Reduction of Neonatal Macrosomia Rate of Infants Born to Overweight and Obese Women through Nutrition Counseling in Pregnancy – A One-arm Interventional Study

Abstract

Introduction

Because of fetal programming, neonatal macrosomia is associated with a higher long-term risk of metabolic disease. In 2020, the overall macrosomia rate of term-born singletons born to overweight or obese mothers in our center was approximately 30%. The aim of our study was to reduce the macrosomia rate with pregnancy-related nutrition counseling.

Methods

This is a single center, one-arm, interventional pilot study of 99 singleton pregnancies. The intervention took the form of three individual and group education sessions on pregnancy-relevant nutritional topics and exercise in the 10th to 14th, 20th to 24th and 30th to 34th weeks of gestation. The primary endpoint was the overall macrosomia rate born to overweight/obese mothers and birth ≥ 37 weeks of gestation. Macrosomia was defined as the presence of at least one of the following criteria: birth weight ≥ 4000 g, birth weight > 90th percentile, length-related birth weight > 90th percentile, birth weight > 90th percentile after adjustment for initial maternal weight and height. The results were compared with those of a non-interventional cohort from the same center.

Results

Ninety-one percent of pregnant women with a pre-pregnancy BMI ≥ 25 kg/m² had a delivery at term (n = 77/85). The overall macrosomia rate of these children was 19.5% (95% CI: 11.3% to 30.1%, n = 15/77) and therefore lower than the expected BMI-corrected macrosomia rate of the comparison group of 31.3% (p = 0.026). In the total cohort, which included normal-weight women, a trend toward normalization of birth weights was observed (p = 0.083).

Conclusion

Professional nutrition counseling during pregnancy can reduce the neonatal macrosomia rate of infants born to women with a BMI ≥ 25 kg/m². Relevant provision of counseling services in the context of antenatal care would be useful for affected women.

Keywords

obesity - overweight - pregnancy - nutrition counseling - neonatal macrosomia

Introduction

The health risks associated with overweight (body mass index, BMI 25–29,9 kg/m²) and obesity (BMI ≥ 30 kg/m²) are socially very important because of the increasing prevalence of overweight and obesity [1]. The percentage of overweight and obese adults in Germany in 2021 was 53% [2]. According to the German Perinatal Statistics, the percentage of overweight/obese pregnant women has increased continually from 35.0% in 2013 to more than 38.2% in 2019 and 43.82% in 2022 [3] [4] [5]. Maternal overweight and obesity in pregnancy lead to higher birth weights and higher neonatal macrosomia rates [6] [7] [8] [9]. Neonatal macrosomia is associated with a higher lifelong risk of overweight, obesity, cardiovascular disease and metabolic diseases such as diabetes mellitus [10] [11]. In addition to postnatal lifestyle factors, prenatal imprinting from “fetal programming” is assumed to be an important risk factor [12] [13]. Factors which promote neonatal macrosomia and/or childhood overweight or obesity are not just higher maternal BMI but also lack of exercise and the consumption of carbohydrate-rich foods which lead to excessive weight gain in pregnancy and the development of gestational diabetes [1] [14] [15] [16] [17]. If a glucose-rich intrauterine milieu develops due to a high overall energy intake and the consumption mainly of energy-dense processed foods, this is not just likely to result in the birth of significantly heavier infants but can also lead to “erroneous neuroendocrine programming” of the body weight and metabolic regulation of the child over the longer term [18] [19]. Fetal macrosomia also increases the rates of obstetric complications such as shoulder dystocia, higher-grade maternal childbirth injuries, and postnatal adaptation disorders, especially if gestational diabetes mellitus (GDM) is also present [20] [21].

There is no consistent international definition of neonatal macrosomia and the term “neonatal obesity” is not yet established. Absolute birth weights of 4000 g and 4500 g are used as lower limits [1] [3] [4] [5]. But this definition does not take account of regional differences [22], gestational age, or sex, and it is useful to use population-based standard values rather than specified birth weights. Neonates with a birth weight of more than the 90th percentile are considered large for gestational age (LGA) or hypertrophic. Both terms are used in the German-language guideline on GDM (since 2018) and in German perinatal statistics [3] [21].

