2
Competence Centre for Nutrition (KErn), Am Gereuth 4, 85354 Freising, Germany
*
Author to whom correspondence should be addressed.
Received: 11 September 2019 / Accepted: 15 October 2019 / Published: 19 October 2019

Abstract

:
Prenatal physical activity (PA) was discussed to decrease the incidence of obstetric and neonatal complications. In this secondary cohort analysis of the cluster-randomized GeliS (“healthy living in pregnancy”) trial, associations between prenatal PA and such outcomes were investigated. PA behavior was assessed twice, before or during the 12th week (baseline, T0) and after the 29th week of gestation (T1), using the self-reported Pregnancy Physical Activity Questionnaire. Obstetric and neonatal data were collected in the routine care setting. Data were available for 87.2% (n = 1994/2286) of participants. Significant differences between the offspring of women who adhered to PA recommendations at T1 and offspring of inactive women were found in birth weight (p = 0.030) but not in other anthropometric parameters. Sedentary behavior was inversely associated with birth weight at T1 (p = 0.026) and, at both time points, with an increase in the odds of low birth weight (T0: p = 0.004, T1: p = 0.005). Light-intensity PA at T0 marginally increased the odds of caesarean section (p = 0.032), but neither moderate-intensity nor vigorous-intensity activity modified the risk for caesarean delivery at any time point. The present analyses demonstrated associations between prenatal PA and some neonatal and obstetric outcomes.
Keywords:
physical activity; exercise; lifestyle intervention; pregnancy; neonatal outcomes; obstetric outcomes; obesity prevention; routine care; birth weight; large for gestational age

1. Introduction

Worldwide, more than 41 million children under 5 years of age are affected by childhood obesity and being overweight, which poses one of the major challenges of the 21st century [1]. Research suggests that babies born with specific anthropometric characteristics are more susceptible to childhood obesity and to an increased risk of obesity later in life [2]. For example, neonatal outcomes such as high birth weight (>4000 g) and being born large for gestational age (LGA; >90th percentile for gestational age) were shown to be early markers for an increased obesity risk in infancy [3,4].
A healthy lifestyle during pregnancy is discussed to enhance the maternal health status, positively impact fetal development, and improve neonatal as well as obstetric outcomes [5,6]. Within the last few years, approaches focusing on the prenatal lifestyle of the mother-to-be have been initiated to avoid an early obesogenic environment in utero. Lifestyle interventions frequently target a modification of the maternal diet and/or physical activity (PA) behavior [7]. However, the role of PA in the prevention of adverse neonatal and obstetric complications is controversially discussed. While some reported PA to lower the risk for LGA and high birth weight [8,9], others suggested positive associations between PA and birth weight dependent on the PA intensity [10]. Moreover, the effect of prenatal PA on the risk for preterm and caesarean delivery is highly debated, as some analyses showed beneficial associations between prenatal PA and the risk of preterm birth and cesarean section, while others did not demonstrate any effects of prenatal PA on gestational age at birth or mode of delivery [11,12,13,14,15]. Thus, evidence is still inconclusive. The activity mode, time point during pregnancy, and intensity seem to be particularly important in this heterogeneous picture on the effect of PA on neonatal and obstetric parameters. Nevertheless, no negative effects of prenatal PA on obstetric or neonatal outcomes have been found so far.
In order to encourage expectant mothers to engage in adequate levels and intensity of PA, the American College of Obstetricians and Gynecologists (ACOG) established recommendations in the report “Physical Activity and Exercise During Pregnancy and the Postpartum Period” [16]. These recommendations have been adapted for Germany [17]. The key message of these recommendations is that pregnant women without contraindications should not stop exercising during the course of pregnancy. In the absence of medical or obstetric complications, pregnant women are recommended to engage in moderate-intensity PA for at least 20–30 min per day on most or all days of the week [16,17].
In Bavaria, Germany, the large-scale “Gesund leben in der Schwangerschaft”/ “Healthy living in pregnancy” (GeliS) trial was initiated offering a lifestyle intervention program that is linked to routine prenatal care [18]. The GeliS trial sought to improve maternal and neonatal health outcomes as well as obstetric parameters in order to positively influence the long-term health development of both mothers and infants. The primary objective of the GeliS trial was to reduce the proportion of women with excessive gestational weight gain. The GeliS intervention was not successful in reducing the incidence of excessive gestational weight gain [19]. However, it led to some improvements in maternal antenatal dietary [20], and PA behavior [21]. Moreover, some minor but likely clinically irrelevant benefits in maternal postpartum weight development and breastfeeding behavior were observed [22].
The present work aims to investigate associations between early and late prenatal PA behavior and neonatal and obstetric parameters in the entire GeliS cohort. Moreover, we sought to describe differences in neonatal and obstetric outcomes between women meeting or not meeting the PA recommendations given by the ACOG.

2. Materials and Methods

2.1. The GeliS Study

The GeliS study is a prospective, multicenter, cluster-randomized, controlled, open intervention trial that was conducted alongside routine prenatal care with the aim to improve prenatal weight development and reduce the risk for adverse maternal and infant health outcomes. A detailed description of the study design, setting, population, and randomization has already been published elsewhere [18]. In brief, between 2013 and 2015, women with (1) a pre-pregnancy body mass index (BMI) between ≥ 18.5 kg/m2 and ≤ 40.0 kg/m2, (2) a singleton pregnancy, (3) age between 18 and 43 years, (4) sufficient German language skills, and (5) stage of pregnancy before the end of the 12th week of gestation were recruited by gynecological and midwifery practices in five administrative regions of Bavaria depicting the “real-life” setting of routine prenatal care. Written informed consent for participation was given by all participants.
Apart from routine prenatal care, participants of the control group (C) obtained only general information on a healthy antenatal lifestyle via a flyer. Participants of the intervention group (IV) additionally received a comprehensive lifestyle intervention program consisting of three antenatal counselling sessions and one postpartum face-to-face counselling session given by previously trained midwives, medical personnel, or gynecologists. Within these sessions, the importance of a healthy prenatal and postnatal lifestyle was addressed and practice-oriented advice was given in accordance with national and international recommendations [16,17]. A detailed description of the counselling content has already been reported [18].
The study was performed in accordance with the current local regulatory requirements and laws as well as with the declaration of Helsinki. The Ethics Commission of the Technical University of Munich approved the study protocol. The trial is registered at the ClinicalTrials.gov Protocol Registration System (NCT01958307) [23].
The intervention yielded some improvements in the PA behavior [21] but no major between-group differences in primary and secondary maternal, neonatal, and obstetric outcomes except for infants’ birth weight and height [19]. Therefore, we made the post-hoc decision to pool data from the IV and C for the present analysis and adjusted for the group assignment.

