Preconception dietary intake and physical activity
van Elten, T.M.
2019
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van Elten, T. M. (2019). Preconception dietary intake and physical activity: The importance for future lifestyle
and health of two generations.
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PART II
Women’s lifestyle before and during
pregnancy and offspring’s cardiovascular
CHAPTER 5
Preconception lifestyle and cardiovascular
health in the offspring of overweight and
ABSTRACT
BackgroundWomen’s preconception lifestyle has important implications for the growth, development and health of their offspring. Yet little is known about the association between maternal preconception dietary intake and physical activity with cardiovascular health of the offspring. We therefore examined this association in a group of overweight/obese women (BMI≥29 kg/m2), who participated in a 6 months randomised preconception lifestyle intervention trial, and their offspring (N=46).
Methods
Preconception dietary intake and physical activity were assessed using a food frequency questionnaire and the Short QUestionnaire to ASsess Health-enhancing physical activity (SQUASH), respectively. Offspring cardiovascular health (i.e. BMI, waist:height ratio, systolic and diastolic blood pressure, fat mass and fat free mass, and pulse wave velocity) was measured at age 3-6 years. Linear regression analyses were used to examine the associations between maternal preconception lifestyle and offspring cardiovascular health.
Results
Higher preconception vegetable intake (per 10 gram/day) was associated with lower offspring diastolic blood pressure (Z-score: -0.05 [-0.08;-0.01]; P=0.007) and higher preconception maternal fruit intake (per 10 gram/day) was associated with lower offspring pulse wave velocity (-0.05 m/s [-0.10;-0.01]; P=0.03). Against our expectations, higher preconception intake of maternal sugary drinks was associated with a higher offspring fat free mass (0.54 kg [0.01; 1.07]; P=0.045).
Conclusion
BACKGROUND
Women’s preconception lifestyle has important implications for the growth, development and health of their offspring.1–3 Suboptimal conditions during the earliest stages of embryonic and foetal development have lasting consequences for cardiovascular and metabolic health, and thereby increase an individual’s risk of cardiovascular disease in later life.4 This phenomenon is known as developmental programming.5
Yet little is known about the association between maternal preconception dietary intake and physical activity, and cardiovascular health of the offspring.2 One study showed that higher preconception physical activity has been associated with lower infant weight gain and weight-for-length in 246 mother-child pairs.6 There is a lack of studies reporting about associations between maternal preconception dietary intake and offspring cardiovascular health. Previous research in pregnant women suggests there may be a dose-response relationship between maternal lifestyle behaviours during pregnancy and later life health of the offspring. For example, the higher the mothers’ scores on the Mediterranean Diet Score during pregnancy, the lower the offspring blood pressure.7 The LIFEstyle study was a large randomised controlled trial (RCT) studying the effects of a preconception lifestyle intervention in overweight and obese, infertile women.8,9 The six month preconception lifestyle intervention was successful in decreasing the intake of high caloric snacks and beverages10, reducing weight9, and improving cardiometabolic health in women by halving the odds for metabolic syndrome.11 We observed within the LIFEstyle study that individual changes in preconception lifestyle varied greatly among participants and also women in the control group changed their diet and physical activity to some extent.
We therefore here investigated preconception dietary intake and physical activity of overweight and obese women in association with offspring cardiovascular health. We hypothesised that women with a more healthy diet, i.e. higher vegetable and fruit consumption and lower intake of high caloric snacks and beverages, and with more moderate to vigorous physical activity (MVPA) before conception, have offspring with a lower BMI, lower waist:height ratio, lower blood pressure, lower fat mass and higher fat free mass, and lower pulse wave velocity (PWV). Additionally, since both dietary intake and physical activity contribute to energy balance and might interact12, we examined both maternal lifestyle behaviours into one model.
METHODS
Study populationThe LIFEstyle study was a large multicentre RCT conducted between 2009 and 2014 in the Netherlands (Dutch trial register; NTR 1530).13 The design and results of the LIFEstyle study are described in detail previously.8,9 In brief, the original study population consisted of 577 infertile women between 18 and 39 years old, with a BMI of ≥29 kg/m2. Participants were randomised into a six-month structured lifestyle intervention program (intervention group), or promptly started infertility care as usual (control group). The intervention was based on the Dutch dietary guidelines of 200614 and the Dutch physical activity guidelines.15 All singleton children, conceived within 24 months after randomisation of their mothers into the LIFEstyle study were eligible to participate. The follow-up study (WOMB project) was conducted in 2016 and 2017 when the children were aged 3-6 years old.16
The LIFEstyle study as well as the WOMB project were conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures were approved by the Medical Ethics Committee of the University Medical Centre Groningen, the Netherlands (METc 2008/284). Written informed consent was obtained from all female participants at the start of the LIFEstyle study as well as from both parents for the follow-up study.