There are also percentage-related classifications similar to BMI which take the length of the infant at birth (> 90th length-related weight percentile) into consideration as well as individualized percentile curves which take account of maternal weight. However, these figures are not yet recorded across all of Germany [23]. Because the definitions are inconsistent, this study has included all possible definitions of macrosomia in the form of an overall macrosomia rate.

In principle, lifestyle changes can modify BMI, weight gain in pregnancy, and ultimately the macrosomia rate. The success of such measures depends on the timing of the start of the intervention and the motivation for and intensity of the intervention [8]. The aim is to establish physiological changes in dietary and exercise habits starting in early pregnancy. Healthy foodstuffs with a high percentage of dietary fiber can reduce the risk of excessive weight gain in pregnancy and prevent excessive intrauterine fetal growth in the context of primary prevention of obesity. Professional nutrition counseling is currently not part of standard antenatal care. However, the motivation of women to address the issue of healthy eating is especially high in this stage of life [24].

This pilot study aimed to test the feasibility and practicability of methods and processes of nutrition counseling in pregnancy. The question was whether the macrosomia rate of term-born neonates in the study could be effectively reduced compared to comparative figures for 2020 from University Gynecological Hospital (UFK) Rostock.

Methods

Study design and participants

The “Gesund mal Zwei” (GemaZ) [= Healthy times Two] study was carried out as a single center, one-arm, interventional pilot study from October 2018 to December 2021. Women with an intact singleton pregnancy were included. Exclusion criteria were maternal age < 18 years, multiple pregnancy, inability to communicate properly in German, or preexisting diabetes mellitus. Participants were enrolled in the study in the first trimester of pregnancy between 10 and 14 weeks of gestation (GW). Initially, only women with a preconception BMI ≥ 25 kg/m² were included but because of the limited recruitment numbers, the protocol was amended in September 2019 to allow women to be included irrespective of their BMI. The aim of this change was to destigmatize participants and thereby increase willingness to participate in the study. Primary endpoint of the study was the overall macrosomia rate of term-born neonates born to overweight and obese pregnant women, defined as a gestational age at delivery of ≥ 37 GW. The due date was determined based on the date of the last menstruation. The date was amended if there was a deviation of ≥ 7 days when the crown-rump length was determined by sonography in early pregnancy. The overall macrosomia rate was compiled based on by the presence of at least one of the following criteria: birth weight ≥ 4000 g, > 90th weight percentile relating to GW and sex (LGA), > 90th length-related weight percentile (similar to BMI) or > 90th weight percentile after adjusting for preconception maternal weight and height [23] (Fig. S1) (supplementary material, online).

Secondary endpoints were maternal weight gain during pregnancy based on the recommendation of the Institute of Medicine (IOM), development of GDM, and evaluation by dieticians. The IOM recommends that normal-weight women should have a weight gain of 11.5–16 kg, overweight women should limit their weight gain to 7–11.5 kg and obese women should only gain 5–9 kg in pregnancy [25]. Based on these recommendations, weight gain was classified into “below to adequate” and “excessive.”

The definition of GDM was based on the criteria of the consensus recommendation of the International Association of Diabetes and Pregnancy Study Groups (IADPSG) [26].

The intervention consisted of repeated nutrition education sessions led by certified dieticians who received study-related training beforehand. The training focused on pregnancy-specific aspects of metabolic regulation and diet. Test subjects received three counselling sessions of 60 minutes each which consisted of both individual discussions and group discussions in the period from 10 to 14 GW after inclusion in the study, between 20 and 24 GW, and between 30 and 34 GW ([Fig. 1]). The contents of the training sessions build upon each other and are easily understandable by non-experts. In addition to practical lifestyle-relevant recommendations on nutrition and diet including a daily schedule and physical activities, the sessions also provided theoretical information about the association between carbohydrate-dense maternal diet and intrauterine fetal growth. The contents of the different sessions were adjusted to the specific metabolic situation in the respective trimester of pregnancy. The contents of each session were also provided to participants in writing. After each session, the test persons were asked to evaluate the training session on a voluntary and anonymous basis. Otherwise, antenatal care was provided in accordance with standard recommendations. The anthropometric data of the neonates were evaluated and classified postnatally.