2.2. Data Collection and Outcomes

At the time of recruitment (before the end of the 12th week of gestation), all baseline characteristics were collected through a screening questionnaire. Pre-pregnancy BMI was calculated based on self-reported weight. Infant anthropometrics, including neonatal and obstetric parameters, were retrieved from maternity and birth records. Preterm birth was defined as delivery before the 37th week of gestation. Newborn’s birth weight below 2500 g was described as “low birth weight,” above 4000 g as “high birth weight” and above 4500 g as “macrosomic.” Offspring whose weight was above the 90th percentile for gestational age was defined as “large for gestational age” (LGA) and whose weight was below the 10th percentile for gestational age as “small for gestational age” (SGA). BMI-z-scores were calculated on the basis of the German reference group, according to Kromeyer-Hauschild et al. (2001) [24].
Prenatal PA behavior was assessed twice, at T0 (before or in the 12th week of gestation) and at T1 (after the 29th week of gestation), using the validated Pregnancy Physical Activity Questionnaire (PPAQ) [25], which was slightly adapted to German habits. Data were self-reported without supervision. In the PPAQ, participants were asked to estimate the mean time spent engaging in 32 activities in the past month. In two included open-ended questions, participants were able to name activities that were not specifically listed in the PPAQ.
For the analyses of the PPAQ data, we made use of the widely applied concept of a metabolic equivalent of task (MET), which is a procedure to express energy costs of PA as multiples of the resting metabolic rate [26,27]. One MET equals the resting metabolic rate during sitting [26]. The 2011 Compendium of Physical Activities lists MET values for different types of sports and, thus, activity-specific multiples of the resting metabolic rate [28]. Moreover, the PPAQ evaluation instruction indicates MET values for activities that are assessed in the PPAQ [29].
PPAQ data were processed to receive a measure of average weekly energy expenditure in MET-h/week by multiplying the number of hours spent in each activity by its corresponding intensity (MET). Corresponding MET values were retrieved from the evaluation instruction of the PPAQ [29]. Using the 2011 Compendium of Physical Activities [28], the corresponding MET values were assigned to reported activities in open-ended questions. As described by the authors [29], calculated average weekly energy expenditure was grouped into activity “types” and activity “intensities” or summed up into “total PA” and “total PA of light intensity and above” (TALIA). Types included the categories “household/caregiving”, “transportation”, and “occupational activities”, as well as “sport/exercise” and “inactivity”. Intensities were sub-grouped into “sedentary” (MET < 1.5), “light” (MET ≥ 1.5 and < 3.0), “moderate” (MET ≥ 3.0 and ≤ 6.0), or “vigorous” activities (MET > 6.0). As done by others [7], questionnaires were excluded from the analysis due to over-reporting if the total number of reported hours exceeded the total number of hours per week. Moreover, if participants indicated to have spent more than 12 hours per day for seven days per week in occupational activity, they were defined as an over-reporter for this specific category and not considered in “occupational activity” analyses. To obtain a dichotomized variable indicating whether women met the national and international PA recommendations [16,17], the threshold of ≥ 7.5 MET-h/week in sport activities of moderate intensity or above was used. This procedure was recommended by the PPAQ developer (personal communication) and was applied by others [30]. Women with a level of ≥ 7.5 MET-h/week in sport activities of moderate-intensity or above, thus, meeting the recommendations at one time point (T0 or T1), were defined as “active”, whereas the “inactive” group was characterized by values below this threshold at one time point. In sub-analyses, women meeting the recommendations at both time points were named “activeT0+T1” and women meeting the recommendations never or only at one time point were described as “inactiveT0+T1”.

2.3. Statistical Analysis

Power calculation was based on the primary study outcome and has been described elsewhere [18]. All presented analyses were performed using SPSS software (IBM SPSS Statistics for Windows, version 24.0, IBM Corp, Armonk, NY, USA). The subsequent analyses included all participants except for the ones that either dropped out before delivery due to miscarriage or late loss of pregnancy, terminations, pregnancy complications interfering with the intervention, and maternal deaths or the ones that did not provide any of the three infant parameters: birth weight, birth length, and head circumference. Moreover, participants were excluded from the analysis of single PA intensities or types if one corresponding question was not answered.
Baseline characteristics, infant anthropometrics, obstetric, and neonatal outcomes are presented as proportions or as mean ± standard deviation (SD) if appropriate. PA behavior of active and inactive participants is characterized by type and intensity of PA and is presented in mean MET-h/week ± SD. To assess differences in anthropometric, neonatal, and obstetric outcomes between active and inactive or activeT0+T1 and inactiveT0+T1 women, respectively, general linear regression models were applied for continuous variables and binary logistic regression models for dichotomized outcomes. Thereby, unadjusted as well as adjusted models were performed controlling for the pre-pregnancy BMI category, parity, age, and group assignment. Similarly, linear and binary logistic regression models were used to explore potential associations of a change in PA intensities and TALIA by 10 MET-h/week with obstetric and neonatal outcomes adjusting for the same confounding factors. p-values below 0.05 were considered to be statistically significant.

3. Results

3.1. Participant Flow and Baseline Characteristics

A total of 2286 women were enrolled in the GeliS study (Figure 1). Among them, n = 112 participants dropped out during the course of pregnancy and, for n = 156 participants, the minimum of infant outcomes was not available. Thus, 2018 women were eligible for analysis of whom n = 24 provided neither PA data at T0 nor at T1, resulting in n = 1994 women with PA data at either one or both time points. After the exclusion of over-reporters, n = 1904 valid questionnaires were available at T0 and n = 1890 questionnaires at T1.
Maternal characteristics, obstetric outcomes, and corresponding neonatal parameters of all eligible subjects are depicted in Table 1.

3.2. Associations Between Prenatal Physical Activity and Infant Anthropometrics, Neonatal, and Obstetric Outcomes

Among all women providing valid PA data, 47.0% met the PA recommendations at T0 and 56.2% at T1. Among participants providing valid data for both time points, 597 (33.1%) women met the recommendations at both time points. Obstetric parameters as well as corresponding anthropometrics and neonatal outcomes of offspring of women considered active and inactive at T0 and T1 are shown in Table 2. Results of unadjusted analyses are shown in Table S1. There was evidence that infants of women who were active in late pregnancy (T1) had a higher birth weight (3364.5 ± 481.0 g) than infants whose mothers were inactive at T1 (3341.4 ± 492.5 g, adjusted effect size 49.74, 95% CI 4.94 to 94.53, p = 0.030). No significant differences in other anthropometric parameters such as length, BMI, head circumference, or BMI-z-score were detected either at T0 or at T1. In the adjusted analysis, preterm birth was less likely among women who were active at T1 compared to women who were inactive (adjusted OR 0.66, 95% CI 0.44 to 0.98, p = 0.038).
The odds of LGA tended to be higher at both time points for offspring of women adhering to the PA recommendations (T0: adjusted OR 1.37, 95% CI 0.96 to 1.94, p = 0.079, T1: adjusted OR 1.39, 95% CI 0.97 to 2.00, p = 0.075), but statistical evidence was lacking. No significant differences between active and inactive women were observed in other neonatal and obstetric outcomes at any time, neither in the unadjusted (Table S1) nor in the adjusted analysis (Table 2).
We found evidence that infants of women who adhered to PA recommendations at both time points (activeT0+T1) were more likely of being born LGA when compared to infants of women who either met the recommendations once or at no time point (Table S2, adjusted p = 0.025). Moreover, these infants showed, by trend, an increased risk for high birth weight (Table S2, adjusted p = 0.095), but statistical evidence was lacking.
Table 3 shows the effect of different PA intensities on infant anthropometrics as well as obstetric outcomes and Table 4 on neonatal outcomes. Corresponding unadjusted models are presented in the supplement (Table S3 and Table S4). The level of sedentary PA in late pregnancy was significantly and inversely associated with infant birth weight (Table 3, adjusted p = 0.026) and positively associated with the odds of low birth weight at both time points (Table 4, T0: adjusted p = 0.004, T1: adjusted p = 0.005). Moreover, the level of sedentary-intensity was, by trend, associated with increasing odds of preterm birth at T0 and T1 (Table 3, T0: adjusted p = 0.051, T1: adjusted p = 0.070) like vigorous activity at T1 (Table 3, adjusted p = 0.081), but there was no statistically significant evidence for these findings. The level of TALIA and light-intensity activities at T0 was related to a marginal increase in the odds of caesarean section (Table 3, TALIA: adjusted p = 0.040, light-intensity PA: adjusted p = 0.032).
The level of moderate-intensity activity at both time points was, by trend, positively associated with the odds of high birth weight (Table 4, T0: adjusted p = 0.080, T1: adjusted p = 0.050). The level of light-intensity activities at T0 seemed to be linked to decreasing odds of SGA (Table 4, adjusted p = 0.053). However, none of these trends were statistically significant.

