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Word count text: 3597; Word count abstract: 250;
Number of references: 45;
Tables: 5; Figures: 0; Supplementary Figure: 1;
Supplementary Tables: 2.
Maternal educational level and blood pressure, aortic stiffness,
cardiovascular structure and functioning in childhood: The Generation R
Study
Running title: Maternal education and cardiovascular outcomes
Selma H. BOUTHOORN MDa,b, Frank J. VAN LENTHE PhDb, Layla L. DE JONGE MDa,c,d,
Albert HOFMAN MD PhDa,c , Lennie VAN OSCH-GEVERS, MD, PhDd, Vincent WV
JADDOE MD PhDa,c,d, Hein RAAT MD PhDb
a
The Generation R Study Group, Erasmus Medical Centre, Rotterdam, the Netherlands;
b
c
Department of Public Health, Erasmus Medical Centre, the Netherlands;
Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands;
d
Department of Pediatrics, Erasmus Medical Centre, the Netherlands.
Corresponding author
Selma H. Bouthoorn MD. The Generation R Study Group, Erasmus MC, University Medical
Centre Rotterdam. P.O. Box 2040, 3000 CA Rotterdam, the Netherlands; Telephone: +31
(0)10-704 38496; fax: +31 (0)10 704 4645; e-mail: s.bouthoorn@erasmusmc.nl.
Conflict of interest: None
2
Abstract
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Background: In adults, low level of education was shown to be associated with higher blood
2
pressure levels and alterations in cardiac structures and function. It is currently unknown
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whether socioeconomic inequalities in arterial and cardiac alterations originate in childhood.
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Therefore, we investigated the association of maternal education with blood pressure levels,
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arterial stiffness and cardiac structures and function at the age of 6 years, and potential
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underlying factors.
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Methods: The study included 5843 children participating in a prospective cohort study in the
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Netherlands. Maternal education was assessed at enrollment. Blood pressure, carotid-femoral
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pulse wave velocity, left atrial diameter, aortic root diameter, left ventricular mass and
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fractional shortening were measured at the age of 6 years.
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Results: Children with low educated (category 1) mothers had higher systolic (2.80 mm Hg,
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95% CI: 1.62-2.94) and diastolic (1.80 mm Hg, 95% CI: 1.25-2.35) blood pressure levels as
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compared to children with high educated (category 4) mothers. The main explanatory factors
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were the child’s BMI, maternal BMI and physical activity. Maternal education was negatively
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associated with fractional shortening (p for trend 0.008), to which blood pressure and child’s
16
BMI contributed the most. No socioeconomic gradient was observed in other arterial and
17
cardiac measurements.
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Conclusion: Socioeconomic inequalities in blood pressure are already present in childhood.
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Higher fractional shortening among children from low socioeconomic families might be a
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first cardiac adaptation to higher blood pressure and higher BMI. Interventions should be
21
aimed at lowering child BMI and increasing physical activity among children from low
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socioeconomic families.
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Keywords: Maternal educational level, blood pressure, cardiac structures, cardiac function,
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arterial stiffness, childhood
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Introduction
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Cardiovascular disease (CVD) is the leading cause of death in most western parts of the world.
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Low socioeconomic position (SEP) has been recognized as a marked risk factor in the
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occurrence of CVD among adults (1, 2). A better understanding of the origins and underlying
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mechanisms of socioeconomic inequalities in CVD is essential to develop effective strategies
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aimed at preventing or reducing these inequalities. Growing evidence suggest that CVD
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inequalities arise already in childhood, since several CVD risk factors including, low birth
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weight, short gestational age, physical inactivity, childhood obesity and familial hypertension,
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affect children from low socioeconomic families more frequently (3-5). These risk factors
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may cause inequalities in blood pressure levels in childhood, and may track into adulthood (6).
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Indeed, a recent study showed socioeconomic inequalities in blood pressure to appear at the
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age of 5-6 years old already, mediated by known CVD risk factors including birth weight,
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childhood BMI and maternal BMI (7).