Fig. 1 Protocol of the methodology of the study. Counseling sessions included the following aspects: basic principles behind the building blocks of a healthy diet with a focus on carbohydrates and dietary fiber, energy metabolism, weight gain during pregnancy including the recommendation of the Institute of Medicine, specific examples of a balanced diet, creation of a daily schedule, individual exercise counseling (e.g., walking with recommendations about the duration and calculation of energy consumption), pathophysiology of gestational diabetes, importance of breastfeeding, discussion of counseling experiences.

Sample size calculation, statistics

As this was a one-arm interventional study, a comparison with data of women and neonates receiving standard care at UFK Rostock was planned. The overall macrosomia rate for term-born singletons born to mothers with a preconception BMI ≥ 25 kg/m² from 2017 of 29.0% was taken as the basis for calculating the sample size (Table S1) (supplementary material, online). If the assumption was an estimated reduction of 10% in absolute terms as clinically relevant, an initial sample size of 300 participants was calculated. Recruitment proved to be slow and the study protocol was therefore amended in September 2019 by opening the study to women with a BMI < 25 kg/m². In addition, the recruitment goal was lowered to 100 participants.

To evaluate the obtained data, the overall macrosomia rates of University Gynecological Hospital Rostock from 2020 were used as the comparison group.

In accordance with the relative distribution of BMI classes in the GemaZ study (< 25 kg/m² 14.44%, 25–29.9 kg/m² 34,44% and ≥ 30 kg/m² 51.11%), the weighted means of the macrosomia rates of University Gynecological Hospital Rostock for these classes were determined for 2020. These were then used as comparison rates for binomial macrosomia percentages in binomial tests and for exact confidence intervals. The significance level for the statistical tests was 5%. The secondary endpoint was maternal weight development and this was categorized in accordance with the recommendation of the Institute of Medicine (IOM) [25].

Ethics vote and consent

The study was registered in the German Registry of Clinical Studies (Deutsches Register Klinischer Studien, DRKS-No. 00014914). The initial study protocol and necessary subsequent amendments due to changes in the General Data Protection Regulation as well as the changes to the study protocol including adjustments of the sample size and inclusion criteria was approved by the appropriate ethics commission (ethics vote A 2018–0077). Participation in the study was voluntary after having been informed about the study and having given written consent.

Results

Characteristics of the study cohort

A total of 99 test persons were included in the study ([Fig. 2]). 85 of them (85.9%) had a BMI ≥ 25 kg/m². Over the course of the study, 90 children with a gestational age ≥ 37 GW were born (90.9%). There were three miscarriages, one of which was a late miscarriage in week 22 of gestation and one stillbirth in week 33 of gestation. Five children were preterm (5.9%), all of them born to women with a BMI ≥ 25 kg/m². 77 children with a gestational age ≥ 37 GW (90.6%) were born to the group of 85 women with a BMI ≥ 25 kg/m².

Fig. 2 Flow diagram of the study participants.

Additional data on the study cohort differentiated according to BMI class is listed in [Table 1].

Table 1 Patient data of the study population according to BMI class. Mean and standard deviation as well as absolute and relative frequencies are presented.