4. Discussion

In this secondary analysis of the GeliS cohort, we were able to show associations between early and late prenatal PA and infant anthropometrics as well as several neonatal and obstetric outcomes. Moreover, we could comprehensively investigate the influence of differences in the PA behavior between women who met and did not meet the prenatal PA recommendations on these outcomes. Lastly, we could associate different PA intensities with infant anthropometrics and the risk of adverse neonatal and obstetric outcomes.
Infants of women meeting the PA recommendations in late pregnancy were born significantly heavier and tended to be larger than offspring of inactive women. However, the estimated differences between groups were small. We observed that late sedentary PA was inversely associated with birth weight and positively associated with the risk of low birth weight but not for SGA. Engaging in light-intensity activities in early pregnancy was associated with a decreasing risk of the offspring to be born SGA. Our findings on infant birth weight correspond to the results of Koushkie Jahromi et al. [31] and Badon et al. [32] who, likewise, reported that babies born to women who exercised during pregnancy were heavier than those born to non-exercising women [31] with no impact of early sedentary behavior on birth weight [32]. However, our results contrast the observations of Bisson et al. [33] who also used the PPAQ to explore effects of PA on infant birth weight in a Canadian cohort. Although study samples seemed to be comparable in terms of BMI, educational level, and parity, these authors observed a reduction in infant birth weight by 2.5 g with each increase of 1 MET-h/week in the level of sports and exercise [33]. A possible explanation for the discrepancy with our results might be that the authors included more covariates in their model such as maternal education and smoking status, paternal weight, and infant sex, among others.
In general, the opinion about the effect of prenatal PA on infant birth weight is conflicting. Some studies report no significant association [14,34,35,36], while others report a positive [31,37] or a negative association [38,39]. The considerable heterogeneity in the assessment of PA data complicates the comparison of study results. Furthermore, inconsistency of results may arise from differences in type, frequency, timing, and duration of PA [40]. There is some evidence suggesting an inverted U-shaped relationship between PA intensity and birth weight [10]. Although this hypothesis has been criticized [9], it provides a possible explanation for our observations and seems to explain why we found late sedentary-intensity to be inversely associated with birth weight and positively associated with the risk for a low birth weight, while moderate-intensity PA in early and late pregnancy appeared to be linked to a slight increase in the odds of high birth weight. Bisson et al. [10] explain this relationship by alterations in glucose availability and uteroplacental blood flow in response to exercise [41], which seems to be reduced by exercise intensity [42,43] and compensated afterward, resulting in enhanced fetal growth. A comprehensive estimation of the influence of PA on neonatal body composition might elucidate the debate on its effect on birth weight [35].
In our cohort, infants of active women at T0 and T1 tended to be at higher risk for being born LGA. This observation was shown to be significant in women meeting the recommendations in early as well as in late pregnancy. However, it is difficult to explain this finding since we could not identify any PA intensity during the course of pregnancy, which was associated with an increasing risk of LGA. Current research has either found no influence of PA on the incidence of LGA [12], or observed PA to be protective against LGA [8,40,44], which calls into question whether our observations were chance findings.
Our results showed that women who were active in late pregnancy were less likely to give birth prematurely, which was similarly observed by others [45]. Likewise, we identified sedentary PA in early and late pregnancy to be, by trend, associated with an increase in the odds of preterm delivery, even though statistical evidence was lacking. These observations are in line with some investigations showing either no effect of PA on the risk for preterm birth [12,13,46], or a protective influence [47]. However, we observed that vigorous-intensity PA in late pregnancy appeared to be linked to an increasing risk for preterm birth. This is in contrast with observations from a prospective study [48], a systematic review [49], and a meta-analysis [11], which showed that higher leisure-time and vigorous PA did not change the incidence of, or reduce the risk for preterm deliveries. Nevertheless, the impact of prenatal PA on pregnancy duration was studied in women with different weight classifications, which might explain inconsistencies with our results since not all trials included women with normal and overweight outcomes simultaneously.
In the present analyses, we found no difference in the incidence of caesarean delivery between active and inactive women during the course of pregnancy. This corresponds to other current investigations [13,36,50] even though some studies observed a lower caesarean section rate in exercising women [8,14,46]. However, we observed that TALIA and light-intensity PA in early pregnancy were associated with a marginal increase in the odds of caesarean delivery. Poyatos-Léon et al. [15], likewise, assessed the association between PA intensities and the risk for caesarean section deliveries and provided a possible extension of our findings. They concluded that, in general, exercise during pregnancy appears to decrease the risk of caesarean delivery. In particular, women who engaged in exercise during the second and third trimester seemed to increase their likelihood of a normal delivery [15].
This secondary analysis of the GeliS trial has some limitations. As noted by others [40], we did not include dietary intake as a covariate. Previously, we reported small effects of the maternal diet on neonatal weight-related parameters [51], and are aware that maternal dietary behavior might have biased the present results. Further potential confounders such as the maternal employment, living circumstances, or other lifestyle factors (smoking, drinking) might have influenced the maternal PA level, but were not considered in the present analyses. Moreover, we used a self-administered PPAQ, which, although a being validated and easily applicable tool, was filled out by participants at both time points without supervision or accompanying interview. Self-reports rely on the subjective estimation of participants who had to remember their PA level and type of performed sports for the past four weeks. As reported by others [52], the presented self-reported data might have been susceptible to over-reporting and under-reporting. Despite our efforts to exclude over-reporting, this mode of PPAQ self-administration might have biased our results. While done by others [30] and recommended by the questionnaire developers (personal communication), assessing the adherence to the PA recommendations by means of the PPAQ might present a methodological shortcoming and might explain some inaccuracies with observed effects of PA intensities. We acknowledge that objectively measuring prenatal PA using accelerometers might provide a more precise assessment and might provide a more accurate estimation of changes and variations in the PA level during the course of pregnancy. Since the GeliS trial was performed in a large cohort within the real-life setting of routine prenatal care, using other methods of PA data collection in place of or in addition to the PPAQ was not feasible. A minor limitation is that our cohort differed slightly from the general German population of women of child-bearing age in terms of educational level and BMI categories [53], which needs to be considered when generalizing our findings. Moreover, neonatal and obstetric outcomes were collected from different hospitals, and data collection was, thus, not completely standardized. In addition, there was no possibility to collect offspring´s body composition measurements, which may have expanded some of our findings beyond associations with crude measurements of body weight and BMI. Lastly, we are aware that some pregnancy-induced complications such as premature contractions that potentially led to a reduction of maternal PA, could have resulted in obstetric complications (e.g., preterm birth) and could have biased our results.
There are several strengths of this analysis that merit particular attention. Current research has either investigated women with normal weight or studied women with overweight and obesity. The GeliS cohort comprised women of all BMI categories, which allowed us to report the impact of prenatal PA for women in all weight ranges. Irrespective of shortcomings, the PPAQ is a valid and easily applicable tool that enables an extensive description of PA behavior during pregnancy. Using the PPAQ, we could not only estimate the impact of different PA intensities, but could also sub-group participants according to their activity level into meeting or not meeting the ACOG prenatal PA recommendations. This gave us the opportunity to report differences in obstetric and neonatal outcomes between sub-groups. Data for this study were collected within a public health approach under real-life conditions without requiring further measurements or tools, which allowed for methodological advantages. First, we were able to follow participants and collect data longitudinally over the course of pregnancy, which allowed us to observe the impact of prenatal PA in early as well as in late pregnancy. Second, we were able to collect data on a relatively large study sample. This provided a comprehensive and valuable assessment of the influence of antenatal PA on infant health outcomes as well as obstetric parameters.
To the best of our knowledge, there is no other trial that has provided a comprehensive description of the impact of early as well as late prenatal PA on obstetric and neonatal outcomes in such a large sample and that was additionally able to demonstrate the influence of PA intensities on these parameters.

