Publications by authors named "Anna Sijtsma"

14 Publications

  • Page 1 of 1

Comparison of health behaviours between cancer survivors and the general population: a cross-sectional analysis of the Lifelines cohort.

J Cancer Surviv 2020 06 14;14(3):377-385. Epub 2020 Jan 14.

Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1 (9713 GZ), Groningen, The Netherlands.

Purpose: To compare the differences in lifestyle behaviours between cancer survivors (CSs) and cancer-free participants in a large and representative population-based cohort.

Methods: We included 115,257 adults from the Lifelines cohort. Cancer status was self-reported, and health behaviours were measured (e.g. body mass index [BMI]) or assessed by questionnaire (e.g. physical activity, smoking, alcohol consumption, sedentary behaviour and diet). The data were then categorised for logistic regression analysis, stratified and adjusted by sex and age (< 55 vs ≥ 55 years).

Results: CSs (5473; 4.7%) were diagnosed 9 ± 8.5 years before data collection, were older (mean age 55.4 vs 44.4 years) and more often female (66.6% vs 33.4%) than the cancer-free participants. They were also more likely to be physically active and to have a better diet, and also less likely to be alcohol drinkers; but, were more likely to have a higher BMI, be former smokers and to be sedentary. After adjustment for sex and age, however, BMI was more likely to be normal, physical activity was more likely to be higher and smoking to be prevalent in CSs. Current smoking was also significantly higher among females and those aged < 55 years who were CSs than for those with no history of cancer.

Conclusions: In this population-based cohort, CSs have health behaviour comparable to those without a cancer diagnosis.

Implications For Cancer Survivors: Smoking cessation strategies should target all CSs, but efforts could yield greatest benefit if they target females and those younger than 55 years.
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June 2020

Letter to editor: Reply on question of Marques JR et al. regarding the paper entitled: "The LifeLines cohort study: Prevalence and treatment of cardiovascular disease and risk factors".

Int J Cardiol 2019 11;294:57

University of Groningen, University Medical Center Groningen, The Department of Cardiology, Groningen, the Netherlands. Electronic address:

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November 2019

Parental physical activity is associated with objectively measured physical activity in young children in a sex-specific manner: the GECKO Drenthe cohort.

BMC Public Health 2018 Aug 20;18(1):1033. Epub 2018 Aug 20.

Department of Epidemiology, University Medical Center Groningen, Hanzeplein 1, 9713, GZ, Groningen, The Netherlands.

Background: Physical activity (PA) is important in combating childhood obesity. Parents, and thus parental PA, could influence PA in young children. We examined whether the time spent at different intensities of PA and the type of parental PA are associated with the PA of children aged 4-7 years, and whether the associations between child-parent pairs were sex-specific.

Methods: All the participants were recruited from the Groningen Expert Center for Kids with Obesity (GECKO) birth cohort (babies born between 1 April 2006 and 1 April 2007 in Drenthe province, the Netherlands) and were aged 4-7 years during measurement. PA in children was measured using the ActiGraph GT3X (worn at least 3 days, ≥10 h per day). PA in parents was assessed using the validated SQUASH questionnaire.

Results: Of the N = 1146 children with valid ActiGraph data and 838 mothers and 814 fathers with valid questionnaire data, 623 child-parent pairs with complete data were analysed. More leisure time PA in mothers was associated with more time spent in moderate-to-vigorous PA (MVPA) in children (Spearman r = 0.079, P < .05). Maternal PA was significantly related to PA in girls, but not boys. More time spent in maternal vigorous PA, in sports activity, and leisure time PA, were all related to higher MVPA in girls (Spearman r = 0.159, r = 0.133 and r = 0.127 respectively, P < .05). In fathers, PA levels were predominantly related to PA in sons. High MVPA in fathers was also related to high MVPA in sons (r = 0.132, P < 0.5). Spending more time in light PA was related to more sedentary time and less time in MVPA in sons.

Conclusions: Higher PA in mothers, for instance in leisure activities, is related to higher PA in daughters, and more active fathers are related to more active sons. To support PA in young children, interventions could focus on the PA of the parent of the same sex as the child. Special attention may be needed for families where the parents have sedentary jobs, as children from these families seem to adopt more sedentary behaviour.
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August 2018

Dietary patterns and physical activity in the metabolically (un)healthy obese: the Dutch Lifelines cohort study.

Nutr J 2018 02 12;17(1):18. Epub 2018 Feb 12.

Department of Endocrinology, University of Groningen, University Medical Center Groningen, HPC AA31, P.O. Box 30001, 9700, RB, Groningen, The Netherlands.

Background: Diversity in the reported prevalence of metabolically healthy obesity (MHO), suggests that modifiable factors may be at play. We evaluated differences in dietary patterns and physical activity between MHO and metabolically unhealthy obesity (MUO).

Methods: Cross-sectional data of 9270 obese individuals (30-69 years) of the Lifelines Cohort Study was used. MHO was defined as obesity and no metabolic syndrome risk factors and no cardiovascular disease history. MUO was defined as obesity and ≥2 metabolic syndrome risk factors. Sex-specific associations of dietary patterns (identified by principal component analysis) and physical activity with MHO were assessed by multivariable logistic regression (reference group: MUO). Analyses were adjusted for multiple covariates.

