Quick search in Citations
This JournalAnywhereCitation
Advanced Search
Research Article
Originally Published 22 July 2013
Free Access

Maternal Prepregnancy Body Mass Index and Their Children’s Blood Pressure and Resting Cardiac Autonomic Balance at Age 5 to 6 Years

Maaike G.J. Gademan, Manon van Eijsden, Tessa J. Roseboom, Joris A.M. van der Post, Karien Stronks, and Tanja G.M. VrijkotteAuthor Info & Affiliations
Hypertension
Volume 62, Number 3
https://doi.org/10.1161/HYPERTENSIONAHA.113.01511
Track CitationsAdd to favorites
PDF/EPUB

Abstract

Adverse intrauterine conditions can program hypertension. Because one of the underlying mechanisms is thought to be cardiac autonomic balance, we investigated the association between prepregnancy body mass index (BMI) and blood pressure and indicators of the autonomic balance in the child at age 5 to 6 years. Also investigated was whether these associations were mediated by standardized birth weight and child BMI. Pregnant women (n=3074) participating in the Amsterdam Born Children and their Development study completed a questionnaire at gestational week 14. At age 5 to 6 years, offspring’s sympathetic drive (pre-ejection period), parasympathetic drive (respiratory sinus arrhythmia), and heart rate were measured by electrocardiography and impedance cardiography at rest. Blood pressure was assessed simultaneously. After adjusting for possible maternal/offspring confounders, prepregnancy BMI was positively linearly associated with diastolic blood pressure (β=0.11 mm Hg; 95% confidence interval, 0.05–0.17), systolic blood pressure (β=0.14 mm Hg; 95% confidence interval, 0.07–0.21), but not with heart rate, sympathetic or parasympathetic drive. After adding birth weight and child BMI to the model, the independent effect size of prepregnancy body mass index on systolic blood pressure (β=0.07 mm Hg; 95% confidence interval, 0.00–0.14) and diastolic blood pressure (β=0.07 mm Hg; 95% confidence interval, 0.01–0.13) decreased by ≈50%. Birth weight did not mediate these relationships, but was independently and negatively associated with blood pressure. Child BMI was positively associated with blood pressure and partly mediated the association between prepregnancy BMI and blood pressure. In conclusion, higher prepregnancy BMI is associated with higher blood pressure in the child (aged 5–6 years) but does not seem to be attributable to early alterations in resting cardiac autonomic balance. Child BMI, but not birth weight, mediated the association between prepregnancy BMI and blood pressure.

Introduction

See Editorial Commentary, pp 457–458
With the drastic increase in the prevalence of obesity, there is an exponential increase in the prevalence of obesity among women in the reproductive age group. Currently, in the United States, nearly two thirds of the women of reproductive age are overweight or obese.1 This causes an increased risk for pregnancy complications.2
Besides short-term pregnancy complications, maternal obesity can also have serious consequences for their offspring’s health later in life. There is increasing evidence that maternal metabolism and intrauterine conditions can program the development and growth of their children.3–5 Although the exact mechanisms remain unclear, animal studies have shown that maternal obesity can program the child for obesity and related cardiometabolic disorders such as hypertension.6–8
One of the pathways through which maternal obesity could program their offspring for hypertension is that maternal overweight/obesity may cause a shift in the offspring’s cardiac autonomic balance toward more sympathetic activation. This seems plausible as one of the pathways via which blood pressure is regulated is by autonomic control.9,10 A rat study on the effect of maternal obesity on blood pressure, and blood pressure regulatory pathways in juvenile and adult offspring, showed that hypertension in the offspring of obese rats may arise from persistent sympathoexcitatory hyper-responsiveness acquired in the early stages of development.11
Although the relationship between maternal obesity and blood pressure in the child has been studied,12–14 little is known about the association between maternal obesity, child blood pressure, and the excitation of the autonomic nervous system. One study investigating this association in 41 fetuses found that maternal prepregnancy body mass index (pBMI) was positively associated with cardiac sympathetic activation during labor.15 However, in the latter study, blood pressure was not assessed, and (to our knowledge) the consequences after birth have not yet been examined.
Therefore, the present study investigates the association between pBMI and blood pressure in the child at age 5 to 6 years. We hypothesized that elevated sympathetic nervous system activity is programmed in utero as an underlying mechanism; therefore, we investigated the association between pBMI and the offspring’s heart rate (HR), and sympathetic and parasympathetic drive. Second, we assessed whether birth weight (BW) mediated this association because BW lies within the pathways via which maternal pBMI could program the fetus for hypertension either by decreased BW, attributable to, for instance, placental insufficiency or increased maternal plasma leptin levels,16,17 or by increased BW through increased glucose and fatty acid exposure.6,7,18 Third, we investigated whether child BMI could be a mediating pathway reflecting familial environmental factors that could result in higher offspring blood pressure.

Methods

Study Population

The present study is part of the Amsterdam Born Children and their Development (ABCD) study, a large community-based birth cohort.19 The study protocol was approved by the Medical Ethics Committees of the Amsterdam hospitals involved and the Registration Committee of Amsterdam. All participants provided written informed consent. Details of the study design are described elsewhere.20
In short, between January 2003 and March 2004, all pregnant women living in Amsterdam were invited to participate in the ABCD study by their obstetric care provider at their first antenatal care visit. After inclusion, women were asked to fill out a questionnaire that covered sociodemographic characteristics, medical history, height, weight, and lifestyle. In the questionnaire, permission was requested for follow-up. When the children turned 5 years, the mothers received another questionnaire, including an informed consent sheet for the health check at 5 years. For the current study, only mothers with singletons who participated in the health check, and children without congenital malformations of the nervous system, cardiovascular system, chromosomal deviations, and multiple malformations were included (Figure S1 in the online-only Data Supplement).

Independent Variables

Prepregnancy Body Mass

pBMI was based on height and weight as reported in the pregnancy questionnaire. Missing values were imputed for maternal height (1.9% missing) and prepregnancy weight (7.7% missing) by a random imputation procedure using linear regression analysis and other variables known to be associated with maternal height and weight, respectively.21

Birth Weight

Children’s BW, parity (primiparous: yes/no), gestational age (≈90% by echo), and sex were available from the Youth Health Care Registration. BW was standardized for sex, gestational age, and parity (standardized [std] BW) using reference values from the Dutch Perinatal Registration (www.perinatreg.nl)22 to have a proxy for intrauterine growth.