5. Conclusions

This secondary analysis of the large-scale GeliS cohort demonstrated moderate differences in offspring anthropometrics and obstetric as well as neonatal outcomes associated with maternal PA behavior. Moreover, the odds of adverse neonatal and obstetric outcomes seemed to be dependent on the intensity and timing of prenatal PA. Future research should concentrate on offspring´s body composition to expand current investigations and to provide more insight into the clinical meaning of such findings. In terms of health benefits for the mothers-to-be and their offspring, it remains a challenge to characterize the optimal intensity level of antenatal PA. A follow-up of infants may help to reveal the long-term impact of PA during pregnancy on infant health and its potential contribution in the development of childhood obesity.

Supplementary Materials

The following are available online at https://www.mdpi.com/2077-0383/8/10/1735/s1. Table S1: Unadjusted differences between active and inactive women in infant anthropometrics, neonatal, and obstetric outcomes. Table S2: Differences between activeT0+T1 and inactiveT0+T1 women in infant anthropometrics, neonatal, and obstetric outcomes. Table S3: Associations between physical activity intensity and infant anthropometrics and obstetric outcomes (unadjusted data). Table S4: Associations between physical activity intensity and neonatal outcomes (unadjusted data).

Author Contributions

Conceptualization, H.H., K.R., J.H., and J.G. Methodology, H.H., K.R., J.H., J.G., and L.S. Formal analysis, J.H., K.G., and L.S. Investigation, J.H., J.G., and J.K. Resources, K.R., J.K., E.R., L.K., and J.G. Data curation, J.H., K.G., and L.S. Writing—original draft preparation, J.H. Writing—review and editing, J.G., K.G., L.S., K.R., J.K., M.S., D.M., E.R., L.K., and H.H. Visualization, J.H. Supervision, H.H. Project administration, K.R. and J.H. Funding acquisition, H.H.

Funding

The study is funded by the Else Kröner-Fresenius Center for Nutritional Medicine at the Technical University of Munich, the Competence Center for Nutrition (KErn) in Bavaria, the Bavarian State Ministry of Food, Agriculture and Forestry, the Bavarian State Ministry of Health and Care (Health Initiative ”Gesund.Leben.Bayern“), the AOK Bayern, the largest statutory health insurance in Bavaria, as well as the DEDIPAC consortium by the Joint Programming Initiative (JPI) “A Healthy Diet for a Healthy Life.” Data collection, analysis, interpretation of data, and manuscript preparation were independent from founders.

Acknowledgments

We gratefully acknowledge the valuable contribution from the Munich Study Center at the Technical University of Munich and project managers at the expert centers for nutrition/community catering at the regional offices (AELF) of the Bavarian State Ministry of Food, Agriculture and Forestry (StMELF), which have been coordinating the study on the regional level. We gratefully acknowledge the work and contribution of our colleague Christina Holzapfel, Institute for Nutritional Medicine, Klinikum rechts der Isar, Technical University of Munich. The support of Renate Oberhoffer and Christina Sitzberger, Chair of Preventative Pediatrics, Technical University of Munich, Martin Wabitsch and Stefanie Brandt, Pediatric Endocrinology and Diabetes, Department of Pediatrics and Adolescent Medicine, University Medical Center Ulm, Kurt Ulm and Victoria Kehl, Institute of Medical Informatics, Statistics and Epidemiology, Klinikum rechts der Isar of the Technical University of Munich, the network Healthy Start - Young Family Network, Federal Center for Nutrition (BZfE), Federal Office for Agriculture and Food (BLE), belonging to the national IN FORM initiative (Maria Flothkötter, Katharina Krüger), Bonn, Uta Engels, Sports Center, University of Regensburg, Karl-Heinz Ladwig, Head of Research Group Mental Health at the Institute of Epidemiology, Helmholtz Centre Munich, K.T.M. Schneider, Division of Obstetrics and Perinatal Medicine, Technical University of Munich, Rüdiger von Kries, Institute of Social Paediatrics and Adolescent Medicine, Ludwig-Maximilians-University Munich, Regina Ensenauer, von Hauner Children’s Hospital, Ludwig-Maximilians-University Munich and Heinrich Heine University Düsseldorf, Rolf Holle, Institute of Health Economics and Health Care Management, Institute of Epidemiology, Helmholtz Center Munich, Gabi Pfeifer, Educational Center Nuremberg, and Eveline Rieg, Competence Center for Nutrition, Freising/Kulmbach, is gratefully acknowledged. We are also indebted to the Board of Trustees: Maria Flothkötter, German Federal Ministry of Food and Agriculture (BZfE) in the Federal Office for Agriculture and Food (BLE), Bonn, Beatrix Heilig and Martina Enke, Bavarian State Ministry of Health and Care, Marion Kratzmair and Wolfram Schaecke, Bavarian State Ministry of Food, Agriculture and Forestry, Annette Scheder and Katharina Leopold, AOK Bayern. We would also like to acknowledge the support of the Bayerische Landesärztekammer, Bayerischer Hebammen Landesverband e.V. and the Company Beurer GmbH, Ulm. Lastly, we would like to thank our colleagues Annie Naujoks and Melanie Perschl, Institute for Nutritional Medicine, Klinikum rechts der Isar, Technical University of Munich for their support and all participating practices, gynecologists, medical personnel, midwives, participants, and their families for their involvement.

Conflicts of Interest

The authors declare no conflict of interest.