Maternal preconception diet and physical activity
During participation in the LIFEstyle study, all women were asked to fill out a 33-item food frequency questionnaire (FFQ) and the Short QUestionnaire to ASsess Health-enhancing physical activity (SQUASH) four times: at the start of the intervention and at three, six and twelve months after randomisation into the trial. Maternal dietary intake and physical activity preconception was determined by the last questionnaire filled out before pregnancy.
(crisps, pretzels, nuts and peanuts; handful/week) and sweet snacks (biscuits, pieces of chocolate, candies or liquorices; portion/week) before start of the pregnancy. One portion of sweet snacks included 2 biscuits, 2 pieces of chocolate, 5 candies, or 5 pieces of liquorice. Besides analysing maternal dietary intake in food groups, we examined maternal diet using a self-composed composite score. All five food groups were split based on median intake of the total study population. For vegetables and fruit, an intake equal to or below the median scored zero points and an intake above the median scored one point. For sugary drinks, savoury and sweet snacks, an intake equal to or below the median scored one point and an intake above the median scored zero points. The food composite score therefore ranges between 0 and 5 points; the higher the score, the healthier the dietary intake based on these five available food groups.
The SQUASH is considered valid to rank subjects according to their level of physical activity.18 Data were collected about commuting activities, leisure time activities, household activities, and activities at work and school, using three main questions: days per week active, average time per day/week spending in that particular activity (hours and/or minutes), and intensity of the activity (low, moderate, high). Preconception physical activity was operationalised as the last reported total MVPA (hour/week) measurement before start of the pregnancy.
Offspring cardiovascular health
Offspring cardiovascular health was measured by physical examinations in a mobile research vehicle, which ensured a standardized environment. Examinations were done by two out of six trained researchers, according to a standardised research protocol. Children were asked not to eat or drink from 90 minutes before the mobile research vehicle arrived at their home. Height was measured on bare feet to the nearest 0.1cm using a stadiometer. Weight was measured in underwear to the nearest 0.1kg using a digital weighting scale. BMI was calculated by dividing the weight of the child in kilograms by their height in metres squared. Waist circumference was measured to the nearest 0.1cm using a flexible measurement tape. Waist to height ratio was calculated by dividing the waist circumference in centimetres by the height of the child in centimetres. All anthropometric measurements were done twice, and in case of >0.5cm difference in height, >0.5kg difference in weight, and >1cm difference in waist circumference between the two measurements, a third measurement was done. After the child sat quietly for 5 minutes, blood pressure was measured three times at heart level, in sitting position at the non-dominant arm, using an automatic measurement device (Omron HBP-1300)
with appropriate cuff size. The child was not allowed to talk in between. Time in between the subsequent measurements was 30 seconds. After all metal containing attributes were removed (e.g. earrings and hair elastics) and the child laid quietly for 5 minutes, body composition was measured by bio-electrical impedance (BIA; Bodystat 1500). The child was already asked to empty his/her bladder before the measurements in the research vehicle started. Electrode strips were attached at the dorsal side of the left hand and foot, with at least 3-5 cm in between the two electrodes. If the impedance or resistance differed >5Ω a third measurement was done. The recalibrated Kushner equation19 was used to estimate total body water, after which fat free mass (kg) and fat mass (as percentage of total body weight) were calculated. Directly after the BIA measurement, still in supine position, carotid-femoral PWV was measured twice using the Complior Analyse (Complior; Alam medical). Censors were placed at the carotid artery on the right side and on the femoral artery on the left side. If the results of the two measurements differed >10% from each other a third measurement was done. For all physical examinations, mean values of the two or three measurements were used for data analysis.