Dependent Variables

Blood Pressure, HR, Parasympathetic, and Sympathetic Activation

Blood pressure, HR, pre-ejection period (PEP; a derivate of sympathetic nervous system activity),23 and respiratory sinus arrhythmia (RSA; a derivative of parasympathetic nervous system activity)24 were measured during the health check performed at age 5 to 6 years.20
To assess PEP and RSA, the VU University-Ambulatory Monitoring System (VU-AMS, Amsterdam, The Netherlands) was used.23 Reliability and validity and recording methodology aspects of this device have been described previously.23 Measurement of blood pressure, HR, PEP, and RSA was as follows: first, the electrodes for the 3-lead ECG and the 4-lead impedance cardiogram were attached; then the child lay in supine position. After 1 minute of rest in which a test blood pressure was measured (Omron Healthcare Inc, Bannockburn, IL), 6 minutes of VU-AMS recording took place from which HR, PEP, and RSA in lying position were assessed. This was followed by another 2 minutes of lying supine in which blood pressure was measured twice. Then the child was seated at a table and acclimatized for 1 minute, followed by 4 minutes of sitting at rest during which VU-AMS recording took place again. Subsequently, blood pressure was measured twice. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were calculated by taking the mean values of the repeated measurements. Blood pressure was measured with the Omron 750 IT (Omron Healthcare Inc, Bannockburn, IL) with its small cuff (arm circumference, 17–22 cm) that is validated in children.25
RSA was defined as the peak valley estimation.24 This was obtained automatically by subtracting the mean shortest interbeat interval during HR acceleration in the inspirational phase from the mean longest interbeat interval during deceleration in the expirational phase. PEP was defined as the time interval between the onset of ventricular depolarization (the Q-wave onset in the ECG) and the opening of the aortic valves (B-point in impedance cardiogram).23 This was scored manually in large-scale ensemble averages of the impedance cardiograms.26

Potential Confounders and Effect Modifiers

Maternal age, ethnicity, educational level, and smoking were available from the pregnancy questionnaire. Ethnicity was defined by maternal country of birth and the country of birth of her mother. Five ethnic categories were formed: Dutch, Turkish, Moroccan, Western African, and others. Years of education after primary school were considered as a proxy for socioeconomic status. Smoking during pregnancy was dichotomized (yes/no). Information on hypertension (no/pre-existent/pregnancy induced) was available by combining data from the pregnancy questionnaire and The Netherlands Perinatal Registry. The categories were classified in accordance with the guidelines of the International Society for the Study of Hypertension in Pregnancy (www.isshp.com).

Child BMI

During the health check measurements, the children wore their underwear only. Height was determined to the nearest mm with a Leicester portable height measure (Seca, Hamburg, Germany) and weight to the nearest 100 g using a weighing scale (Marsden MS-4102, Oxfordshire, UK).

Statistics

ANOVA with post hoc Tukey test was used to assess differences between maternal pBMI categories for continuous variables, and the χ2 test for categorical variables. An independent Student t test was used to compare the study population with the women lost to follow-up for continuous variables and the χ2 test for categorical variables. Departure from linearity within the regression models was tested with a likelihood ratio test using splines (R version 2.14.2); no proof was found for departure from linearity. Linear regression models assuming normally distributed errors were used to investigate the association between maternal pBMI and SBP, DBP, HR, RSA, and PEP. In the basic model, adjustments were made only for the child’s sex, height, and age at the time of outcome measurement (model 1). Interactions between sex and other variables were investigated. Subsequently, we adjusted for maternal characteristics that could confound the association (model 2) knowing ethnicity, gestational age, maternal age, maternal education, maternal height, hypertension during pregnancy, parity, and smoking. In model 3, std BW was added to investigate the role of intrauterine growth in the postulated associations. In the final model (model 4), we added the child’s BMI at age 5 to 6 years. Analyses were performed for all outcome measures in both lying and sitting positions. Because analyses of the outcome measures in both positions resulted in the same conclusions, only the results in lying position are reported; the rationale for this is that blood pressure measurements were more stable in lying position.

Results

Maternal and Child Characteristics

The present study included 3074 mothers with their singletons (Figure S1). Compared with the women lost to follow-up, the included women had a lower pBMI (23.0±3.8 versus 23.2±4.1 kg/m2; P<0.01), were more often Dutch origin (P<0.01), and had a higher education level, that is, 9.7±3.7 versus 8.0±4.2 years of education after primary school, respectively (P<0.01; see Table S1).
Table 1 presents the maternal/child characteristics by pBMI category. Obesity (BMI≥30) was prevalent in 5.2% of the mothers, and 16.2% were overweight (BMI, 25–29.9). Women in higher pBMI categories were more often of non-Dutch origin, had a higher prevalence of pregnancy or preexisting hypertension, were more likely to be multiparous, and their educational level was lower. Furthermore, children of women with a higher pBMI had a higher BW and a higher BMI at age 5 to 6 years.
Table 1. Maternal (N=3074) and Child Characteristics by Maternal Prepregnancy Body Mass Index
CharacteristicspBMI<18.5 n=143 (4.7%)pBMI=18.5–24.9 n=2271 (73.9%)pBMI=25–29.9 n=499 (16.2%)pBMI≥30 n=161 (5.2%)P Value
Maternal     
 Age, y30.3±5.032.06±4.531.4±5.131.6±5.1<0.001
 Ethnicity, %    <0.001
  Dutch48.365.851.143.4 
  Turkish3.53.03.85.0 
  Moroccan5.63.913.414.3 
  Western African6.33.99.210.6 
  Others35.723.422.426.1 
 Education after primary school, y9.28±3.910.1±3.58.5±4.07.5±3.9<0.001
 Primiparous, % yes61.557.647.541.0<0.001
 Hypertension    <0.001
  Preexisting hypertension, % yes02.35.811.8 
  Pregnancy hypertension, % yes2.18.011.011.8 
 Nonsmoking, % yes90.991.390.290.10.86
Child     
 Sex, % boys55.949.550.950.90.48
 Gestational age, d277±13279±12279±12278±150.07
 Birth weight, g3222±4983478±5353538±5523528±658<0.001
 Standardized birth weight0.95±0.121.01±0.121.02±0.131.03±0.14<0.001
 Age, y5.69±0.475.73±0.505.77±0.505.83±0.53<0.05
 BMI, kg/m214.9±1.315.4±1.416.0±1.616.4±2.1<0.001
ANOVA with post hoc Tukey test was used to assess differences between maternal pBMI categories for continuous variables, and the χ2 test for categorical variables. BMI indicates body mass index; and pBMI, maternal prepregnancy body mass index.
Table 2 reports the outcome measures by pBMI category. Offspring of women in the higher pBMI categories had significantly higher DBP/SBP values. There was a trend toward a higher HR in the lowest pBMI category (P=0.052). No differences in RSA and PEP were found between the pBMI categories.
Table 2. Offspring Blood Pressure, Heart Rate, and Activation of the Autonomic Nervous System by Maternal Prepregnancy Body Mass Index
ParametersOverall N=3074 100%pBMI<18.5 n=143 4.7%pBMI=18.5–24.9 n=2271 73.9%pBMI=25–29.9 n=499 16.2%pBMI≥30n=1615.2%P Value
DBP, mm Hg57.29±6.0956.35±5.3456.98±5.8958.31±6.6259.44±7.02<0.001
SBP, mm Hg99.45±7.3897.36±6.4099.22±7.19100.46±8.02101.56±8.12<0.001
HR, bpm85.38±9.9187.03±11.0685.10±9.6285.98±10.6985.95±9.980.052
RSA, ms124.45±58.67118.61±59.34124.03±58.17125.66±58.80131.77±64.420.25
PEP, ms71.5±9.070.5±8.471.6±8.071.3±9.172.2±8.50.10
ANOVA with post hoc Tukey test was used to assess differences between maternal pBMI categories. DBP indicates diastolic blood pressure; HR, heart rate; pBMI, maternal prepregnancy body mass index (kg/m2); PEP, pre-ejection period; RSA, respiratory sinus arrhythmia; and SBP, systolic blood pressure.