List of Abbreviations

ACOGAmerican College of Obstetrics and Gynecology
BMIBody mass index
CControl group
CIConfidence interval
GeliS“Gesund leben in der Schwangerschaft”/“Healthy living in pregnancy“
IVIntervention group
METMetabolic equivalent of task
OROdds ratio
PAPhysical activity
PPAQPregnancy Physical Activity Questionnaire
RCTRandomized-controlled trial
SDStandard deviation
TALIATotal physical activity of light intensity and above
LGALarge for gestational age
SGASmall for gestational age

References

  1. World Health Organization. Childhood Overweight and Obesity. Available online: https://www.who.int/dietphysicalactivity/childhood/en/ (accessed on 28 January 2019).
  2. Singh, A.S.; Mulder, C.; Twisk, J.W.R.; van Mechelen, W.; Chinapaw, M.J.M. Tracking of childhood overweight into adulthood: A systematic review of the literature. Obes. Rev. 2008, 9, 474–488. [Google Scholar] [CrossRef] [PubMed]
  3. Schellong, K.; Schulz, S.; Harder, T.; Plagemann, A. Birth weight and long-term overweight risk: Systematic review and a meta-analysis including 643,902 persons from 66 studies and 26 countries globally. PLoS ONE 2012, 7, e47776. [Google Scholar] [CrossRef] [PubMed]
  4. Boney, C.M.; Verma, A.; Tucker, R.; Vohr, B.R. Metabolic syndrome in childhood: Association with birth weight, maternal obesity, and gestational diabetes mellitus. Pediatrics 2005, 115, e290–e296. [Google Scholar] [CrossRef] [PubMed]
  5. Weight Gain During Pregnancy. Reexamining the Guidelines; Institute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines: Washington, DC, USA, 2009; ISBN 9780309131131.
  6. The International Weight Management in Pregnancy (i-WIP) Collaborative Group. Effect of diet and physical activity based interventions in pregnancy on gestational weight gain and pregnancy outcomes: Meta-analysis of individual participant data from randomised trials. BMJ 2017, 358, j3119. [Google Scholar] [CrossRef]
  7. Muktabhant, B.; Lawrie, T.A.; Lumbiganon, P.; Laopaiboon, M. Diet or exercise, or both, for preventing excessive weight gain in pregnancy. Cochrane Database Syst. Rev. 2015, 6, CD007145. [Google Scholar] [CrossRef] [PubMed]
  8. Wiebe, H.W.; Boulé, N.G.; Chari, R.; Davenport, M.H. The effect of supervised prenatal exercise on fetal growth: A meta-analysis. Obstet. Gynecol. 2015, 125, 1185–1194. [Google Scholar] [CrossRef]
  9. Pastorino, S.; Bishop, T.; Crozier, S.R.; Granström, C.; Kordas, K.; Küpers, L.K.; O’Brien, E.; Polanska, K.; Sauder, K.A.; Zafarmand, M.H.; et al. Associations between maternal physical activity in early and late pregnancy and offspring birth size: Remote federated individual level meta-analysis from eight cohort studies. BJOG Int. J. Obstet. Gynaecol. 2018. [Google Scholar] [CrossRef]
  10. Bisson, M.; Lavoie-Guénette, J.; Tremblay, A.; Marc, I. Physical Activity Volumes during Pregnancy: A Systematic Review and Meta-Analysis of Observational Studies Assessing the Association with Infant’s Birth Weight. AJP Rep. 2016, 6, e170–e197. [Google Scholar] [CrossRef]
  11. Aune, D.; Schlesinger, S.; Henriksen, T.; Saugstad, O.D.; Tonstad, S. Physical activity and the risk of preterm birth: A systematic review and meta-analysis of epidemiological studies. BJOG Int. J. Obstet. Gynaecol. 2017, 124, 1816–1826. [Google Scholar] [CrossRef]
  12. Du, M.-C.; Ouyang, Y.-Q.; Nie, X.-F.; Huang, Y.; Redding, S.R. Effects of physical exercise during pregnancy on maternal and infant outcomes in overweight and obese pregnant women: A meta-analysis. Birth 2018. [Google Scholar] [CrossRef]
  13. Davenport, M.H.; Ruchat, S.-M.; Sobierajski, F.; Poitras, V.J.; Gray, C.E.; Yoo, C.; Skow, R.J.; Jaramillo Garcia, A.; Barrowman, N.; Meah, V.L.; et al. Impact of prenatal exercise on maternal harms, labour and delivery outcomes: A systematic review and meta-analysis. Br. J. Sports Med. 2019, 53, 99–107. [Google Scholar] [CrossRef] [PubMed]
  14. Domenjoz, I.; Kayser, B.; Boulvain, M. Effect of physical activity during pregnancy on mode of delivery. Am. J. Obstet. Gynecol. 2014, 211, 401.e1. [Google Scholar] [CrossRef]
  15. Poyatos-León, R.; García-Hermoso, A.; Sanabria-Martínez, G.; Álvarez-Bueno, C.; Sánchez-López, M.; Martínez-Vizcaíno, V. Effects of exercise during pregnancy on mode of delivery: A meta-analysis. Acta Obstet. Gynecol. Scand. 2015, 94, 1039–1047. [Google Scholar] [CrossRef]
  16. The American College of Obstetricians and Gynecologists. ACOG Committee Opinion No. 650 (Reaffirmed 2019): Physical Activity and Exercise During Pregnancy and the Postpartum Period. Obstet. Gynecol. 2015, 126, e135–e142. [Google Scholar] [CrossRef]
  17. Koletzko, B.; Bauer, C.-P.; Bung, P.; Cremer, M.; Flothkötter, M.; Hellmers, C.; Kersting, M.; Krawinkel, M.; Przyrembel, H.; Rasenack, R.; et al. Practice recommendations of the Network “Healthy Start—Young Family Network”. Dtsch. Med. Wochenschr. 2012, 137, 1366–1372. [Google Scholar] [CrossRef] [PubMed]
  18. Rauh, K.; Kunath, J.; Rosenfeld, E.; Kick, L.; Ulm, K.; Hauner, H. Healthy living in pregnancy: A cluster-randomized controlled trial to prevent excessive gestational weight gain—Rationale and design of the GeliS study. BMC Pregnancy Childbirth 2014, 14, 119. [Google Scholar] [CrossRef]
  19. Kunath, J.; Günther, J.; Rauh, K.; Hoffmann, J.; Stecher, L.; Rosenfeld, E.; Kick, L.; Ulm, K.; Hauner, H. Effects of a lifestyle intervention during pregnancy to prevent excessive gestational weight gain in routine care - the cluster-randomised GeliS trial. BMC Med. 2019, 17, 5. [Google Scholar] [CrossRef] [PubMed]
  20. Günther, J.; Hoffmann, J.; Kunath, J.; Spies, M.; Meyer, D.; Stecher, L.; Rosenfeld, E.; Kick, L.; Rauh, K.; Hauner, H. Effects of a Lifestyle Intervention in Routine Care on Prenatal Dietary Behavior-Findings from the Cluster-Randomized GeliS Trial. J. Clin. Med. 2019, 8, 960. [Google Scholar] [CrossRef]