	All BMI classes n = 99	BMI < 25 kg/m2 n = 14	BMI 25–29.9 kg/m2 n = 34	BMI ≥ 30 kg/m2 n = 51	P value
BMI = body mass index; GemaZ = “Gesund mal Zwei” study; GW = week(s) of gestation
Age (years)	32.3 (3.93)	32.6 (3.52)	31.8 (4.26)	32.6 (3.83)	0.596
Height (cm)	169 (6.17)	170 (7.80)	169 (5.39)	170 (6.28)	0.971
Preconception weight (kg)	90.4 (22.5)	64.5 (6.17)	77.3 (7.12)	106 (19.6)	< 0.001
Preconception BMI (kg/m2)	31.4 (6.91)	22.4 (1.47)	26.9 (1.38)	36.8 (5.08)	< 0.001
Gravidity after inclusion in the GemaZ study	1.82 (0.92)	1.57 (0.85)	1.79 (0.88)	1.90 (0.96)	0.487
Parity after giving birth during the GemaZ study	1.46 (0.69)	1.57 (0.85)	1.41 (0.66)	1.47 (0.67)	0.767
Attended 1st training session, n (%)	99 (100)	14 (100)	34 (100)	51 (100)
Attended 2nd training session, n (%)	83 (100)	13 (92.9)	29 (85.3)	41 (80.4)
Attended 3rd training session, n (%)	73 (100)	11 (78.6)	26 (76.5)	36 (70.6)
Birth data, n	n = 95	n = 13	n = 33	n = 49
Maternal weight at delivery (kg)	102 (22.5)	76.2 (6.82)	89.8 (8.61)	118 (20.1)	< 0.001
Maternal weight gain during pregnancy (kg)	11.8 (6.54)	11.7 (3.85)	12.6 (4.16)	11.4 (8.23)	0.715
Gestational week at delivery	39.1 (1.52)	39.5 (1.2)	38.8 (1.81)	39.2 (1.36)	0.318
Preterm birth < 37 GW, n (%)	5 (5.3)	0	2 (6.1)	3 (6.1)
Birth ≥ 37 GW, n (%)	90 (94.7)	13 (100)	31 (93.9)	46 (93.9)
Sex of the infant
Male	47 (49.5)	8 (61.5)	16 (48.5)	23 (46.9)	0.639
Female	48 (50.5)	5 (38.5)	17 (51.5)	26 (53.1)
Body measurements of the infant
Weight (g)	3469 (485)	3626 (428)	3340 (566)	3515 (426)	0.127
Length (cm)	50.7 (2.5)	51.3 (3.01)	50.2 (2.86)	50.9 (2.05)	0.321
Head circumference (cm)	35.1 (1.61)	35.7 (1.48)	34.8 (1.89)	35.1 (1.4)	0.172

Neonatal macrosomia rates

The overall macrosomia rate irrespective of maternal BMI of live-born singletons born at term in UFK Rostock in 2020 was 24.9% (n = 620/2491, [Table 2]). Overall, 29.9% (n = 314/1049) of term-born children born to pregnant women with a BMI ≥ 25 kg/m² met at least one criterion of macrosomia. The BMI distribution in the study population differed from the BMI distribution in the comparison population with a higher rate of obesity reported for the study population (BMI ≥ 30 kg/m²: 51.1% GemaZ cohort vs. 42.8% comparison group). Because of this difference between the two groups, the expectation of macrosomia in children born to women with a BMI ≥ 25 kg/m² in the GemaZ cohort was also higher at 31.3% instead of 29.9%.

Table 2 Macrosomia rates of Voigt et al. [23] according to gestational age and maternal BMI. Comparison of births in University Gynecological Hospital Rostock in 2020 (comparison population) and in the GemaZ cohort. Only live-born singletons were included.