Maternal pBMI and Children’s Blood Pressure and Cardiac Autonomic Balance at Age 5 Years

Table 3 shows the linear associations between pBMI and the child’s SBP, DBP, HR, RSA, and PEP. We did not find significant interactions between sex and pBMI on any outcome variables (P>0.40), indicating similar associations for boys and girls. Both SBP and DBP were positively associated with pBMI when adjusted for offspring sex, age at time of outcome measurement, and child’s height. After adjusting for possible maternal confounders, the association between SBP, DBP, and pBMI was reduced. When adding std BW to the model, the associations between pBMI and SBP and DBP remained similar. Std BW was inversely associated with SBP and DBP. Finally, when adding child BMI to the model, the independent effect size of pBMI on SBP/DBP decreased by ≈50%. However, the impact of pBMI remained significant for DBP, and a trend existed for SBP (P=0.056).
Table 3. Linear Multivariable Associations Between Maternal Prepregnancy Body Mass Index and Systolic Blood Pressure, Diastolic Blood Pressure, Heart Rate, Respiratory Sinus Arrhythmia, and Pre-Ejection Period
Dependent VariablesModelBETA pBMI (CI)BETA BW (CI)BETA Child BMI (CI)
SBP, mm HgM10.19 (0.12 to 0.26)*  
 M20.14 (0.07 to 0.21)*  
 M30.16 (0.09 to 0.23)*−3.83 (−5.94 to −1.72)* 
 M40.07 (0.00 to 0.14)−5.82 (−7.87 to −3.76)*1.30 (1.12 to 1.48)*
DBP, mm HgM10.18 (0.12 to 0.23)*  
 M20.11 (0.05 to 0.17)*  
 M30.13 (0.07 to 0.19)*−3.81 (−5.56 to −2.05)* 
 M40.07 (0.01 to 0.13)*−5.02 (−6.76 to −3.28)*0.79 (0.64 to 0.93)*
HR, bpmM10.09 (−0.01 to 0.17)  
 M20.06 (−0.03 to 0.16)  
 M30.06 (−0.03 to 0.16)−0.57 (−3.44 to 2.30) 
 M40.09 (−0.01 to 0.19)−0.04 (−2.94 to 2.85)−0.34 (−0.59 to −0.10)*
RSA, msM10.56 (0.01 to 1.12)*  
 M20.38 (−0.21 to 0.97)  
 M30.47 (−0.13 to 1.06)−13.38 (−31.09 to 4.33) 
 M40.40 (−0.21 to 1.00)−14.95 (−32.81 to 2.91)1.04 (−0.50 to 2.57)
PEP, msM10.02 (−0.07 to 0.10)  
 M20.04 (−0.05 to 0.12)  
 M30.03 (−0.06 to 0.12)1.82 (−0.85 to 4.50) 
 M40.00 (−0.09 to 0.09)1.16 (−1.53 to 3.86)0.44 (0.21 to 0.67)*
M1: adjusted for offspring sex, age at time of outcome measurement and child’s height.
M2: Model 1 + adjusted for ethnicity, gestational age, maternal age, maternal education, maternal height, hypertension during pregnancy, parity, and smoking.
M3: Model 2 + standardized birth weight.
M3: BW: the standardized birth weight effect in model 3.
M4: Model 3 + child’s BMI.
M4: BMI child: the effect of the child’s BMI in model 4.
BETA BMI indicates effect size per unit increase in body mass index; BETA BW, effect size per unit increase in standardized birth weight; BETA Child BMI, effect size per unit increase in child body mass index; BW, standardized birth weight; DBP, diastolic blood pressure; HR, heart rate; pBMI, maternal prepregnancy body mass index; PEP, pre-ejection period; RSA, respiratory sinus arrhythmia; and SBP, systolic blood pressure.
*
P<0.05.
No associations between pBMI, HR, and PEP were found. RSA was positively associated with pBMI in the crude model only. After adjusting for possible confounders, this association was reduced and was no longer significant. Child BMI was positively associated with PEP and negatively associated with HR.
In absolute numbers, per unit maternal pBMI (model 2), there was an increase in SBP of 0.14 mm Hg and an increase in DBP of 0.11 mm Hg. Because we used std BW in the model, the decrease in SBP of 3.83 mm Hg should be interpreted as a decrease per unit BW (from 1 to 2). For example, for std BW, the decrease in SBP and DBP from the 2.5th percentile (std BW of 0.77) to the 97.5th percentile (std BW of 1.26) would be 1.87 mm Hg for SBP and 1.86 mm Hg for DBP. In the same model (model 3) for pBMI, the increase in SBP and DBP from the 2.5th percentile (pBMI of 17.96 kg/m2) to the 97.5th percentile (pBMI of 33.25 kg/m2) would be 2.44 mm Hg for SBP and 1.99 mm Hg for DBP. When adding child BMI to model 4, the impact of pBMI decreased to 1.07 mm Hg for both SBP and DBP. Child BMI had the highest absolute impact on blood pressure: the change in blood pressure from the 2.5th percentile (child BMI of 13.24 kg/m2) to the 97.5th percentile (child BMI of 19.22 kg/m2) was 7.77 mm Hg for SBP and 4.72 mm Hg for DBP.
Figure S2 shows the relation between SBP, DBP, std BW, and pBMI; std BW was divided into quintiles. Irrespective of BW, blood pressure increased with every pBMI category. We found no synergistic effect of pBMI and BW on blood pressure (P for interaction >0.45), However, pBMI and BW showed additive effects such that children with a low BW, from a mother with high pBMI, had the highest blood pressure.