  21. Hoffmann, J.; Günther, J.; Geyer, K.; Stecher, L.; Rauh, K.; Kunath, J.; Meyer, D.; Sitzberger, C.; Spies, M.; Rosenfeld, E.; et al. Effects of a lifestyle intervention in routine care on prenatal physical activity—findings from the cluster-randomised GeliS trial. BMC Pregnancy Childbirth 2019, in press. [Google Scholar]
  22. Hoffmann, J.; Günther, J.; Stecher, L.; Spies, M.; Meyer, D.; Kunath, J.; Raab, R.; Rauh, K.; Hauner, H. Effects of a Lifestyle Intervention in Routine Care on Short- and Long-Term Maternal Weight Retention and Breastfeeding Behavior-12 Months Follow-up of the Cluster-Randomized GeliS Trial. J. Clin. Med. 2019, 8, 876. [Google Scholar] [CrossRef]
  23. U.S. National Library of Medicine—ClinicalTrials.gov. Healthy Living in Pregnancy—NCT01958307. Available online: https://clinicaltrials.gov/ct2/show/NCT01958307 (accessed on 16 April 2019).
  24. Kromeyer-Hauschild, K.; Wabitsch, M.; Kunze, D.; Geller, F.; Geiß, H.C.; Hesse, V.; von Hippel, A.; Jaeger, U.; Johnsen, D.; Korte, W.; et al. Perzentile für den Body-mass-Index für das Kindes- und Jugendalter unter Heranziehung verschiedener deutscher Stichproben. Monatsschr. Kinderheilkunde 2001, 149, 807–818. [Google Scholar] [CrossRef]
  25. Chasan-Taber, L.; Schmidt, M.D.; Roberts, D.E.; Hosmer, D.; Markenson, G.; Freedson, P.S. Development and validation of a Pregnancy Physical Activity Questionnaire. Med. Sci. Sports Exerc. 2004, 36, 1750–1760. [Google Scholar] [CrossRef]
  26. Ainsworth, B.E.; Haskell, W.L.; Whitt, M.C.; Irwin, M.L.; Swartz, A.M.; Strath, S.J.; O’Brien, W.L.; Bassett, D.R.; Schmitz, K.H.; Emplaincourt, P.O.; et al. Compendium of physical activities: An update of activity codes and MET intensities. Med. Sci. Sports Exerc. 2000, 32, S498–S504. [Google Scholar] [CrossRef]
  27. Byrne, N.M.; Hills, A.P.; Hunter, G.R.; Weinsier, R.L.; Schutz, Y. Metabolic equivalent: One size does not fit all. J. Appl. Physiol. 2005, 99, 1112–1119. [Google Scholar] [CrossRef] [PubMed]
  28. Ainsworth, B.E.; Haskell, W.L.; Herrmann, S.D.; Meckes, N.; Bassett, D.R.; Tudor-Locke, C.; Greer, J.L.; Vezina, J.; Whitt-Glover, M.C.; Leon, A.S. 2011 Compendium of Physical Activities: A second update of codes and MET values. Med. Sci. Sports Exerc. 2011, 43, 1575–1581. [Google Scholar] [CrossRef]
  29. Chasan-Taber, L.; Schmidt, M.D. Pregnancy Physical Activity Questionnaire. Can. J. Public Health 2016, 106, e563. [Google Scholar] [CrossRef] [PubMed]
  30. Nguyen, C.L.; Pham, N.M.; Lee, A.H.; Nguyen, P.T.H.; Chu, T.K.; Ha, A.V.V.; Duong, D.V.; Duong, T.H.; Binns, C.W. Physical activity during pregnancy is associated with a lower prevalence of gestational diabetes mellitus in Vietnam. Acta Diabetol. 2018. [Google Scholar] [CrossRef]
  31. Koushkie Jahromi, M.; Namavar Jahromi, B.; Hojjati, S. Relationship between Daily Physical Activity During Last Month of Pregnancy and Pregnancy Outcome. Iran. Red Crescent Med. J. 2011, 13, 15–20. [Google Scholar] [PubMed]
  32. Badon, S.E.; Littman, A.J.; Chan, K.C.G.; Williams, M.A.; Enquobahrie, D.A. Maternal sedentary behavior during pre-pregnancy and early pregnancy and mean offspring birth size: A cohort study. BMC Pregnancy Childbirth 2018, 18, 267. [Google Scholar] [CrossRef]
  33. Bisson, M.; Croteau, J.; Guinhouya, B.C.; Bujold, E.; Audibert, F.; Fraser, W.D.; Marc, I. Physical activity during pregnancy and infant’s birth weight: Results from the 3D Birth Cohort. BMJ Open Sport Exerc. Med. 2017, 3, e000242. [Google Scholar] [CrossRef] [PubMed]
  34. Hegaard, H.K.; Petersson, K.; Hedegaard, M.; Ottesen, B.; Dykes, A.K.; Henriksen, T.B.; Damm, P. Sports and leisure-time physical activity in pregnancy and birth weight: A population-based study. Scand. J. Med. Sci. Sports 2010, 20, e96–e102. [Google Scholar] [CrossRef]
  35. Harrod, C.S.; Chasan-Taber, L.; Reynolds, R.M.; Fingerlin, T.E.; Glueck, D.H.; Brinton, J.T.; Dabelea, D. Physical activity in pregnancy and neonatal body composition: The Healthy Start study. Obstet. Gynecol. 2014, 124, 257–264. [Google Scholar] [CrossRef] [PubMed]
  36. Ming, W.-K.; Ding, W.; Zhang, C.J.P.; Zhong, L.; Long, Y.; Li, Z.; Sun, C.; Wu, Y.; Chen, H.; Chen, H.; et al. The effect of exercise during pregnancy on gestational diabetes mellitus in normal-weight women: A systematic review and meta-analysis. BMC Pregnancy Childbirth 2018, 18, 440. [Google Scholar] [CrossRef] [PubMed]
  37. Nieuwenhuijsen, M.J.; Northstone, K.; Golding, J. Swimming and birth weight. Epidemiology 2002, 13, 725–728. [Google Scholar] [CrossRef] [PubMed]
  38. Juhl, M.; Olsen, J.; Andersen, P.K.; Nøhr, E.A.; Andersen, A.-M.N. Physical exercise during pregnancy and fetal growth measures: A study within the Danish National Birth Cohort. Am. J. Obstet. Gynecol. 2010, 202, 63-e1. [Google Scholar] [CrossRef]
  39. Perkins, C.C.D.; Pivarnik, J.M.; Paneth, N.; Stein, A.D.; Stein, A.D. Physical activity and fetal growth during pregnancy. Obstet. Gynecol. 2007, 109, 81–87. [Google Scholar] [CrossRef]
  40. Ferraro, Z.M.; Gaudet, L.; Adamo, K.B. The potential impact of physical activity during pregnancy on maternal and neonatal outcomes. Obstet. Gynecol. Surv. 2012, 67, 99–110. [Google Scholar] [CrossRef]
  41. Clapp, J.F. Influence of endurance exercise and diet on human placental development and fetal growth. Placenta 2006, 27, 527–534. [Google Scholar] [CrossRef]
  42. Ruchat, S.-M.; Davenport, M.H.; Giroux, I.; Hillier, M.; Batada, A.; Sopper, M.M.; McManus, R.; Hammond, J.-A.; Mottola, M.F. Effect of exercise intensity and duration on capillary glucose responses in pregnant women at low and high risk for gestational diabetes. Diabetes Metab. Res. Rev. 2012, 28, 669–678. [Google Scholar] [CrossRef]
  43. Salvesen, K.Å.; Hem, E.; Sundgot-Borgen, J. Fetal wellbeing may be compromised during strenuous exercise among pregnant elite athletes. Br. J. Sports Med. 2012, 46, 279–283. [Google Scholar] [CrossRef]