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Alterations in arterial and cardiac structures such as aortic stiffness, aortic root size, left atrial
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and left ventricular enlargement, contribute to the risk of CVD among adults (8-11). In adults,
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it has been shown previously that a low level of education was associated with left ventricular
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hypertrophy, left ventricular dilatation and cardiac dysfunction (12). Factors recognized to
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influence these structures include elevated blood pressure levels and obesity (12-15). These
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factors are more common in children from low SEP families and were also found to cause a
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higher left ventricular mass in childhood already (16, 17). However, no previous study
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examined the socioeconomic gradient in early structural changes of the heart among children.
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Therefore, to improve the understanding of the origins and underlying mechanisms of CVD
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inequalities, we investigated in a population-based, prospective cohort study, the association
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between maternal educational level and blood pressure levels, arterial stiffness and cardiac
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structures and function at the age of 6 years. Furthermore, we examined whether adiposity
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measures, lifestyle-related determinants and birth characteristics could explain these
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associations.
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Methods
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Study design
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This study is embedded within the Generation R Study, a population-based prospective cohort
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study from early pregnancy onwards described in detail elsewhere (18). Enrolment was aimed
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at early pregnancy, but was allowed until the birth of the child. All children were born
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between April 2002 and January 2006 and form a prenatally enrolled birth-cohort that is
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currently being followed-up until young adulthood. The study was conducted in accordance
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with the guidelines proposed in the World Medical Association of Helsinki and has been
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approved by the Medical Ethical Committee of the Erasmus MC, University Medical Centre
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Rotterdam. Written consent was obtained from all participating parents (19).
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Study group
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In total, 8305 children still participate in the study from the age of 5 years (18). The
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participating children and their mothers were invited to a well-equipped and dedicated
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research center in the Erasmus Medical Center - Sophia Children’s Hospital between March
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2008 and January 2012. Measurements were focused on several health outcomes including
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body composition, obesity, heart and vascular development and behaviour and cognition (18).
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In total, 6690 children visited the research center. Mothers of children who didn’t visit the
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research center had a lower educational level, more frequently smoked during pregnancy
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(p<0.001) and fewer of them gave breastfeeding (p=0.001) as compared to mothers of
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children who visited the research center. No differences were found in other characteristics
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between these groups (Supplementary Table S1). We excluded twins (n=167) and participants
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who lacked information on maternal educational level (n=594) and on cardiovascular
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measurements (n=50). Furthermore, children with echocardiographic evidence of congenital
7
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heart disease or kidney disease were excluded (n=36), leaving a study population of 5843
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children (Supplementary Figure S1).
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Maternal educational level
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Our indicator of SEP was educational level of the mother. Level of maternal education was
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established using questionnaires at enrollment. The Dutch Standard Classification of
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Education was used to categorize 4 subsequent levels of education: 1. high (university degree),
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2. mid-high (higher vocational training, Bachelor’s degree), 3. mid-low (>3 years general
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secondary school, intermediate vocational training) and 4. low (no education, primary school,
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lower vocational training, intermediate general school, or 3 years or less general secondary
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school) (20).
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Child cardiovascular structures and function
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We measured blood pressure with the child in supine position quietly awake. Systolic and
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diastolic blood pressure (SBP and DBP) was measured at the right brachial artery, four times
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with one minute intervals, using the validated automatic sphygmanometer Datascope Accutor
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Plus TM (Paramus, NJ, USA) (21). A cuff was selected with a cuff width approximately 40%
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of the arm circumference and long enough to cover 90% of the arm circumference. More than
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90% of the children who visited the research center had four successful blood pressure
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measurements available. SBP and DBP were determined by excluding the first measurement
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and averaging the other measurements.
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Carotid-femoral pulse wave velocity, the reference method to assess aortic stiffness (11), was
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assessed using the automatic Complior device (Complior; Artech Medical, Pantin, France)
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with participants in supine position. The distance between the recording sites at the carotid
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(proximal) and femoral (distal) artery was measured over the surface of the body to the
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nearest centimeter. Through piezoelectric sensors placed on the skin, the device collected
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signals to assess the time delay between the pressure upstrokes in the carotid artery and the
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femoral artery. Carotid-femoral pulse wave velocity was calculated as the ratio of the distance
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travelled by the pulse wave and the time delay between the feet of the carotid and femoral
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pressure waveforms, as expressed in meters per second (22). To cover a complete respiratory
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cycle, the mean of at least 10 consecutive pressure waveforms was used in the analyses.