Covariates
package Compl-eat from Wageningen University. Data on offspring physical activity was measured for seven consecutive days using the triaxial Actigraph wGT3X-BT or GT3X+ monitor. Crude data were obtained using ActiLife 6 (ActiGraph, LLC, Pensacola, Florida, USA). Only children with at least 3 days including at least 7 valid hours of wear time per day were included in data analysis.20 Non-wear time was defined as ≥20 minutes of consecutive zero counts. We additionally examined if allocated maternal randomisation group (intervention or control group) affected the associations.
Data analysis
Linear regression analysis was used to examine the association between preconception diet and physical activity and cardiovascular health of the offspring. Residuals were shown to be normally distributed. Results are displayed as regression coefficients and 95% confidence intervals (C.I.). We additionally combined preconception diet, as the self-composed composite score, and preconception MVPA into one regression model and studied the interaction between those two independent variables by adding an interaction term into the model. Because of extreme values (+/- 3SD), we excluded five mother-child pairs from our analyses regarding preconception MVPA and offspring cardiovascular health (>33 hours preconception MVPA per week).
For the cardiovascular outcomes, age and sex specific BMI Z-scores were calculated by the lambda-mu-sigma (LMS) method using the WHO BMI growth standards21 and age and sex specific blood pressure Z-scores were calculated based on the fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents.22 Based on biological implausibility, we excluded two children with a body fat percentage of <5% from our statistical analysis regarding body composition.23 We checked if offspring sex was an effect modifier by adding an interaction term into the regression models. Covariates were added one by one into the univariate regression models. Effect estimates were small and hence adding covariates into the univariate model changed the majority of the effect estimates by 10% or more. We therefore decided only to add covariates into our model if our conclusions changed based on the adjusted effect estimates and 95% C.I.
Statistical analyses were performed using the software Statistical Package for the Social Sciences (SPSS) version 24 for Windows (SPSS, Chicago, IL, USA). P-values <0.05 were considered statistically significant.
RESULTS
In total, 341 children were conceived within 24 months after the start of the LIFEstyle study, of whom 7 died during pregnancy or shortly after labour. Twins (N=29) were excluded for follow-up, resulting in a total of 305 eligible singletons. We received informed consent of 51 children (16.7%; Figure 5.1). Because of missing data regarding preconception lifestyle and offspring cardiovascular health, we were able to include 28 up to 46 children in our analysis. Table 5.1 shows the characteristics of the participating mothers and their offspring (N=46). Mothers had a mean pre-pregnancy BMI of 35.3kg/ m2 (SD: 3.4) and 73.9% of them were nulliparous at inclusion in the LIFEstyle trial. Children were born with a mean birth weight of 3497 grams (SD: 507) after on average 39.1 weeks (SD: 1.7) of gestation. Age of the child at time of the physical examinations was 4.7 years (SD: 1.0).
Figure 5.1. Flow-chart of the women and their offspring included in this study. IC = informed
Table 5.1. Study characteristics of the participating mothers and their offspring (N=46).* Maternal characteristics
Age at pregnancy (years; mean; SD) 30.1 (3.9)
Caucasian (yes; N; %) 44 (95.7)
Education level (N; %)
No education or primary school 0
Secondary school 10 (22.7)
Intermediate vocational education 26 (59.1)
Higher vocational education and university 8 (18.2)
Nulliparous (yes; N; %) 34 (73.9)
Pre-pregnancy BMI (kg/m2; mean; SD) 35.3 (3.4)
Gestational diabetes (yes; N; %) 11 (23.9)
Smoking at randomisation (yes; N; %) 8 (17.4)
Mode of conception (N; %)
Spontaneous 18 (39.1)
Ovulation induction 16 (34.8)
Intra Uterine Insemination 7 (15.2)
IVF/ICSI/CRYO 5 (10.9)
PCOS (yes; N; %) 20 (43.5)
Offspring characteristics
Sex (boys; N; %) 22 (47.8)
Birth weight (grams; mean; SD) 3497 (507)
Gestational age at birth (weeks; mean; SD) 39.1 (1.7)
Exclusively breastfed (months; median; IQR) 0.0 (0.0; 2.0) Age of the child at time of physical examinations (years; mean; SD) 4.7 (1.0) * Missing data for education level: N=2 and breastfeeding: N=4.