  44. Morison, P.N.; Bacardi-Gascon, M.; Lopez-Corrales, M.; Jimenez-Cruz, A. Combined dietary-exercise intervention for gestational weight gain and birthweight: A meta-analysis. Asia Pac. J. Clin. Nutr. 2018, 27, 860–868. [Google Scholar] [CrossRef]
  45. Juhl, M.; Andersen, P.K.; Olsen, J.; Madsen, M.; Jørgensen, T.; Nøhr, E.A.; Andersen, A.-M.N. Physical exercise during pregnancy and the risk of preterm birth: A study within the Danish National Birth Cohort. Am. J. Epidemiol. 2008, 167, 859–866. [Google Scholar] [CrossRef] [PubMed]
  46. Di Mascio, D.; Magro-Malosso, E.R.; Saccone, G.; Marhefka, G.D.; Berghella, V. Exercise during pregnancy in normal-weight women and risk of preterm birth: A systematic review and meta-analysis of randomised controlled trials. Am. J. Obstet. Gynecol. 2016, 215, 561–571. [Google Scholar] [CrossRef] [PubMed]
  47. Magro-Malosso, E.R.; Saccone, G.; Di Mascio, D.; Di Tommaso, M.; Berghella, V. Exercise during pregnancy and risk of preterm birth in overweight and obese women: A systematic review and meta-analysis of randomised controlled trials. Acta Obstet. Gynecol. Scand. 2017, 96, 263–273. [Google Scholar] [CrossRef] [PubMed]
  48. Jukic, A.M.Z.; Evenson, K.R.; Daniels, J.L.; Herring, A.H.; Wilcox, A.J.; Hartmann, K.E. A prospective study of the association between vigorous physical activity during pregnancy and length of gestation and birthweight. Matern. Child Health J. 2012, 16, 1031–1044. [Google Scholar] [CrossRef]
  49. Kahn, M.; Robien, K.; DiPietro, L. Maternal Leisure-time Physical Activity and Risk of Preterm Birth: A Systematic Review of the Literature. J. Phys. Act. Health 2016, 13, 796–807. [Google Scholar] [CrossRef]
  50. Baena-García, L.; Ocón-Hernández, O.; Acosta-Manzano, P.; Coll-Risco, I.; Borges-Cosic, M.; Romero-Gallardo, L.; de La Flor-Alemany, M.; Aparicio, V.A. Association of sedentary time and physical activity during pregnancy with maternal and neonatal birth outcomes. The GESTAFIT Project. Scand. J. Med. Sci. Sports 2018. [Google Scholar] [CrossRef]
  51. Günther, J.; Hoffmann, J.; Spies, M.; Meyer, D.; Kunath, J.; Stecher, L.; Rosenfeld, E.; Kick, L.; Rauh, K.; Hauner, H. Associations between the Prenatal Diet and Neonatal Outcomes-A Secondary Analysis of the Cluster-Randomised GeliS Trial. Nutrients 2019, 11, 1889. [Google Scholar] [CrossRef]
  52. Prince, S.A.; Adamo, K.B.; Hamel, M.E.; Hardt, J.; Connor Gorber, S.; Tremblay, M. A comparison of direct versus self-report measures for assessing physical activity in adults: A systematic review. Int. J. Behav. Nutr. Phys. Act. 2008, 5, 56. [Google Scholar] [CrossRef]
  53. Mensink, G.B.M.; Schienkiewitz, A.; Haftenberger, M.; Lampert, T.; Ziese, T.; Scheidt-Nave, C. Übergewicht und Adipositas in Deutschland. Gesundheitsschutz 2013, 56, 786–794. [Google Scholar] [CrossRef]
Figure 1. Participant flow and availability of physical activity data. 1 Women without miscarriages, late loss of pregnancy, terminations, pregnancy complications that interfere with the intervention, maternal deaths, and/or that provided at least one of the three infant outcomes (birth weight, birth length, and head circumference). 2 Women who provided PA data at T0 or T1. Abbreviations: PA: physical activity, T0: assessment before or in the 12th week of gestation, and T1: assessment after the 29th week of gestation.
Figure 1. Participant flow and availability of physical activity data. 1 Women without miscarriages, late loss of pregnancy, terminations, pregnancy complications that interfere with the intervention, maternal deaths, and/or that provided at least one of the three infant outcomes (birth weight, birth length, and head circumference). 2 Women who provided PA data at T0 or T1. Abbreviations: PA: physical activity, T0: assessment before or in the 12th week of gestation, and T1: assessment after the 29th week of gestation.
Jcm 08 01735 g001
Table 1. Maternal, neonatal, and obstetric characteristics of eligible participants.
Table 1. Maternal, neonatal, and obstetric characteristics of eligible participants.
CharacteristicsTotal (n = 2018)
Maternal Characteristics
Pre-pregnancy age, years30.3 ± 4.4
Pre-pregnancy weight, kg68.2 ± 13.4
Pre-pregnancy BMI, kg/m224.4 ± 4.5
Pre-Pregnancy BMI Category
BMI 18.5–24.9 kg/m21311/2018 (65.0%)
BMI 25.0–29.9 kg/m2464/2018 (23.0%)
BMI 30.0–40.0 kg/m2243/2018 (12.0%)
Educational Level
General secondary school320/2014 (15.9%)
Intermediate secondary school856/2014 (42.5%)
(Technical) High school 838/2014 (41.6%)
Country of Birth
Germany1790/2014 (88.9%)
Others224/2014 (11.1%)
Nulliparous1162/2018 (57.6%)
Living with a partner 1939/2011 (96.4%)
Full-time employed1056/1996 (52.9%)
Neonatal and Obstetric Characteristics
Birth weight, g3337.6 ± 517.8
Birth length, cm51.3 ± 2.6
Head circumference, cm34.7 ± 1.6
BMI, kg/m212.7 ± 1.3
BMI-z-Score a0.04 ± 1.02
LGA148/2016 (7.3%)
SGA172/2016 (8.5%)
Low birth weight101/2018 (5.0%)
High birth weight169/2018 (8.4%)
Macrosomia19/2018 (0.9%)
Preterm birth132/2016 (6.5%)
Caesarean section582/2017 (28.9%)
Depicted are mean ± SD or proportions (percent). a BMI-z-score was calculated using German standards [24]. Abbreviations: BMI: body mass index, LGA: large for gestational age, and SGA: small for gestational age.
Table 2. Differences between active and inactive women in infant anthropometrics, neonatal, and obstetric outcomes.
Table 2. Differences between active and inactive women in infant anthropometrics, neonatal, and obstetric outcomes.
Time PointActiveInactive
Anthropometrics naMean±SDnaMean±SDAdjusted Effect Size b (95% CI)Adjusted p Value b
Birth weight, gT0n = 8933338.0 ± 527.9n = 10083337.4 ± 508.911.44 (−35.02, 57.91)0.629
T1n = 10613364.5 ± 481.0n = 8273341.4 ± 492.549.74 (4.94, 94.53)0.030
Birth length, cmT0n = 88551.3 ± 2.6n = 100051.4 ± 2.6−0.00 (−0.24, 0.23)0.980
T1n = 105651.4 ± 2.4n = 82451.3 ± 2.60.23 (−0.00, 0.46)0.054