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Recently, it has been shown that pulse wave velocity can be measured reliably, with good
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reproducibility in a large pediatric population-based cohort (23).
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Two-dimensional M-mode echocardiographic measurements were performed using the ATL-
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Philips Model HDI 5000 (Seattle, WA, USA) or the Logiq E9 (GE Medical Systems,
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Wauwatosa, WI, USA) devices. The children were examined in a quiet room with the child
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awake in supine position. Missing echocardiograms were mainly due to restlessness of the
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child or unavailability of equipment or sonographer. Left atrial diameter, interventricular end-
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diastolic septal thickness (IVSTD), left ventricular end-diastolic diameter (LVEDD), left
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ventricular end-diastolic posterior wall thickness (LVPWTD), interventricular end-systolic
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septal thickness, left ventricular end-systolic diameter, left ventricular end-systolic posterior
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wall thickness, aortic root diameter, and fractional shortening were measured using methods
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recommended by the American Society of Echocardiography (24). Left ventricular mass (LV
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mass) was computed using the formula derived by Devereux et al (25):LV mass = 0.80 ×
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1.04((IVSTD + LVEDD + LVPWTD)3 − (LVEDD) 3)+ 0.6. To assess reproducibility of
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ultrasound measurements, the intraobserver and interobserver intraclass correlation
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coefficients were calculated previously for left atrial diameter, aortic root diameter, IVSTD,
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LVEDD and LVPWTD in 28 subjects (median age 7.5 years, interquartile range 3.0-11.0) and
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varied between 0.91 to 0.99 and 0.78 to 0.96, respectively (26).
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Explanatory variables
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The following factors were considered to be potential explanatory factors in the pathway
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between SEP and blood pressure, cardiovascular structures and function. These were chosen
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based on previous literature (7, 27-30).
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Maternal characteristics
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Information on pre-pregnancy weight, pre-pregnancy hypertension (yes, no) and smoking
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during pregnancy (no, until confirmed pregnancy and continued during pregnancy) and
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financial difficulties, as indicator of family stress, was obtained by questionnaires. Also,
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another measurement of family stress was assessed with the family assessment device score at
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age 5. A higher score reflects more ‘stress’. Information on pregnancy-induced hypertension
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and preeclampsia was obtained from medical records. Women suspected of pregnancy
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hypertensive complications, based on these records, were crosschecked with the original
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hospital charts. Details of these procedures have been described elsewhere (31). Maternal
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height was measured during visits at our research center. On the basis of height and pre-
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pregnancy weight, we calculated pre-pregnancy body mass index (BMI) (weight/height2).
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Birth characteristics
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Birth weight and gestational age at birth were obtained from midwife and hospital registries.
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Information on breastfeeding during infancy (ever/never) was obtained by questionnaires.
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Child characteristics
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Weight of the child was measured while wearing lightweight clothes and without shoes by
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using a mechanical personal scale (SECA), and height was measured by a Harpenden
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stadiometer (Holtain Limited) in standing position, which were both calibrated on a regular
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basis. BMI was calculated using the formula; weight (kg) / height (m)2. Standard-deviation
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scores (SDS) adjusted for age and gender were constructed for these growth measurements
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(32). Watching television (< 2 hours/day, ≥ 2 hours/day), as indicator of sedentary behaviour,
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and playing sports (yes/no), as indicator of physical activity, were obtained from
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questionnaires at the age of 5 years.
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Confounding variables
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Gender and date of birth of the child were obtained from midwife and hospital registries.
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Ethnicity (Dutch, other western, non-western) was obtained from the first questionnaire at
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enrollment in the study. These factors were considered as potential confounding factors.