Discussion

This study shows that a higher pBMI was associated with higher blood pressure in the child at age 5 to 6 years, but this was not the result of early alterations in resting cardiac autonomic balance because pBMI was not related to HR, PEP, and RSA. Low BW was also associated with higher blood pressures. Child BMI, but not standardized BW, mediated the association between pBMI and blood pressure.
Our finding that pBMI is positively associated with offspring blood pressure is in line with other epidemiological studies.12–14 Therefore, a high maternal pBMI is a risk factor for higher blood pressure in the offspring in later in life. Although we hypothesized that an elevated sympathetic nervous system activity programmed in utero was an underlying mechanism, no association was found between pBMI and sympathetic/parasympathetic drive. An earlier study showed an association between pBMI and fetal sympathetic activation,15 but these results were not confirmed in our study population. However, the latter study assessed sympathetic activation in fetuses during labor using a fetal ECG, whereas we measured older children with the VU-AMS device, that is, we measured cardiac autonomic balance at rest only, and did not investigate sympathetic hyper-responsiveness. The differences in outcome between these studies might be attributable to the differences in age and study protocols. To our knowledge, no other human studies have reported on the association between pBMI and activation of the autonomic nervous system at rest; this topic warrants further investigation.
Similar to others, we found that BW was inversely related to blood pressure27–30; no evidence was found for a U-shaped curve. Although Filler et al12 found a positive relation between high BW and high blood pressure, we could not confirm these findings; however, they did not use age, sex, and height standardization of blood pressure, and included hospitalized patients. In the present study, BW did not mediate the relation between pBMI and blood pressure but was independently and negatively associated with blood pressure. Thus, low BW is an independent risk factor for higher blood pressure later in life. Furthermore, our results indicate that high pBMI in combination with low BW led to the highest blood pressure in the child. Common genes related to both high blood pressure and growth retardation might explain this additive effect.31 On the other hand, the theory of predictive adaptive response may also be applicable. Placenta vascular dysfunction, which is more prevalent in obese pregnancies, could lead to nutrient and oxygen restriction to which the fetus adapts.32 After birth in an environment with abundance of food, these adaptations could have detrimental consequences for blood pressure regulation.33
As expected, child BMI was positively associated with blood pressure.34 Furthermore, child BMI mediated the association between pBMI and blood pressure of the child at age 5 to 6 years; in this association, the effect size of child BMI was high (an increase of 1 unit in child BMI increased SBP by 1.30 mm Hg). Also, the independent effect size of pBMI dropped by ≈50% after the addition of child BMI to the model. Therefore, it seems that familial environmental factors (family diet, physical activity patterns) are relatively important in this association. However, animal and human studies showed that prenatal nutrition may affect dietary preferences.8,35 Thus, besides a family pattern, a high caloric diet may also exert, in part, a programming effect. Furthermore, in the model with child BMI included, the association between pBMI and blood pressure remained significant. The increase of 1.07 mm Hg from the 2.5th to the 97.5th percentile seems a small change; however, as blood pressure tracks into adulthood, this increase could have serious consequences later.29 For instance the Bogalusa Heart Study showed that the prevalence of clinically diagnosed hypertension was much higher in subjects whose childhood SBP was in the top quintile: 18% versus 5% compared with subjects in every other quintile.36
We found a significant correlation between RSA at rest and blood pressure of the child (data not shown), but not between resting PEP and blood pressure. This was against expectation because sympathetic drive is one of the pathways via which blood pressure is regulated.9,10 However, we consider PEP to be a valid measure of sympathetic drive. This has been validated several times,23,26 also among 5-year-old children.37 Few studies have examined the association between the sympathetic drive and blood pressure in young children. Zhou et al38 performed a study in 9- to 11-year-olds and found that elevated blood pressure was associated with both altered sympathetic and vagal drive, measured by HR variability indices obtained by 24-hour Holter recordings. Again, the age difference and the measurement protocol (other indices, and an overall 24-hour measurement instead of measurement at rest) might explain the differences compared with our study.
Thus, although we found an association between pBMI and child blood pressure, and a correlation between RSA and blood pressure of the child, we found no evidence that pBMI programmed the autonomic nervous system of the offspring at rest toward a more sympathetic drive or less parasympathetic drive. This would imply that at the age of 5 to 6 years other mechanisms, such as epigenetics, endothelial dysfunction, the renin-angiotensin-aldosterone system, and vascular stiffness, play a role in the relationship between pBMI and blood pressure. For example, Martyn and Greenwald39 hypothesized that impaired elastin synthesis may be the underlying mechanism behind intrauterine growth retardation and high blood pressure later in life. Also, in a human study, pBMI was associated with methylation of a transcriptional coactivator involved in mitochondrial biogenesis and function (metabolic programming of the offspring via epigenetics).40 Further research is needed on the underlying mechanisms by which maternal adiposity programs the blood pressure of the child.

Strengths and Limitations

This large multiethnic cohort study collected extensive data on blood pressure and the autonomic nervous system and their confounders in 5- to 6-year-olds. However, as in most cohort studies, selective loss to follow-up occurred. The women lost to follow-up had a higher pBMI than our study participants, were more often of non-Dutch origin, and had a lower education level. However, this selective loss to follow-up was unlikely to distort our results because there are no reasons why the association between pBMI and child blood pressure would differ between these 2 populations. Moreover, because our study population is a relatively healthy cohort, it is more difficult to find significant associations because the number of overweight/obese women is relatively low. Furthermore, although we measured children in lying position, with good support of the upper arm, blood pressure is highly variable in children. This means that variation in blood pressure measurements is high. However, because of our large sample size, we were able to detect relatively small effect sizes. Also, because the children were measured during rest, it might be possible that fetal programming did result in altered reactivity in the autonomic nervous system.11 Hence, research on the topic of altered reactivity is necessary to further elucidate the effects of maternal pBMI on the offspring’s autonomic nervous system. And finally, pBMI of the mothers was self-reported; it is known that self-reported height tends to be slightly overestimated and weight underestimated, resulting in an underestimation of BMI.41 Nevertheless, such an underestimation would have occurred across almost the entire study population.