	All singleton births	Overall macrosomia	Weight ≥ 4000 g	Weight > 90th perc. (LGA)	Length-related weight > 90th perc.	Weight > 90th perc. after adjustment for maternal data
BMI = body mass index; GemaZ = “Gesund mal Zwei” study; LGA = large for gestational age; perc. = percentile; GW = week(s) of gestation
Comparison population, total number of singletons
All GW	2671	635 (23.7%)	373 (14.0%)	326 (12.2%)	566 (21.2%)	259 (9.7%)
< 37 GW	180	15 (8.3%)	0 (0%)	12 (6.7%)	15 (8.3%)	9 (5.0%)
≥ 37 GW	2491	620 (24.9%)	373 (15.0%)	314 (12.6%)	551 (22.1%)	250 (10.0%)
Maternal BMI classes	Comparison population, only term-born singletons born ≥ 37 GW
< 25 kg/m2	1442	306 (21.2%)	186 (12.9%)	145 (10.1%)	264 (18.3%)	150 (10.4%)
25–29.9 kg/m2	600	159 (26.5%)	93 (15.5%)	81 (13.5%)	144 (24.0%)	46 (7.7%)
≥ 30 kg/m2	449	155 (34.5%)	94 (20.9%)	88 (19.6%)	143 (31.8%)	54 (12.0%)
≥ 25 kg/m2	1049	314 (29.9%)	187 (17.8%)	169 (16.1%)	287 (27.4%)	100 (9.5%)
GemaZ study cohort, all singletons
All GW	95	20 (21.1 %)	13 (13.7 %)	11 (11.6 %)	15 (15.8 %)	6 (6.3 %)
< 37 GW	5	1 (20%)	0	1 (20%)	1 (20%)	0
≥ 37 GW	90	19 (21.1%)	13 (14.4%)	10 (11.1%)	14 (15.6%)	6 (6.6%)
Maternal BMI classes	GemaZ study cohort, only term-born singletons born ≥ 37 GW
< 25 kg/m2	13	4 (30.8%)	3	2	3	2
25–29.9 kg/m2	31	4 (12.9%)	2	2	4	1
≥ 30 kg/m2	46	11 (23.9%)	8	6	7	3
≥ 25 kg/m2	77	15 (19.5%)	10 (13.0%)	8 (10.4%)	11 (14.3%)	4 (5.2%)

The overall macrosomia rate irrespective of BMI for all term-born infants in the study just missed statistical significance at 21.1% (n = 19/90; 95% CI 13.2%–31.0%, p = 0.083). In contrast, the overall macrosomia rate of the neonates born ≥ 37 GW from the target group with a preconception BMI ≥ 25 kg/m² was 19.5% (n = 15/77; 95% CI: 11.3%–30.1%, p = 0.026) and was therefore significantly below the adjusted comparison rate ([Fig. 3]).

Fig. 3 Relative frequency of macrosomia of term-born singletons of women with a maternal BMI ≥ 25 kg/m² born in UFK Rostock in 2020, after BMI adjustment according to BMI distribution in the GemaZ study cohort and in the GemaZ study cohort (with 95% CI [confidence intervals]).

Sensitivity analysis showed a significant reduction compared to the comparison cohort for the macrosomia criterion “length-related weight > 90th percentile” for both the overall cohort of term-born neonates and for the subgroup of term-born singletons born to mothers with a BMI ≥ 25 kg/m² ([Table 3]). Analysis also showed a trend to reduction for the other macrosomia definitions (birth weight > 4000 g, birth weight > 90th percentile and birth weight adjusted for maternal data > 90th percentile).

Table 3 Frequency of macrosomia according to Voigt et al. [23] of term-born singletons born to the GemaZ study cohort compared to BMI-adjusted comparative rate for births born in UFK Rostock in 2020.

Definition	UFK 2020 rate, %	Adjusted comparative UFK 2020 rate, %*	Macrosomia in the GemaZ cohort, n/N	Point estimation rate, % (95% CI)	P value
BMI = body mass index; CI = confidence interval; GW = week(s) of gestation; UFK = University Gynecological Hospital * Adjustment for BMI distribution in the GemaZ cohort using weighted means
All singleton births born ≥ 37 GW
≥ 4000 g	15.0	17.9	13/90	14.44 (7.92–23.43)	0.491
Birth weight > 90th percentile (LGA)	12.6	16.1	10/90	11.11 (5.46–19.49)	0.250
Length-related birth weight > 90th percentile	22.1	27.2	14/90	15.56 (8.77–24.72)	0.012
Birth weight > 90th percentile after adjustment for maternal data	10.0	10.3	6/90	6.67 (2.49–13.95)	0.301
Overall macrosomia rate	24.9	29.8	19/90	21.11 (13.21–30.99)	0.083
Only singleton births at term ≥ 37 GW born to mothers with a BMI ≥ 25 kg/m2
≥ 4000 g	17.8	18.7	10/77	12.99 (6.41–22.59)	0.242
Birth weight > 90th percentile (LGA)	16.1	16.1	8/77	10.39 (4.59–19.45)	0.214
Length-related birth weight > 90th percentile	27.4	28.7	11/77	14.29 (7.35–24.13)	0.005
Birth weight >90th percentile after adjustment for maternal data	9.5	10.3	4/77	5.19 (1.43–12.77)	0.186
Overall macrosomia rate	29.9	31.3	15/77	19.48 (11.33–30.09)	0.026