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Statistical analyses
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First, univariate associations of maternal educational level to all covariates, blood pressure,
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carotid-femoral pulse wave velocity, cardiac structures and function were explored using Chi-
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square tests and ANOVAs. Second, we assessed the association of maternal educational level
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with blood pressure levels, carotid-femoral pulse wave velocity, cardiac structures and
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function using linear regression models adjusted for the potential confounders (model 1). To
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evaluate the mediating effects of all potential explanatory factors Baron and Kenny’s causal
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step approach was used (33). Only those factors that were significantly associated with the
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outcome (independent of maternal educational level; data available upon request) and
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unequally distributed across SEP groups (Table 1) were added separately to model 1 (33). To
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assess their mediating effects, the corresponding percentages of attenuation of effect estimates
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were calculated by comparing differences of model 1 with the adjusted ones (100 x (B model 1 –
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B model 1 with
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level and all the explanatory factors assessed the joint effects of the explanatory factors. The
explanatory factor)
/ (B model 1 )). Finally, a full model containing maternal educational
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explanatory mechanisms were investigated only for outcomes (blood pressure, pulse wave
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velocity, cardiac structures and function) that differed by maternal educational level after
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adjustment for confounders (model 1). Interaction terms between maternal educational level
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and child’s sex on all the outcomes were not significant (p>0.1); therefore analyses were not
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stratified for sex. Multiple imputation was used to deal with the missing values in the
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covariates. Five imputed datasets were created and analysed together. A 95% confidence
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interval (CI) was calculated around the percentage attenuation using a bootstrap method with
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1000 re-samplings per imputed dataset in the statistical program R (34). All the other
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statistical analyses were performed using Statistical Package of Social Science (SPSS) version
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20.0 for Windows (SPSS Inc, Chicago, IL, USA).
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Results
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Table 1 shows the characteristics of the study population. Of all participating children 22.4%
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(n= 1308) had mothers with a low educational level and 25.3% (n=1483) of the mothers were
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high educated. Compared with mothers with a high education, those with a low education had
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a higher pre-pregnancy BMI, suffered more frequently from pre-pregnancy hypertension, had
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more financial difficulties and a higher family assessment device score (p<0.001), indicating
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more stress within their families, fewer of them gave breastfeeding, and they more frequently
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smoked during pregnancy (p=0.002). Their children were on average lighter at birth and had
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a shorter gestational duration (p<0.001). Mothers with a high education were more frequently
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Dutch, while mothers with a low education had more frequently a non-western ethnic
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background (p<0.001). Children of low educated mothers less frequently played sports,
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watched more frequently ≥ 2 hours television per day and were heavier as compared with
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children of high educated mothers (p<0.001). Mean systolic (SBP) and diastolic blood
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pressure (DBP) levels (p<0.001) and carotid-femoral pulse wave velocity (p=0.02) were
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negatively associated with level of education. Also, left atrial diameter (p<0.001) and left
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ventricular mass (p=0.003) differed according to educational level (Table 1).
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Multivariable linear regression analyses adjusted for the potential confounders showed that
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the lower the education of the mother, the higher the systolic and diastolic blood pressure of
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their children (p for trend <0.001) (Table 2). No consistent associations of maternal education
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were observed with carotid-femoral pulse wave velocity, aortic root diameter, left atrial
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diameter, and left ventricular mass. Fractional shortening was negatively associated with
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maternal educational level (p for trend 0.008). There was no interaction between ethnicity and
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maternal education on these outcomes (p > 0.05).
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Maternal pre-pregnancy BMI, maternal pre-pregnancy hypertension, gestational age, and the
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child’s height and BMI were related both to maternal educational level and SBP. The selected
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explanatory factors for DBP included maternal pre-pregnancy hypertension, birth weight,
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watching television, playing sports, and the child’s height and BMI. Birth weight, child’s
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BMI, SBP and DBP were the selected explanatory factors in the association between maternal
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education and fractional shortening. For each selected factor, an interaction with maternal
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education was tested for significance, none of them were significant (p > 0.05).