Conclusions

Higher prepregnancy BMI and lower BW are associated with higher blood pressure in the child at age 5 to 6 years. However, this does not seem to be the result of early alterations in resting cardiac autonomic balance.

Perspectives

Higher prepregnancy BMI and lower BW are associated with higher blood pressure in the child aged 5 to 6 years. Because of the tracking of childhood blood pressure into adulthood, we expect this increase in blood pressure to persist and become more distinct later in life. Therefore, the impact of this small increase at a young age might have detrimental effects on hypertension and cardiovascular disease later in life. We are aware of the need for our results to be confirmed by future research that would also address causality. However, the effects observed here already at early age, in combination with convincing animal studies and the epidemic proportion of overweight and obese women in the reproductive age, justify further study into preventive strategies to reduce prepregnancy BMI, for example, physical activity, and diet advice, already in the preconception phase, to improve offspring’s health.

Acknowledgments

We thank the following who participated in the study: the obstetric care workers, the primary schools, students, and youth healthcare centers in Amsterdam. We also thank Wim Busschers for his statistical advice and Rebecca Reynolds for her critical comments on drafts of this article.

Novelty and Significance

What Is New?

•
Extensive study on the relation between prepregnancy body mass index (BMI) and blood pressure and the autonomic balance in the child aged 5 to 6 years.
•
Also, we investigated the role of birth weight and child BMI within these associations.

What Is Relevant?

•
Higher prepregnancy BMI and lower birth weight are associated with higher blood pressure in the child aged 5 to 6 years. To improve offspring’s health, studies should investigate preventive strategies to reduce prepregnancy BMI in the preconception phase.

Summary

Higher prepregnancy BMI and lower birth weight are associated with higher blood pressure in the child at age 5 to 6 years. This does not seem to be the result of early alterations in resting cardiac autonomic balance.

Supplemental Material

File (hyp201629_supplemental_material.pdf)