Maternal weight changes and prevalence of GDM

The majority of normal-weight test persons (n = 11/13, 84.6%) had a physiological weight gain consistent with the recommendation of the IOM. The physiological pregnancy weight gain of 54.5% of overweight test persons (n = 18/33) and 44.9% of obese test persons (n = 22/49) was within the recommended range.

The higher the BMI category, the higher the rate of excessive weight gain during pregnancy which increased from 15.4% (normal weight) to 45.5% (overweight) to 55.1% (obese) ([Table 4]).

Table 4 Weight changes in the GemaZ cohort and prevalence of GDM. Classification according to BMI class. Weight gain based on the recommendation of the IOM.

	All BMI n = 95	BMI < 25 kg/m2 n = 13	BMI ≥ 25 kg/m2 n = 33	BMI ≥ 30 kg/m2 n = 49	Total p value
BMI = body mass index; GDM = gestational diabetes mellitus; IOM = Institute of Medicine
Absolute weight gain					0.001
−9 to 0 kg	4	0	0	4
1 to 4 kg	4	0	1	3
5 to 9 kg	26	3	8	15
10 to 12 kg	22	6	9	7
13 to 16 kg	20	2	8	10
17 to 33 kg	19	2	7	10
Weight change, range		+5 to +18 kg	+4 to +23 kg	−9 to +33 kg
Weight gain according to the recommendation of the IOM	Below to adequate	11 (84.6%)	18 (54.5%)	22 (44.9%)
	Excessive	2 (15.4%)	15 (45.5%)	27 (55.1%)
Gestational diabetes mellitus
No GDM	58 (61.1%)	12 (92.3%)	23 (69.7%)	23 (46.9%)
Managed with diet	14 (14.7%)	1 (7.7%)	7 (21.2%)	6 (12.2%)
Required insulin	23 (24.2%)	0 (0.0%)	3 (9.1%)	20 (40.8%)

Overall GDM frequency was 38.9% (n = 37/95); the higher the BMI category, the higher GDM frequency (7.7% vs. 30.3% vs. 53.0%). The relative percentage of GDM managed with insulin similarly increased (0% vs. 30% vs. 76.9%).

Evaluation of questionnaires

The attendance rate at the education sessions decreased slightly over the course of pregnancy and the attendance rate at the final session was 73% (n = 73/99) ([Table 1]). After the first education session, 97% (n = 96/99) of participants completed the evaluation questionnaire and 100% (n = 73) of participants completed the questionnaire after the third session. The quality of the training sessions was overwhelmingly assessed as good to very good (Table S2) (supplementary material, online). The recommendations on diet and nutrition were new for 52% of the participants (Table S3) (supplementary material, online). All the pregnant women, including those who were already familiar with the details presented in the first training session, came away from the event with information which was relevant for their daily life. Almost everyone rated the training materials as useful and an interest in nutritional issues going beyond the counseling sessions was awakened in 96% (1st session) and 89% (3rd session) of participants. At the end of the 3rd training session, 97% of the test persons stated that counseling had inspired them to pay more attention to healthy eating after the end of the pregnancy.

According to their own assessment, 8% of the participants had not previously thought much about a healthy diet and 32% of participants had only partially considered it; only about 27% of test persons had tried to ensure that they ate a healthy diet prior to the first counseling session (Table S4) (supplementary material, online). For 93% of the test persons, the information conveyed in the session was easy to understand and they did not feel overwhelmed by the information. After the last consultation, 85% of women planned to concentrate more on their diet in the future. More than half were motivated to eat healthier in the future (Table S4) (supplementary material, online). The counseling was overwhelmingly evaluated as positive. 98% of the test persons wanted the counseling sessions to be integrated in the routine antenatal care offered to pregnant women (Table S4) (supplementary material, online).