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Regarding the proportion of explanation by each risk factor (Table 3 and Table 4), the child’s
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BMI was the most important contributor to the association of maternal education to SBP in
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the mid-low and low educational subgroup (15% attenuation (95% CI: -29% to -7%) and 29%
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(95% CI: -42% to -20%) ). Secondly, maternal pre-pregnancy BMI contributed to the
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association between maternal education and SBP accounting for 11% (95% CI: -22% to -6%)
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and 12% (95% CI: -18% to -7%) respectively. Overall, 12% (95% CI: -26% to 0.3%) and
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24% (95% CI: -36% to -14%) of the association of maternal education and SBP was
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explained for mid-low and low education by including the explanatory factors (Table 3). For
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DBP, the child’s BMI and playing sports were the most contributing factors in the association
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between maternal education and DBP, explaining 8% (95% CI: -14% to -3%) and 7% (95%
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CI: -13% to -3%) in the lowest educational subgroup. The overall explanation was 12% (95%
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CI: -47% to -3%), 16% (95% CI: -30% to -8%) and 21% (95% CI: -35% to -12%) in the mid-
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high, mid-low and low educational subgroup respectively (Table 4). For both SBP and DBP
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the socioeconomic differences remained significant after including all the explanatory factors
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(Table 3 and Table 4). Complete elimination of the association of mid-low and low education
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with fractional shortening was observed after individual adjustment for BMI, SBP and DBP.
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SBP was the most contributing factor, explaining 27% (95% CI: -142% to 25%) and 42%
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(95% CI: -159% to -12%) respectively (Table 5).
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Discussion
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This study shows that socioeconomic inequalities in adult CVD may have their origins in
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childhood. We found socioeconomic inequalities in systolic and diastolic blood pressure to
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occur already at the age of 6 years. Furthermore, a positive association was found between
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maternal education and fractional shortening, which was explained by higher blood pressure
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levels and a higher BMI among children of lower educated mothers. We did not find evidence
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for socioeconomic inequalities in carotid- femoral pulse wave velocity, aortic root diameter,
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left atrial diameter, and left ventricular mass at the age of 6 years.
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Methodological considerations
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The strengths of this study are the prospective population-based design and the availability of
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many important covariates that may explain the association between maternal education,
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blood pressure levels, and cardiac structures and function. In addition, we had a large sample
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size of 5843 participants and the availability of several cardiovascular measurements in most
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of these children.
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To various extents, our results may have been influenced by the following limitations. We
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used maternal educational level as indicator of SEP. Maternal education may reflect general
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and health-related knowledge, health behavior, health literacy and problem-solving skills (35,
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36). Furthermore, it has been shown that education is the strongest and most consistent
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socioeconomic predictor of cardiovascular risk factors (37). It is less clear to what extent it
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captures the material and financial aspects of the household. We therefore repeated the
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analyses using household income level as determinant, and we found comparable results with
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the highest SBP and DBP and the highest fractional shortening in the lowest income group
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(Supplementary Table S2). Information on various covariates in this study was self-reported,
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which may have resulted in underreporting of certain adverse lifestyle related determinants. In
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our blood pressure measurements, we were not able to account for circadian rhythm. Yet,
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while this may have resulted in random error, it seems less likely that bias varied
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systematically across socioeconomic groups. Although the participation rate in The
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Generation R Study was relatively high (61%), there was some selection towards a relatively
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highly educated and more healthy study population (38). Non-participation would have led to
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selection bias if the associations of maternal educational level with the outcome differed
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between participants and non-participants. Previous research showed that this bias is minimal
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(39, 40). However, it cannot be ruled out completely. Finally, unmeasured factors related to
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both SEP and blood pressure, such as salt intake and psychosocial factors, might explain some
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of the remaining effect of SEP on blood pressure. Sleep patterns may also explain some of the
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remaining effect, since this has been associated with cardiovascular health in previous studies
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(41).