References

1.
Hillemeier MM, Weisman CS, Chuang C, Downs DS, McCall-Hosenfeld J, Camacho F. Transition to overweight or obesity among women of reproductive age. J Womens Health (Larchmt). 2011;20:703–710.
Crossref
PubMed
Google Scholar
2.
Galtier-Dereure F, Boegner C, Bringer J. Obesity and pregnancy: complications and cost. Am J Clin Nutr. 2000;71(5 suppl):1242S–1248S.
Crossref
PubMed
Google Scholar
3.
Barker DJ, Osmond C. Infant mortality, childhood nutrition, and ischaemic heart disease in England and Wales. Lancet. 1986;1:1077–1081.
Crossref
PubMed
Google Scholar
4.
Barker DJP. Fetal Origins of Cardiovascular and Lung Disease. 1st ed. New York, NY: RCOG Press; 1998.
Google Scholar
5.
Gluckman PD, Hanson MA. Living with the past: evolution, development, and patterns of disease. Science. 2004;305:1733–1736.
Crossref
PubMed
Google Scholar
6.
Ramsay JE, Ferrell WR, Crawford L, Wallace AM, Greer IA, Sattar N. Maternal obesity is associated with dysregulation of metabolic, vascular, and inflammatory pathways. J Clin Endocrinol Metab. 2002;87:4231–4237.
Crossref
PubMed
Google Scholar
7.
Armitage JA, Khan IY, Taylor PD, Nathanielsz PW, Poston L. Developmental programming of the metabolic syndrome by maternal nutritional imbalance: how strong is the evidence from experimental models in mammals? J Physiol. 2004;561(pt 2):355–377.
Crossref
PubMed
Google Scholar
8.
Chang G, Gaysinskaya V, Karatayev O, Leibowitz SF. Maternal high-fat diet and fetal programming: Increases proliferation of hypothalamic peptide-producing neurons that increase risk for overeating and obesity. J Neurosci. 2008; 28:12107–12119.
Crossref
PubMed
Google Scholar
9.
Schlaich MP, Lambert E, Kaye DM, Krozowski Z, Campbell DJ, Lambert G, Hastings J, Aggarwal A, Esler MD. Sympathetic augmentation in hypertension: role of nerve firing, norepinephrine reuptake, and Angiotensin neuromodulation. Hypertension. 2004;43:169–175.
Crossref
PubMed
Google Scholar
10.
Mark AL. The sympathetic nervous system in hypertension: a potential long-term regulator of arterial pressure. J Hypertens Suppl. 1996;14:S159–S165.
PubMed
Google Scholar
11.
Samuelsson AM, Morris A, Igosheva N, Kirk SL, Pombo JM, Coen CW, Poston L, Taylor PD. Evidence for sympathetic origins of hypertension in juvenile offspring of obese rats. Hypertension. 2010;55:76–82.
Crossref
PubMed
Google Scholar
12.
Filler G, Yasin A, Kesarwani P, Garg AX, Lindsay R, Sharma AP. Big mother or small baby: which predicts hypertension? J Clin Hypertens (Greenwich). 2011;13:35–41.
Crossref
PubMed
Google Scholar
13.
Wen X, Triche EW, Hogan JW, Shenassa ED, Buka SL. Prenatal factors for childhood blood pressure mediated by intrauterine and/or childhood growth? Pediatrics. 2011;127:e713–e721.
Crossref
PubMed
Google Scholar
14.
Eisenman JC, Sarzynski MA, Tucker J, Heelan KA. Maternal prepregnancy overweight and offspring fatness and blood pressure: role of physical activity. Pediatr Exerc Sci. 2010;22:369–378.
Crossref
PubMed
Google Scholar
15.
Ojala T, Aaltonen J, Siira S, Jalonen J, Ekholm E, Ekblad U, Laitinen K. Fetal cardiac sympathetic activation is linked with maternal body mass index. Early Hum Dev. 2009;85:557–560.
Crossref
PubMed
Google Scholar
16.
Guilloteau P, Zabielski R, Hammon HM, Metges CC. Adverse effects of nutritional programming during prenatal and early postnatal life, some aspects of regulation and potential prevention and treatments. J Physiol Pharmacol. 2009;60 suppl 3:17–35.
PubMed
Google Scholar
17.
Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet. 2005;365:785–799.
Crossref
PubMed
Google Scholar
18.
Gorski JN, Dunn-Meynell AA, Hartman TG, Levin BE. Postnatal environment overrides genetic and prenatal factors influencing offspring obesity and insulin resistance. Am J Physiol Regul Integr Comp Physiol. 2006;291:R768–R778.
Crossref
PubMed
Google Scholar
19.
van Eijsden M, Vrijkotte TG, Gemke RJ, van der Wal MF. Cohort profile: the Amsterdam Born Children and their Development (ABCD) study. Int J Epidemiol. 2011;40:1176–1186.
Crossref
PubMed
Google Scholar
20.
van Dijk AE, van Eijsden M, Stronks K, Gemke RJ, Vrijkotte TG. Cardio-metabolic risk in 5-year-old children prenatally exposed to maternal psychosocial stress: the ABCD study. BMC Public Health. 2010;10:251.
Crossref
PubMed
Google Scholar
21.
Allison P. Missing Data. Thousand Oaks, CA: Sage Publications, 2001.
Google Scholar
22.
Visser GH, Eilers PH, Elferink-Stinkens PM, Merkus HM, Wit JM. New Dutch reference curves for birth weight by gestational age. Early Hum Dev. 2009;85:737–744.
Crossref
PubMed
Google Scholar
23.
Vrijkotte TG, van Doornen LJ, de Geus EJ. Overcommitment to work is associated with changes in cardiac sympathetic regulation. Psychosom Med. 2004;66:656–663.
Crossref
PubMed
Google Scholar
24.
Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation. 1996; 93:1043–1065.
Crossref
PubMed
Google Scholar
25.
Stergiou GS, Yiannes NG, Rarra VC. Validation of the Omron 705 IT oscillometric device for home blood pressure measurement in children and adolescents: the Arsakion School Study. Blood Press Monit. 2006;11:229–234.
Crossref
PubMed
Google Scholar
26.
Riese H, Groot PF, van den Berg M, Kupper NH, Magnee EH, Rohaan EJ, Vrijkotte TG, Willemsen G, de Geus EJ. Large-scale ensemble averaging of ambulatory impedance cardiograms. Behav Res Methods Instrum Comput. 2003;35:467–477.
Crossref
PubMed
Google Scholar
27.
Martinez-Aguayo A, Aglony M, Bancalari R, Avalos C, Bolte L, Garcia H, Loureiro C, Carvajal C, Campino C, Inostroza A, Fardella C. Birth weight is inversely associated with blood pressure and serum aldosterone and cortisol levels in children. Clin Endocrinol (Oxf). 2012;76:713–718.
Crossref
PubMed
Google Scholar
28.
Miles KL, McDonnell BJ, Maki-Petaja KM, Yasmin, Cockcroft JR, Wilkinson IB, McEniery CM; Enigma Study investigators. The impact of birth weight on blood pressure and arterial stiffness in later life: the Enigma Study. J Hypertens. 2011;29:2324–2331.
Crossref
PubMed
Google Scholar
29.
Chen W, Srinivasan SR, Berenson GS. Amplification of the association between birthweight and blood pressure with age: the Bogalusa Heart Study. J Hypertens. 2010;28:2046–2052.
Crossref
PubMed
Google Scholar
30.
Strufaldi MW, Silva EM, Franco MC, Puccini RF. Blood pressure levels in childhood: probing the relative importance of birth weight and current size. Eur J Pediatr. 2009;168:619–624.
Crossref
PubMed
Google Scholar
31.
Ylihärsilä H, Eriksson JG, Forsén T, Laakso M, Uusitupa M, Osmond C, Barker DJ. Interactions between peroxisome proliferator-activated receptor-gamma 2 gene polymorphisms and size at birth on blood pressure and the use of antihypertensive medication. J Hypertens. 2004;22:1283–1287.
Crossref
PubMed
Google Scholar
32.
Higgins L, Greenwood SL, Wareing M, Sibley CP, Mills TA. Obesity and the placenta: A consideration of nutrient exchange mechanisms in relation to aberrant fetal growth. Placenta. 2011;32:1–7.
Crossref
PubMed
Google Scholar
33.
Gluckman PD, Hanson MA, Morton SM, Pinal CS. Life-long echoes–a critical analysis of the developmental origins of adult disease model. Biol Neonate. 2005;87:127–139.
Crossref
PubMed
Google Scholar
34.
Weiss R, Dziura J, Burgert TS, Tamborlane WV, Taksali SE, Yeckel CW, Allen K, Lopes M, Savoye M, Morrison J, Sherwin RS, Caprio S. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med. 2004;350:2362–2374.
Crossref
PubMed
Google Scholar
35.
Mühlhäusler BS, Adam CL, McMillen IC. Maternal nutrition and the programming of obesity: The brain. Organogenesis. 2008;4:144–152.
Crossref
PubMed
Google Scholar
36.
Bao W, Threefoot SA, Srinivasan SR, Berenson GS. Essential hypertension predicted by tracking of elevated blood pressure from childhood to adulthood: the Bogalusa Heart Study. Am J Hypertens. 1995;8:657–665.
Crossref
PubMed
Google Scholar
37.
Quigley KS, Stifter CA. A comparative validation of sympathetic reactivity in children and adults. Psychophysiology. 2006;43:357–365.
Crossref
PubMed
Google Scholar
38.
Zhou Y, Guiling X, Wang J, Yang S. Cardiovascular risk factors significantly correlate with autonomic nervous system activity in children . Can J Card. 2012;66:656−663.
Google Scholar
39.
Martyn CN, Greenwald SE. Impaired synthesis of elastin in walls of aorta and large conduit arteries during early development as an initiating event in pathogenesis of systemic hypertension. Lancet. 1997;350:953–955.
Crossref
PubMed
Google Scholar
40.
Gemma C, Sookoian S, Alvariñas J, García SI, Quintana L, Kanevsky D, González CD, Pirola CJ. Maternal pregestational BMI is associated with methylation of the PPARGC1A promoter in newborns. Obesity (Silver Spring). 2009;17:1032–1039.
Crossref
PubMed
Google Scholar
41.
Stewart AW, Jackson RT, Ford MA, Beaglehole R. Underestimation of relative weight by use of self-reported height and weight. Am J Epidemiol. 1987;125:122–126.
Crossref
PubMed
Google Scholar

eLetters(0)

eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.

Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.

Sign In to Submit a Response to This Article

Information & Authors

Information

Published In

Go to Hypertension
Go to Hypertension

Representative confocal microscopic images showing transient receptor potential cation channel 6 (TRPC6) expression in glomeruli from different groups of mice; synaptopotin was used as podocyte marker. Nucleotide-binding oligomerization domain containing 2 (NOD2) deficiency ameliorated renal injury and reduced TRPC6 expression in mice with hyperhomocysteinemia (hHcys). FF indicates folate free; and WT, wild type. (See page 506.)