Discussion

Maternal overweight and obesity, and excessive weight gain in pregnancy increase the risk of complications of pregnancy, fetal macrosomia, and infant obesity and predispose the infant to develop metabolic disorders and chronic disease in later life [6] [11] [19] [27] [28] [29] [30].

There are some indications that an unfavorable intrauterine milieu of abundance may affect the fetal energy metabolism prenatally and may also affect fetal metabolism postnatally over the longer term [17] [19] [20] [31] [32]. A possible cause of fetal macrosomia is a (pre-)diabetic metabolic state, often found in obese women, characterized by insulin resistance, high maternal blood sugar levels, and elevated placental glucose transport [33]. The HAPO study of more than 23000 mother-child pairs found that even a moderately elevated maternal blood glucose level identified using the 75 g oral glucose tolerance test between week 24 and 32 of gestation led to an increase in the prevalence of LGA infants [10]. One prospective study reported that high preconception BMI did not just lead to higher fetal BMI and total body fat but was also associated with changes to metabolic parameters at the age of 6–10 years. This included increased insulin resistance and higher leptin levels [16].

A number of controlled studies, some of which investigated large randomized cohorts, have investigated whether lifestyle counseling or dietary changes could have a positive influence [34] [35] [36]. A summary of recent meta-analyses shows that these measures were largely unable to fulfil expectations [37] [38]. Weight gain during pregnancy was most likely to be affected by measures. No effects on neonatal birth weight, macrosomia rates and neonatal obesity were found [38]. One meta-analysis studied follow-up data on the development of children from the age of one month to seven years and was unable to detect an influence on weight and BMI development as a function of lifestyle interventions during pregnancy [39]. A meta-analysis based on individual participant data with a follow-up of between three and five years (six studies with n = 2529) of pregnant women with a BMI ≥ 25 kg/m² who were randomized to receive dietary and/or a lifestyle intervention or standard antenatal care came to the same conclusion [40]. About 30% of these children between 3–5 years of age had a standard BMI score above the 90th percentile, irrespective of the previous intervention. The long-term results of the LIMIT study with up to ten years of follow-up have confirmed the high rate of overweight and obese children in this high-risk cohort as well as the lack of any effect of lifestyle interventions in pregnancy [41]. Preconception factors such as age and initial BMI of the pregnant women as well as pre- and postnatal factors such as nutrient availability to the fetus, maternal weight gain, and physical exercise up until the birth, rate and duration of breastfeeding, and the relation between energy supply and energy metabolism in later life are likely to be relevant. An intervention limited to the pregnancy alone does not appear to be sufficient [42] [43].

A general problem was that women found it difficult to implement the recommendations to increase physical activity. This also applied during pregnancy where the reported adherence rates under study conditions were just 50% despite the comparatively higher motivation in this cohort [44].

As part of the cooperation project “Gesund leben in der Schwangerschaft” (GeliS) [= Healthy Living in Pregnancy], the option to provide pregnant women with health counseling in the context of routine antenatal care in Germany was evaluated. Maternal weight gain in 1152 pregnant women in the intervention group (three health counseling sessions) compared to weight gain in 1134 participants in the comparison group (standard antenatal care in accordance with the German Maternity Guidelines) was investigated. Lifestyle counseling was provided by previously trained gynecologists, midwives, and physician assistants, certified dieticians were not involved [36]. More than 90% of the intervention group receiving standard antenatal care attended all three training sessions. The analysis of implemented dietary measures, however, showed that total energy intake did not decrease despite selective dietary changes following counseling [45]. The expectation that birth weight would be reduced by implementing the recommendations on healthy eating was not fulfilled [46]. However, an association was found between implementation of the recommendations on physical activity and lower birth weight [47]. When maternal weight gain in the GeliS study was compared with maternal weight gain in the GemaZ study, the rate of excessive weight gain in the group of obese participants was 9% lower in the GemaZ study than in the intervention arm of the GeliS study [36]. The GemaZ study investigated the impact of three nutrition counseling sessions provided to pregnant women by certified dieticians on the overall neonatal macrosomia rate and, in more detail, on macrosomia rates calculated according to varying criteria. Test persons were provided with theoretical information on maternal diet and pregnancy-specific aspects of metabolic regulation and the relationship with intrauterine fetal growth. The training content also included practical recommendations for healthy eating and physical activity. 73.7% of test persons still attended the third nutrition counseling session ([Table 1]). Counseling was overwhelmingly rated as positive and participants supported the inclusion of nutrition counseling in standard antenatal care.