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Maternal education, blood pressure and cardiac structures and function
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Previous literature concerning the association between socioeconomic circumstances and
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blood pressure in childhood is conflicting (7, 42). This might be due to the use of different
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study designs and different study populations. In line with previous literature we found BMI
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to be the factor contributing most to the association between maternal education and blood
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pressure (7). Obesity may cause disturbances in autonomic function, insulin resistance and
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abnormalities in vascular structure and functions, which in turn may cause elevated blood
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pressure levels (43). Maternal pre-pregnancy BMI was also an important explanation of the
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socioeconomic gradient in SBP. Maternal BMI and a child’s BMI are correlated; the effect of
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maternal BMI may act for an important part through its effect on the child’s BMI. This is
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supported by our findings which showed that after adjustment for child’s BMI and maternal
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BMI, only child’s BMI remained significant (data not shown). A novel finding of this study is
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that indicators of sedentary behavior and physical activity, including watching television and
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playing sports, mediate the association between maternal education on DBP. Although these
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effects may pass through the effects of the child’s BMI on DBP, its significant association in
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the fully adjusted model suggests that there is probably also an independent effect of physical
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activity on DBP, which explains the socioeconomic inequalities in DBP. This is supported by
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a recent study of Knowles et al. who found higher physical activity to be associated with
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lower DBP levels among 5-7 year old children, independent of BMI and other markers of
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adiposity (44). These findings suggest that intervention should be aimed at increasing
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physical activity, especially among children with a lower SEP.
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Although children from low SEP families had higher BP levels and a higher BMI which is
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previously shown to be associated with larger left ventricular mass and atrial enlargement
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(12-15), we did not find a socioeconomic gradient in cardiac structures at the age of 6 years.
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We found, however, left ventricular mass to be lower in the mid-high and the mid-low
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educational subgroup as compared to the high educational subgroup. The direction of the
348
association was not entirely equal to what was expected. Also, no socioeconomic gradient
349
was observed and therefore commonly used cardiovascular risk factors explaining
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socioeconomic inequalities are not likely to be an explanation. Future research is necessary to
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replicate these findings. Another remarkable finding was the higher fractional shortening
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among children with mid-low and low educated mothers. One explanation might be that these
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children experience more stress during the echocardiographic assessment due to a lower lack
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of parental support because they, as well as their parents, are more impressed by the
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measurement setting, resulting in a higher fractional shortening. However, stress would also
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have increased their heart rate and adjustment for heart rate would then have explained, at
18
357
least to some extent, the association between maternal education and fractional shortening. In
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our study, this explanation is less likely since heart rate, as indicator of stress, was not
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associated with fractional shortening. Since an increased fractional shortening was explained
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by higher blood pressure levels and a higher BMI, another explanation might be that it is the
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first indication of cardiac adaptation to higher blood pressure levels and higher BMI among
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low SEP children. However, in a later stage higher blood pressure levels and a higher BMI
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result in alterations of cardiac structures such as left ventricular and left atrial enlargement
364
(45) , which are associated with a lower fractional shortening. Thus our findings that lower
365
education leads to a higher fractional shortening at the age of 6 are not fully understood and a
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change finding can also not be excluded. Confirmation in future studies is therefore highly
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recommended and replication would suggest that cardiac structural alterations can be
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prevented at this age by lowering blood pressure levels and body weight, especially among
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children from low socioeconomic families.
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Conclusion
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Our study adds to the small body of literature concerning socioeconomic differences in blood
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pressure and shows that inequalities arise in early childhood which were mainly explained by
373
socio-economic inequalities in the child’s BMI and physical activity. No differences in
374
arterial stiffness or cardiac structures were observed per educational subgroup. However, a
375
socioeconomic gradient in fractional shortening was observed, with children from low SEP
376
families having a higher fractional shortening as compared to children from high SEP families.
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This might be a first cardiac adaptation to a higher blood pressure and a higher BMI. The
378
results require careful interpretation since the associations were relatively small and the
379
clinical importance not yet fully understood.
19
Supplementary information is available at http://www.oup.com/ajh.
Acknowledgements
The Generation R Study is conducted by the Erasmus Medical Centre in close collaboration
with the Erasmus University Rotterdam, School of Law and Faculty of Social Sciences, the
Municipal Health Service Rotterdam area, Rotterdam, the Rotterdam Homecare Foundation,
Rotterdam, and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR),
Rotterdam. We gratefully acknowledge the contribution of general practitioners, hospitals,
midwives and pharmacies in Rotterdam. We also thank Wim Helbing for his valuable
comments on an earlier draft of this manuscript.
Funding
The first phase of the Generation R Study is made possible by financial support from:
Erasmus Medical Centre, Rotterdam, Erasmus University Rotterdam and the Netherlands
Organization for Health Research and Development (ZonMw).
Conflict of interest
None
20
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