SD = standard deviation; BMI = Body Mass Index; IVF = In Vitro Fertilisation; ICSI = Intracytoplasmic Sperm Injection; CRYO = Cryotherapy; PCOS = polycystic ovary syndrome. At follow-up, offspring had a mean BMI of 16.5 kg/m2 (SD: 1.7) (Z-score 0.69 [SD: 1.05]), with a fat mass of 21.0% (SD: 8.7) (Table 5.2). We observed no statistically significant differences comparing the maternal and offspring characteristics of participants versus the maternal and offspring characteristics of non-participants (Supplementary Table 5.1).
Table 5.2. Offspring cardiovascular health outcomes at the ages 3-6 years old.
N Mean; SD
BMI (kg/m2) 46 16.5 (1.7)
BMI (Z-Score)† 46 0.69 (1.05)
Waist to height ratio (waist/height) 46 0.49 (0.03)
Systolic blood pressure (mmHg) 43 100.2 (7.5)
Diastolic blood pressure (mmHg) 43 64.2 (7.0)
Systolic blood pressure (Z-Score)* 43 0.51 (0.59)
Diastolic blood pressure (Z-Score)* 43 0.94 (0.60)
Fat mass (percentage) 42 21.0 (8.7)
Fat free mass (kg) 42 15.6 (2.3)
Pulse wave velocity (m/s) 34 4.5 (1.0)
† Z-Scores BMI were calculated using the WHO BMI growth standards, LMS method.
* Z-Scores blood pressure were calculated based on “The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents” of the National Heart, Lung and Blood institute.
Higher preconception vegetable intake (per 10 gram/day) was associated with a lower diastolic blood pressure (DBP) in the offspring (Z-score: -0.05 [-0.08;-0.01]; P=0.007; Table 5.3). Higher preconception fruit intake (10 gram/day) was associated with a lower PWV in the offspring (-0.05 m/s [-0.10;-0.01]; P=0.03). Higher intake of preconception sugary drinks (glass/day) was associated with a higher offspring fat free mass in the adjusted model (unadjusted: 0.56 kg [-0.14; 1.27]; P=0.11; adjusted: 0.54 kg [0.01; 1.07]; P=0.045). We did not observe any other statistically significant associations between preconception diet and physical activity and offspring cardiovascular health, nor did we observe trends towards statistically significant associations. Preconception total food score was not statistically significantly associated to offspring cardiovascular health (Supplementary Table 5.2). Nevertheless, we observed a trend towards higher maternal preconception diet score (i.e. a more healthy diet) and lower offspring DBP (-0.12 [-0.27; 0.03]; P=0.10).
PCOS) and offspring related covariates (sex, age at time of the physical examinations, breastfeeding, birth weight, current dietary intake [kcal] and physical activity [counts/ min]) into our models.
DISCUSSION
Higher intake of vegetable before conception was associated with lower offspring DBP, and higher intake of fruit before conception was associated with lower offspring PWV. We additionally observed an unexpected association between higher intake of sugary drinks before conception and higher offspring fat free mass. We did not observe any associations between maternal preconception food score and preconception MVPA with offspring cardiovascular health.
Interpretation of results
The association of higher maternal vegetable intake with lower offspring DBP is in line with a previous study showing that the higher the Mediterranean Diet Score (MDS) during pregnancy –which is characterised by a high intake of vegetables–, the lower the offspring DBP (3-point increment in MSD: -0.57 mmHg [-0.98; -0.16]).7 Another study, however, did not find that higher vegetable intake in late pregnancy was associated with lower offspring DBP.24 In that study, maternal dietary intake was assessed at 32 weeks gestation, while we assessed diet preconceptionally. It might be that vegetable intake during the preconception period has a larger influence on offspring DBP compared to vegetable intake in late pregnancy, as the foetal heart and organs develop very early in pregnancy and beneficial effects of vegetable intake preconceptionally can optimally affect cardiovascular development.
The suggested mechanism underlying the observed associations of maternal vegetable and fruit intake with offspring cardiovascular health might be the high fibre content of a diet rich in fruit and vegetables. Consuming a diet rich in fibre is associated with lower maternal body weight and lower body fat25, and therefore might lead to better placental and foetal growth and development, which favourably influences offspring susceptibility to high blood pressure later in life.26 Moreover, it might be that higher maternal vegetable and fruit intake represent a more healthy diet, which favourably programs offspring cardiovascular health.7
Our finding of increased sugary drinks before conception being associated with higher offspring fat free mass is not in line with our expectations. Many studies have shown that a higher intake of sugary drinks during pregnancy is associated with higher offspring BMI at pre-school and primary school age27–29, and additionally with higher fat mass at 6 years of age.28 Our findings contrast with this literature and may be a chance finding.