Hypertension
Volume 62 • Number 3 • September 2013
Pages: 641 - 647
PubMed: 23876476

Copyright

© 2013 American Heart Association, Inc.

Versions

You are viewing the most recent version of this article.

History

Received: 8 April 2013
Revision received: 25 April 2013
Accepted: 17 June 2013
Published online: 22 July 2013
Published in print: September 2013

Permissions

Request permissions for this article.

Keywords

  1. autonomic nervous system
  2. fetal development

Subjects

  1. Epidemiology
  2. Etiology

Authors

Affiliations

Maaike G.J. Gademan
From the Department of Public Health (M.G.J.G., K.S., T.G.M.V.), Department of Obstetrics & Gynaecology (T.J.R., J.A.M.v.d.P.), and Department of Clinical Epidemiology, Biostatistics and Bioinformatics (T.J.R.), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Department of Epidemiology, Documentation and Health Promotion, Public Health Service of Amsterdam (GGD), Amsterdam, The Netherlands (M.v.E.); and Department of Health Sciences, VU University, Amsterdam, The Netherlands (M.v.E.).
View all articles by this author
Manon van Eijsden
From the Department of Public Health (M.G.J.G., K.S., T.G.M.V.), Department of Obstetrics & Gynaecology (T.J.R., J.A.M.v.d.P.), and Department of Clinical Epidemiology, Biostatistics and Bioinformatics (T.J.R.), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Department of Epidemiology, Documentation and Health Promotion, Public Health Service of Amsterdam (GGD), Amsterdam, The Netherlands (M.v.E.); and Department of Health Sciences, VU University, Amsterdam, The Netherlands (M.v.E.).
View all articles by this author
Tessa J. Roseboom
From the Department of Public Health (M.G.J.G., K.S., T.G.M.V.), Department of Obstetrics & Gynaecology (T.J.R., J.A.M.v.d.P.), and Department of Clinical Epidemiology, Biostatistics and Bioinformatics (T.J.R.), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Department of Epidemiology, Documentation and Health Promotion, Public Health Service of Amsterdam (GGD), Amsterdam, The Netherlands (M.v.E.); and Department of Health Sciences, VU University, Amsterdam, The Netherlands (M.v.E.).
View all articles by this author
Joris A.M. van der Post
From the Department of Public Health (M.G.J.G., K.S., T.G.M.V.), Department of Obstetrics & Gynaecology (T.J.R., J.A.M.v.d.P.), and Department of Clinical Epidemiology, Biostatistics and Bioinformatics (T.J.R.), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Department of Epidemiology, Documentation and Health Promotion, Public Health Service of Amsterdam (GGD), Amsterdam, The Netherlands (M.v.E.); and Department of Health Sciences, VU University, Amsterdam, The Netherlands (M.v.E.).
View all articles by this author
Karien Stronks
From the Department of Public Health (M.G.J.G., K.S., T.G.M.V.), Department of Obstetrics & Gynaecology (T.J.R., J.A.M.v.d.P.), and Department of Clinical Epidemiology, Biostatistics and Bioinformatics (T.J.R.), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Department of Epidemiology, Documentation and Health Promotion, Public Health Service of Amsterdam (GGD), Amsterdam, The Netherlands (M.v.E.); and Department of Health Sciences, VU University, Amsterdam, The Netherlands (M.v.E.).
View all articles by this author
Tanja G.M. Vrijkotte
From the Department of Public Health (M.G.J.G., K.S., T.G.M.V.), Department of Obstetrics & Gynaecology (T.J.R., J.A.M.v.d.P.), and Department of Clinical Epidemiology, Biostatistics and Bioinformatics (T.J.R.), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Department of Epidemiology, Documentation and Health Promotion, Public Health Service of Amsterdam (GGD), Amsterdam, The Netherlands (M.v.E.); and Department of Health Sciences, VU University, Amsterdam, The Netherlands (M.v.E.).
View all articles by this author

Notes

The online-only Data Supplement is available with this article at http://hyper.ahajournals.org/lookup/suppl/doi:10.1161/HYPERTENSIONAHA.113.01511/-/DC1.
Correspondence to Maaike G.J. Gademan, Academic Medical Center, Department of Public Health, P.O. Box 22660, 1100 DD Amsterdam, The Netherlands. E-mail [email protected]

Disclosures

None.

Sources of Funding

This study was financially supported by The Netherlands Organization for Health Research and Development (ZonMW, TOP grant: 40-00812-98-11010).

Metrics & Citations

Metrics

Citations

Download Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Select your manager software from the list below and click Download.