Head circum-ference, cmT0n = 87534.7 ± 1.6n = 98934.7 ± 1.6−0.02 (−0.17, 0.12)0.762
T1n = 104734.8 ± 1.5n = 81434.7 ± 1.60.11 (−0.04, 0.25)0.148
BMI, kg/m2T0n = 88512.7 ± 1.3n = 100012.6 ± 1.20.04 (−0.08, 0.15)0.503
T1n = 105612.7 ± 1.3n = 82412.7 ± 1.20.09 (−0.03, 0.20)0.140
BMI-z-scorecT0n = 8840.05 ± 1.07n = 10000.03 ± 0.980.04 (−0.06, 0.13)0.463
T1n = 10550.07 ± 1.04n = 8240.04 ± 0.960.07 (−0.02, 0.16)0.134
Neonatal and Obstetric Outcomes n (%) n (%)Adjusted OR b (95% CI)Adjusted p Value b
LGAT0n = 89374 (8.3)n = 100666 (6.6)1.37 (0.96, 1.94)0.079
T1n = 106187 (8.2)n = 82654 (6.5)1.39 (0.97, 2.00)0.075
SGAT0n = 89372 (8.1)n = 100692 (9.1)0.84 (0.61, 1.16)0.293
T1n = 1061100 (9.4)n = 82661 (7.4)1.16 (0.82, 1.63)0.408
Low birth weightT0n = 89349 (5.5)n = 100846 (4.6)1.16 (0.77, 1.76)0.485
T1n = 106146 (4.3)n = 82734 (4.1)0.95 (0.60, 1.51)0.835
High birth weightT0n = 89381 (9.1)n = 100880 (7.9)1.20 (0.86, 1.66)0.282
T1n = 106192 (8.7)n = 82766 (8.0)1.16 (0.82, 1.62)0.402
MacrosomiaT0n = 89310 (1.1)n = 10088 (0.8)1.37 (0.54, 3.53)0.509
T1n = 106111 (1.0)n = 8277 (0.8)1.18 (0.44, 3.14)0.746
Preterm birthT0n = 89361 (6.8)n = 100662 (6.2)1.09 (0.75, 1.57)0.649
T1n = 106152 (4.9)n = 82657 (6.9)0.66 (0.44, 0.98)0.038
Caesarean sectionT0n = 893264 (29.6)n = 1008278 (27.6)1.11 (0.90, 1.36)0.323
T1n = 1060301 (28.4)n = 827232 (28.1)0.98 (0.80, 1.21)0.868
Depicted are mean ± SD and proportions (n (%)).a Number of participants depend on the availability of anthropometric, neonatal, and obstetric data. b adjusted for pre-pregnancy age, pre-pregnancy BMI, parity, group assignment. c BMI-z-score was calculated using German standards [24]. Active: Women meeting physical activity recommendations defined as ≥ 7.5 MET-h/week in category sports activity of moderate-intensity or greater. Inactive: Women not meeting physical activity recommendations (< 7.5 MET-h/week in category sports activity of moderate-intensity or greater). Abbreviations: BMI: body mass index, LGA: large for gestational age, OR: odds ratio, SGA: small for gestational age, T0: assessment before or in the 12th week of gestation, and T1: assessment after the 29th week of gestation.
Table 3. Associations between physical activity intensity and infant anthropometrics and obstetric outcomes.
Table 3. Associations between physical activity intensity and infant anthropometrics and obstetric outcomes.
Birth Weight BMIPreterm BirthCaesarean Section
Adjusted Effect Size a (95% CI)Adjusted p Value aAdjusted Effect Size a (95% CI)Adjusted p Value aAdjusted OR a (95% CI)Adjusted p Value aAdjusted OR a (95% CI)Adjusted p Value a
TALIA
T02.81 (−0.68, 6.30)0.1150.01 (−0.00, 0.02)0.0990.98 (0.95, 1.01)0.2761.02 (1.00, 1.03)0.040
T11.05 (−2.44, 4.55)0.5550.00 (−0.01, 0.01)0.3570.98 (0.95, 1.02)0.3251.00 (0.98, 1.01)0.789
Sedentary-Intensity
T0−15.92 (−37.41, 5.6)0.1460.00 (−0.05, 0.05)0.9981.16 (0.99, 1.35)0.0511.02 (0.93, 1.12)0.661
T1−20.62 (−38.79, −2.45)0.0260.00 (−0.05, 0.04)0.8831.14 (0.99, 1.32)0.0700.98 (0.90, 1.07)0.717
Light-Intensity
T01.17 (−4.72, 7.06)0.6970.00 (−0.01, 0.02)0.5890.98 (0.93, 1.03)0.4301.03 (1.00, 1.06)0.032
T10.77 (−4.55, 6.08)0.7770.00 (−0.01, 0.02)0.7320.97 (0.92, 1.02)0.2671.00 (0.98, 1.03)0.757
Moderate-Intensity
T03.98 (−0.77, 8.73)0.1000.01 (−0.00, 0.02)0.0870.98 (0.94, 1.02)0.3301.01 (0.99, 1.03)0.262
T13.32 (−2.87, 9.52)0.2930.01 (−0.01, 0.03)0.2280.98 (0.92, 1.04)0.5330.99 (0.96, 1.02)0.540
Vigorous-Intensity
T06.00 (−56.81, 68.81)0.8520.02 (−0.14, 0.17)0.8521.06 (0.65, 1.71)0.8220.91 (0.68, 1.21)0.518
T1−38.10 (−131.22, 55.03)0.423−0.11 (−0.35, 0.13)0.3501.71 (0.94, 3.11)0.0810.79 (0.49, 1.28)0.333
Estimated is the effect of 10 MET-h/week change in intensities on infant anthropometrics and obstetric outcomes. a adjusted for pre-pregnancy age, pre-pregnancy BMI, parity, and group assignment. Abbreviations: BMI: body mass index. OR: odds ratio. T0: assessment before or in the 12th week of gestation. T1: Assessment after the 29th week of gestation. TALIA: Total physical activity of light intensity and above.
Table 4. Associations between physical activity intensity and neonatal outcomes.
Table 4. Associations between physical activity intensity and neonatal outcomes.
Low Birth WeightHigh Birth WeightLGASGA
Adjusted OR a (95% CI)Adjusted p Value aAdjusted OR a (95% CI)Adjusted p Value aAdjusted OR a (95% CI)Adjusted p Value aAdjusted OR a (95% CI)Adjusted p Value a
TALIA
T00.98 (0.94, 1.01)0.1811.02 (0.99, 1.04)0.1941.02 (0.99, 1.04)0.2020.98 (0.96, 1.01)0.148
T11.00 (0.96, 1.04)0.9691.01 (0.98, 1.03)0.5161.01 (0.98, 1.03)0.7401.00 (0.97, 1.03)0.937
Sedentary-Intensity
T01.27 (1.08, 1.48)0.0040.93 (0.79, 1.10)0.3870.92 (0.77, 1.09)0.3300.90 (0.76, 1.06)0.198
T11.25 (1.07, 1.46)0.0050.91 (0.78, 1.05)0.1940.88 (0.75, 1.03)0.1211.00 (0.88, 1.15)0.979
Light-Intensity
T00.97 (0.92, 1.03)0.2981.00 (0.96, 1.04)0.8951.00 (0.96, 1.05)0.9950.96 (0.92, 1.00)0.053
T10.99 (0.93, 1.05)0.7110.99 (0.95, 1.03)0.6810.99 (0.95, 1.04)0.7220.98 (0.94, 1.02)0.404
Moderate-Intensity
T00.98 (0.93, 1.03)0.4031.03 (1.00, 1.06)0.0801.02 (0.99, 1.06)0.1351.00 (0.96, 1.03)0.860
T11.01 (0.94, 1.07)0.8421.04 (1.00, 1.08)0.0501.03 (0.99, 1.07)0.1851.02 (0.98, 1.07)0.383
Vigorous-Intensity
T00.84 (0.45, 1.57)0.5791.08 (0.70, 1.66)0.7431.14 (0.72, 1.80)0.5871.08 (0.72, 1.63)0.703
T10.97 (0.36, 2.57)0.9461.38 (0.77, 2.49)0.2781.24 (0.64, 2.40)0.5331.48 (0.86, 2.55)0.160
Estimated is the effect of 10 MET-h/week change in intensities on neonatal outcomes. a adjusted for pre-pregnancy age, pre-pregnancy BMI, parity, and group assignment. Abbreviations: LGA: large for gestational age; OR: odds ratio; SGA: small for gestational age, T0: assessment before or in the 12th week of gestation, T1: assessment after the 29th week of gestation, TALIA: total physical activity of light intensity and above.

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Back to TopTop