The present study is part of the Amsterdam Born Children and their Development (ABCD) study (http://www.abcd-study.nl), a population-based prospective cohort study that examines the relationship of maternal lifestyle and psychosocial determinants during pregnancy with multiple aspects of child development and health . Approval of the study was obtained from the Academic Medical Center Medical Ethical Committee, the VU University Medical Center Medical Ethical Committee and the Registration Committee of Amsterdam. All participating mothers gave written informed consent for themselves and their children.
Between January 2003 and March 2004, pregnant women in Amsterdam were asked to participate in the ABCD study during their first prenatal visit to an obstetric care provider. In total 12,373 women were approached; by estimate 99% of the target population . A questionnaire covering socio-demographic characteristics, obstetric history, lifestyle, and psychosocial conditions was sent to the women’s home addresses and the women were requested to return it to the Public Health Service by prepaid mail. Of these 12,373 approached women, 8,266 women filled in the pregnancy questionnaire (response rate 67%). A total of 6,735 (81%) women gave permission for follow-up. In the following years, growth data of the children were collected from Child Health Care centres. In 2008, when the children turned five, the addresses of 6,161 mothers were retrieved from the Child Health Care registry; attrition in this follow-up number was largely due to untraceable changes in address or migration. The mothers received a questionnaire, including an informed consent sheet for a health check of their children at age 5. Children were invited for the health check at school for children living in Amsterdam, at a central location in the city for participants living outside Amsterdam until December 2010. The health check included (amongst others) a capillary blood sample (n = 2,108 correct samples) and anthropometrics (n = 3,321), for which separate consents were signed. The questionnaire (n = 4,488) encompassed items about the child’s demography, health status (consultations and medication), nutrition (qualitative and quantitative aspects), physical activity, screen time and familiar risk factors for cardiovascular diseases. Trained personnel from the Public Health Service Amsterdam performed all measurements. Only children with complete data on cardiometabolic biomarkers and screen time were included in the present analyses (n = 1,961) conducted in December 2012-March 2013. Participants with measured fasting blood showed a higher proportion of Dutch ethnicity, lower systolic BP and diastolic BP but no difference in mean age, gender, BMI and WC than participants without fasting blood measurement .
Measures at age 5
Information on child’s sex, date of birth, and birth weight was gathered from the Child Health Care registry. Maternal educational level (highest level of education) and ethnicity (based on country of birth of the mother) was gathered by questionnaire.
Trained research assistants measured weight, height, waist circumference (WC), and systolic and diastolic blood pressure using standard protocols. Height was measured to the nearest millimetre using a Leicester portable height measure (Seca, Hamburg, Germany) and weight to the nearest 100 gram using a Marsden MS-4102 weighing scale (Oxfordshire, United Kingdom). Height and weight were measured in order to calculate Body Mass Index (BMI) (kg/m2). Children were classified as normal weight, overweight or obese according to age and gender-specific cut-off points . WC was measured to the nearest millimetre midway between the costal border and iliac crest, using a Seca measuring tape. For the blood pressure measurements the child first lied down in a supine position. During the first minute, one test blood pressure measurement was performed. Then the child lied in rest for four minutes. Next the child was seated at a table and acclimatized for one minute, followed by four minutes of sitting in rest. Finally, systolic and diastolic blood pressure was measured twice in sitting position . Systolic and diastolic blood pressure (mmHg) were calculated by taking the mean value of the two measures. Using a finger puncture, overnight-fasting capillary blood samples (0.5 ml) were collected to determine glucose, total cholesterol, low density lipoprotein cholesterol (LDLC), high density lipoprotein cholesterol (HDLC), and triglycerides [Demecal, Lab Anywhere, The Netherlands] . The parents were asked to have their child fast from the evening before the morning of blood sampling. The fasting samples were taken between 8:00 and 8:30 A.M. and the children were offered breakfast afterwards.
Mothers were asked to record the time that their child spent watching TV or DVD at home or at friends’ homes on a 7-point scale ranging from almost never to 5 hours/day or more for weekdays and weekend days separately (1 = (almost) never, 2 = <1 hour/day, 3 = 1 hour/day, 4 = 2 hours/day, 5 = 3 hours/day, 6 = 4 hours/day, 7 = 5 hours/day). Responses to each were recorded and summed to compute average hours/day of TV time as follows: (Average TV time on a weekday*5 + Average TV time on a weekend day*2) / 7, possible range 0–5. Additionally, TV time was dichotomised according to screen time recommendations for children i.e. <2 hours/day. The time that their child spent using the PC or game console at home or at friends’ homes was asked and recorded on the same 7-point scale for weekdays and weekend days separately. Responses to each were averaged into hours/day of PC time (possible range 0–5). Since few children used the PC for more than 2 hours/day this variable was not dichotomized.
Physical activity (PA)
PA questions included duration of playing outside in summer and winter for weekdays and weekend days separately (0–5 hours/day), sports participation (0–4 hours/week), and frequency of walking and biking to and from school (0–5 times/week). Responses to playing outside in summer and winter were averaged to compute hours/day playing outside. Mean duration (hours/day) playing outside (0–5), mean duration (hours/week) sports participation (0–4) and frequency (times/week) of walking and biking to school (0–5) were averaged into a PA score with higher scores indicating higher levels of PA.
A relative cardiometabolic function score was computed as the mean of the standardised scores from the following five variables: WC, mean of systolic and diastolic blood pressure, glucose, HDLC, and triglycerides [11, 13]. Each of these variables was first standardised (individual value – group mean)/standard deviations (SD), stratified by gender. All standardised values, except for HDLC, were multiplied by −1 to confer enhanced function with increasing values for the purpose of calculating the metabolic function score. Using a continuously distributed sum score makes more sense in a sample of young and healthy children, since prevalence of deviating values will be low. Moreover, using a continuously distributed sum score maximizes statistical power. Descriptive results are presented as mean (±standard deviation) for continuous variables and percentages for categorical variables. Gender differences in cardiometabolic biomarkers, screen time, and PA were assessed by independent t-tests.
The relationship between screen time and the cardiometabolic biomarkers/function score was examined using linear regression analysis adjusting for gender (except when the gender-specific function score was the outcome), birth weight , and maternal education (model 1). To examine the independent association of screen time and cardiometabolic biomarkers in a subsequent model, adjustments for TV time (except when TV time was the exposure), PC time (except when PC time was the exposure), PA, and WC (except when the cardiometabolic function score or WC was the outcome) were made (model 2). In both models the analyses with WC, blood pressure and metabolic function score as outcome, were additionally adjusted for height since at this age height is related to WC and blood pressure. Additionally, the independent association of excessive TV time (defined as 2 hours or more per day) and cardiometabolic biomarkers was examined, adjusted for PC time, PA, and WC (except when the cardiometabolic function score or WC was the outcome). Significance levels were set at p ≤ .05.