    • Anna L K Cochrane,
    • Michael P Murphy,
    • Susan E Ozanne,
    • Dino A Giussani,
    Pregnancy in obese women and mechanisms of increased cardiovascular risk in offspring, European Heart Journal, 45, 48, (5127-5145), (2024).https://doi.org/10.1093/eurheartj/ehae671
    Crossref
    • Oskar Matuszak,
    • Weronika Banach,
    • Bartosz Pogorzały,
    • Józef Muszyński,
    • Solyana Hailemelekot Mengesha,
    • Paweł Bogdański,
    • Damian Skrypnik,
    The Long-Term Effect of Maternal Obesity on the Cardiovascular Health of the Offspring–Systematic Review, Current Problems in Cardiology, 49, 1, (102062), (2024).https://doi.org/10.1016/j.cpcardiol.2023.102062
    Crossref
    • Shifa Yao,
    • Tian Yang,
    • Xiaoxiao Kong,
    • Yuanyuan Dang,
    • Ping Chen,
    • Mingli Lyu,
    The Influence of Maternal Condition on Fetal Cardiac Function during the Second Trimester, Diagnostics, 13, 17, (2755), (2023).https://doi.org/10.3390/diagnostics13172755
    Crossref
    • Agnieszka Strawa,
    • Ewa Skarżyńska,
    • Barbara Lisowska-Myjak,
    CZY NADWAGA LUB NIEDOWAGA MŁODYCH ZDROWYCH KOBIET W OKRESIE PREKONCEPCYJNYM MOŻE PROGNOZOWAĆ ZABURZONĄ HOMEOSTAZĘ HORMONÓW TARCZYCY ORAZ SKŁADU BIAŁEK W SUROWICY, Prospects in Pharmaceutical Sciences, 20, 1, (1-10), (2022).https://doi.org/10.56782/pps.4
    Crossref
    • Szimonetta Eitmann,
    • Péter Mátrai,
    • Dávid Németh,
    • Péter Hegyi,
    • Anita Lukács,
    • Bálint Bérczi,
    • László Márk Czumbel,
    • István Kiss,
    • Zoltán Gyöngyi,
    • Gábor Varga,
    • Márta Balaskó,
    • Erika Pétervári,
    Maternal overnutrition elevates offspring’s blood pressure—A systematic review and meta‐analysis, Paediatric and Perinatal Epidemiology, 36, 2, (276-287), (2022).https://doi.org/10.1111/ppe.12859
    Crossref
    • Paul D. Taylor,
    • Haotian Gu,
    • Hannah Saunders,
    • Federico Fiori,
    • Kathryn V. Dalrymple,
    • Priyanka Sethupathi,
    • Liana Yamanouchi,
    • Faith Miller,
    • Bethany Jones,
    • Matias C. Vieira,
    • Claire Singh,
    • Annette Briley,
    • Paul T. Seed,
    • Dharmintra Pasupathy,
    • Paramala J. Santosh,
    • Alan M. Groves,
    • Manish D. Sinha,
    • Philip J. Chowienczyk,
    • Lucilla Poston,
    • Lucilla Poston,
    • Andrew Shennan,
    • Annette Briley,
    • Claire Singh,
    • Paul Seed,
    • Jane Sandall,
    • Thomas Sanders,
    • Nashita Patel,
    • Angela Flynn,
    • Shirlene Badger,
    • Suzanne Barr,
    • Bridget Holmes,
    • Louise Goff,
    • Clare Hunt,
    • Judy Filmer,
    • Jeni Fetherstone,
    • Laura Scholtz,
    • Hayley Tarft,
    • Anna Lucas,
    • Tsigerada Tekletdadik,
    • Deborah Ricketts,
    • Carolyn Gill,
    • Alex Seroge Ignatian,
    • Catherine Boylen,
    • Funso Adegoke,
    • Elodie Lawley,
    • James Butler,
    • Rahat Maitland,
    • Matias Vieira,
    • Dharmintra Pasupathy,
    • Eugene Oteng-Ntim,
    • Nina Khazaezadeh,
    • Jill Demilew,
    • Sile O’Connor,
    • Yvonne Evans,
    • Susan O’Donnell,
    • Ari de la Llera,
    • Georgina Gutzwiller,
    • Linda Hagg,
    • Stephen Robson,
    • Ruth Bell,
    • Louise Hayes,
    • Tarja Kinnunen,
    • Catherine McParlin,
    • Nicola Miller,
    • Alison Kimber,
    • Jill Riches,
    • Carly Allen,
    • Claire Boag,
    • Fiona Campbell,
    • Andrea Fenn,
    • Sarah Ritson,
    • Alison Rennie,
    • Robin Durkin,
    • Gayle Gills,
    • Roger Carr,
    • Scott Nelson,
    • Naveed Sattar,
    • Therese McSorley,
    • Hilary Alba,
    • Kirsteen Paterson,
    • Janet Johnston,
    • Suzanne Clements,
    • Maxine Fernon,
    • Savannah Bett,
    • Laura Rooney,
    • Sinead Miller,
    • Paul Welsh,
    • Lynn Cherry,
    • Melissa Whitworth,
    • Natalie Patterson,
    • Sarah Lee,
    • Rachel Grimshaw,
    • Christine Hughes,
    • Jay Brown,
    • Kim Hinshaw,
    • Gillian Campbell,
    • Joanne Knight,
    • Diane Farrar,
    • Vicky Jones,
    • Gillian Butterfield,
    • Jennifer Syson,
    • Jennifer Eadle,
    • Dawn Wood,
    • Merane Todd,
    • Asma Khalil,
    • Deborah Brown,
    • Paola Fernandez,
    • Emma Cousins,
    • Melody Smith,
    • Jane Wardle,
    • Helen Croker,
    • Laura Broomfield,
    • Weight Concern,
    • Keith Godfrey,
    • Sian Robinson,
    • Sarah Canadine,
    • Lynne Greenwood,
    Lifestyle intervention in obese pregnancy and cardiac remodelling in 3-year olds: children of the UPBEAT RCT, International Journal of Obesity, 46, 12, (2145-2155), (2022).https://doi.org/10.1038/s41366-022-01210-3
    Crossref
    • Isabella Inzani,
    • Susan E. Ozanne,
    Programming by maternal obesity: a pathway to poor cardiometabolic health in the offspring, Proceedings of the Nutrition Society, 81, 3, (227-242), (2022).https://doi.org/10.1017/S0029665122001914
    Crossref
    • Nirajan Shrestha,
    • Simone Sleep,
    • Tessa Helman,
    • Olivia Holland,
    • James S. M. Cuffe,
    • Anthony V. Perkins,
    • Andrew J. McAinch,
    • John P. Headrick,
    • Deanne H. Hryciw,
    Maternal diet high in linoleic acid alters offspring fatty acids and cardiovascular function in a rat model, British Journal of Nutrition, 127, 4, (540-553), (2021).https://doi.org/10.1017/S0007114521001276
    Crossref
    • SC. Langley-Evans,
    Diet, maternal nutrition, and long-term health consequences, Molecular Nutrition: Mother and Infant, (3-27), (2021).https://doi.org/10.1016/B978-0-12-813862-5.00001-3
    Crossref
    • Tian Xie,
    • Fahimeh Falahi,
    • Tabea Schmidt‐Ott,
    • Tanja G. M. Vrijkotte,
    • Eva Corpeleijn,
    • Harold Snieder,
    Early Determinants of Childhood Blood Pressure at the Age of 6 Years: The GECKO Drenthe and ABCD Study Birth Cohorts, Journal of the American Heart Association, 9, 22, (2020)./doi/10.1161/JAHA.120.018089
    Abstract
  11. See more

View Options

View options

PDF and All Supplements

Download PDF and All Supplements

PDF/EPUB

View PDF/EPUB
Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Personal login Institutional Login
Save for later Item saved, go to cart
Purchase Options

Purchase this article to access the full text.

Purchase access to this article for 24 hours

Maternal Prepregnancy Body Mass Index and Their Children’s Blood Pressure and Resting Cardiac Autonomic Balance at Age 5 to 6 Years
Hypertension
  • Vol. 62
  • No. 3

Purchase access to this journal for 24 hours

Hypertension
  • Vol. 62
  • No. 3
Restore your content access

Enter your email address to restore your content access:

Note: This functionality works only for purchases done as a guest. If you already have an account, log in to access the content to which you are entitled.

Figures

Tables

Media

Share

Share

Share article link

Share

View full text|Download PDF

Comment Response