In the GemaZ study, the overall neonatal macrosomia rate of term-born singletons born to test persons with a BMI ≥ 25 kg/m² decreased compared to the comparison group ([Table 3]). A comparison of our results with those of other studies is difficult because of the definition of macrosomia chosen for the GemaZ study. An analysis of the different macrosomia definitions showed that the effect can be primarily attributed to a decrease in the percentage of children with a length-related birth weight above the 90th percentile. With regard to the other macrosomia definitions, analysis only showed a trend toward a decrease in frequency. The use of length-related birth weight, which has some parallels with BMI, is possibly the most sensitive macrosomia criterion and therefore useful for interventional studies, but it is still rarely used. Particularly noteworthy was the high percentage of macrosomic infants when this criterion was used. However, the prognostic significance for developments later in childhood remains unclear as studies are lacking.

This study has some limitations. Because the recruitment of pregnant women was slow, the case number fell considerably short of the planned target number, meaning that the study must be assessed as underpowered. Expanding the study protocol to include normal-weight women additionally reduces the scope of the results. The reasons for the poor recruitment levels were not investigated further but were due, at least in part, to the COVID-19 pandemic. In view of the difficult recruitment conditions, it must be assumed that the study population consisted of a group of highly motivated women. This must have contributed to the positive outcome of the study. It is therefore not possible to directly transfer these results to a non-selected population. The one-arm design of the study additionally complicates the interpretation of results. Nevertheless, these results support the benefit of a lifestyle intervention for motivated high-risk patients.

Conclusion

A reduction in the overall macrosomia rates of term-born singletons born to women with a BMI ≥ 25 kg/m² and singletons with length-related birth weight above the 90th percentile irrespective of maternal BMI appears to be possible by means of targeted nutrition advice given in pregnancy. Certified nutrition counseling provided with the aim of primary obesity prevention should become a mandatory part of antenatal care. Based on recent studies, lifestyle interventions should already be initiated prior to conception and must be continued over the longer term for mother and child.

Supplementary Material

• Table S1: Macrosomia rate of term-born neonates in % based on preconception maternal BMI. Percentage of macrosomic term-born singletons as a function of preconception maternal BMI and overall macrosomia rates in 2014 and 2017–2020.

• Table S2: Assessment of the quality of the counseling after the 1st and 3rd sessions.

• Table S3: Assessment of the educational contents after the 1st and 3rd sessions.

• Table S4: Personal data after the 1st and 3rd sessions.

• Fig. S1: Example of neonatal classification (data from Voigt M et al. [23]). In addition to gestational age, the classification takes account of fetal and maternal biometric and gender-specific factors.

Conflict of Interest

The authors declare that they have no conflict of interest.

Acknowledgement

We would like to thank the dieticians involved in the study Ms. Ulrike Bräutigam, Ms. Cordula Parlow, Ms. Anke Geschke, Ms. Birgit Schmarbeck, Ms. Marianne Prabel and cand. med. Anne Kamps for their organizational help. Our thanks also go to Prof. Dr. Günther Kundt for his initial statistical advice prior to submitting the application. The Federal State of Mecklenburg Vorpommern, represented by the Ministry for Economic Affairs, Labor and Health Mecklenburg-Vorpommern fully funded this study, with costs amounting to € 45000 (contact persons: Dr. Kati Möbius-Hastedt and Christina Posekardt).

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Publication History

Received: 12 August 2024

Accepted after revision: 09 March 2025

Article published online:
12 June 2025