This study is unique with respect to the preconception time window during which maternal dietary intake and physical activity were measured, enabling us to study the association with offspring cardiovascular health. Our findings add to the current literature that is largely limited to lifestyle during pregnancy. It shows that increasing fruit and vegetable intake before pregnancy has beneficial effects for cardiovascular health of the offspring. Women tend to change their lifestyle during pregnancy, increasing fruit and vegetable intake and decreasing intake of fried and fast food, coffee and tea30, which may interact with the effects of preconception intake on offspring health. Future studies should therefore take both preconception and pregnancy intakes into account to assess the combined effects on offspring health.
Strengths and limitations
An important strength of the current study is the reliable and extensive data collection regarding cardiovascular health of the children. This enabled us to study anthropometric as well as vascular outcomes. Additionally, we studied the association of both preconception dietary intake and physical activity with offspring cardiovascular health, to test whether these two maternal lifestyle behaviours influenced each other in their association with offspring cardiovascular health. Besides the physical examinations, we collected detailed information about offspring current lifestyle, enabling us to study if associations between preconception lifestyle and offspring cardiovascular health were confounded by offspring current lifestyle, which was not the case. This suggests that offspring vascular health is programmed by maternal preconception lifestyle independently of current offspring diet and physical activity.
fairly represent eating a healthy diet, which is high in fruit and vegetables and low in sugary drinks and snacks.
Generalisability and recommendations for future research
Our study population included children of mothers who were infertile, which was defined as failure to conceive within 12 months of unprotected intercourse in case of an ovulatory cycle, or in case of chronic anovulation according to WHO class I or II. Offspring of infertile mothers have a higher diastolic blood pressure compared to offspring of fertile mothers, irrespective of maternal BMI before pregnancy.33 However, our findings cannot be explained by differences in dietary intake between women who conceived spontaneously and through artificial reproductive technologies, as correction for mode of conception (spontaneous, ovulation induction, IUI, IVF/ICSI/CRYO) did not affect the associations. Since infertility is associated with stress34, which influences maternal lifestyle35,36 as well as offspring health37, future research should examine if our results are generalisable to the fertile obese population. Our sample size was small and therefore preconception research in larger study populations should replicate our findings.
CONCLUSION
Preconception dietary intake is associated to offspring health. Higher intakes of vegetable and fruit before conception were associated with better cardiovascular health in the offspring.
AUTHOR CONTRIBUTIONS
HG, AH, and BWM designed the LIFEstyle trial, RG, HG, AH, MvP, and TR designed the WOMB project, TvE collected the data, TvE and CvdB analysed the data, TvE, CvdB, AG, MvP, and TR interpreted the results, TvE wrote the final manuscript, all authors revised and approved the final manuscript.
FUNDING
The LIFEstyle study was funded by ZonMw, the Dutch Organization for Health Research and Development, grant number: 50-50110-96-518. The WOMB project was funded by grants from the Dutch Heart Foundation (2013T085) and the European Commission (Horizon2020 project 633595 DynaHealth). Neither ZonMw nor the Dutch Heart Foundation nor the European Commission had a role in data collection, analysis, interpretation of data or writing the report.
Supplementary Table 5.2. Linear regression analysis of the preconception food score (0-5
points; the higher the more healthy) and offspring cardiovascular health at age 3-6 years.
Preconception food score (0-5 points)
Offspring lifestyle N β (95% C.I.) unadjusted P-value
BMI (Z-Score) 43 0.02 (-0.27; 0.30) 0.90
Waist:height (ratio) 43 -0.003 (-0.01; 0.01) 0.42
SBP (Z-Score) 41 -0.02 (-0.18; 0.13) 0.76
DBP (Z-Score) 41 -0.12 (-0.27; 0.03) 0.10
Fat mass (%) 40 1.37 (-1.12; 3.87) 0.27
Fat free mass (kg) 40 0.30 (-0.36; 0.96) 0.36
Pulse wave velocity (m/s) 32 0.21 (-0.13; 0.54) 0.22
BMI = body mass index; SBP = systolic blood pressure; DBP = diastolic blood pressure.
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