Results: Among 3442 men and 5828 women, 10.2% and 24.4% had MHO and 56.9% and 35.3% MUO, respectively. We generated four obesity-specific dietary patterns. Two were related to MHO, and in women only. In the highest quartile (Q) of 'bread, potatoes and sweet snacks' pattern, odds ratio (OR) (95% CI) for MHO was 0.52 (0.39-0.70). For the healthier pattern 'fruit, vegetables and fish', an OR of 1.36 (1.09-1.71) in Q3 and 1.55 (1.21-1.97) in Q4 was found for MHO. For physical activity, there was a positive association between moderate physical activity and vigorous physical activity in the highest tertile and MHO in women and men, respectively (OR 1.19 (1.01-1.41) and OR 2.02 (1.50-2.71)).

Conclusion: The healthier diet -characterized by 'fruit, vegetables and fish'- and moderate physical activity in women, and vigorous physical activity in men may be related to MHO. The (refined) carbohydrate-rich 'bread, potatoes and sweet snacks' dietary pattern was found to counteract MHO in women.
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February 2018

Factors of physical activity among Chinese children and adolescents: a systematic review.

Int J Behav Nutr Phys Act 2017 03 21;14(1):36. Epub 2017 Mar 21.

Department of Epidemiology (HPC FA40), University Medical Centre Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands.

Background: Lack of physical activity is a growing problem in China, due to the fast economic development and changing living environment over the past two decades. The aim of this review is to summarize the factors related to physical activity in Chinese children and adolescents during this distinct period of development.

Methods: A systematic search was finished on Jan 10, 2017, and identified 2200 hits through PubMed and Web of Science. English-language published studies were included if they reported statistical associations between factors and physical activity. Adapted criteria from the Strengthening The Reporting of OBservational studies in Epidemiology (STROBE) statement and evaluation of the quality of prognosis studies in systematic reviews (QUIPS) were used to assess the risk of bias of the included studies. Related factors that were reported in at least three studies were summarized separately for children and adolescents using a semi-quantitative method.

Results: Forty two papers (published 2002-2016) were included. Most designs were cross-sectional (79%), and most studies used questionnaires to assess physical activity. Sample size was above 1000 in 18 papers (43%). Thirty seven studies (88%) showed acceptable quality by methodological quality assessment. Most studies reported a low level of physical activity. Boys were consistently more active than girls, the parental physical activity was positively associated with children and adolescents' physical activity, children in suburban/rural regions showed less activity than in urban regions, and, specifically in adolescents, self-efficacy was positively associated with physical activity. Family socioeconomic status and parental education were not associated with physical activity in children and adolescents.

Conclusions: The studies included in this review were large but mostly of low quality in terms of study design (cross-sectional) and methods (questionnaires). Parental physical activity and self-efficacy are promising targets for future physical activity promotion programmes. The low level of physical activity raises concern, especially in suburban/rural regions. Future research is required to enhance our understanding of other influences, such as the physical environment, especially in early childhood.
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March 2017

The LifeLines Cohort Study: Prevalence and treatment of cardiovascular disease and risk factors.

Int J Cardiol 2017 Feb 11;228:495-500. Epub 2016 Nov 11.

University of Groningen, University Medical Center Groningen, The Department of Cardiology, Groningen, The Netherlands. Electronic address:

Background: The LifeLines Cohort Study is a large three-generation prospective study and Biobank. Recruitment and data collection started in 2006 and follow-up is planned for 30years. The central aim of LifeLines is to understand healthy ageing in the 21st century. Here, the study design, methods, baseline and major cardiovascular phenotypes of the LifeLines Cohort Study are presented.

Methods And Results: Baseline cardiovascular phenotypes were defined in 9700 juvenile (8-18years) and 152,180 adult (≥18years) participants. Cardiovascular disease (CVD) was defined using ICD-10 criteria. At least one cardiovascular risk factor was present in 73% of the adult participants. The prevalence, adjusted for the Dutch population, was determined for risk factors (hypertension (33%), hypercholesterolemia (19%), diabetes (4%), overweight (56%), and current smoking (19%)) and CVD (myocardial infarction (1.8%), heart failure (1.0%), and atrial fibrillation (1.3%)). Overall CVD prevalence increased with age from 9% in participants<65years to 28% in participants≥65years. Of the participants with hypertension, hypercholesterolemia and diabetes, respectively 75%, 96% and 41% did not receive preventive pharmacotherapy.

Conclusions: The contemporary LifeLines Cohort Study provides researchers with unique and novel opportunities to study environmental, phenotypic, and genetic risk factors for CVD and is expected to improve our knowledge on healthy ageing. In this contemporary Western cohort we identified a remarkable high percentage of untreated CVD risk factors suggesting that not all opportunities to reduce the CVD burden are utilised.
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February 2017

Parental correlations of physical activity and body mass index in young children--he GECKO Drenthe cohort.

Int J Behav Nutr Phys Act 2015 Oct 9;12:132. Epub 2015 Oct 9.

Department of Epidemiology (FA40), University Medical Center Groningen, University of Groningen, P.O. Box 30.001, 9700 RG, Groningen, Netherlands.

Background: Parental behavior can influence the development of overweight in children. The aim of this study is to examine whether parental BMI and parental physical activity are associated with BMI, waist circumference and physical activity in young children.

Methods: In 3-4 year old children, weight, height and waist circumference were measured. Children's physical activity was measured in a subgroup (n = 299) using a tri-axial activity monitor, TracmorD. Data are represented as activity counts per minute (total physical activity) and as percentage of time in sedentary, light, moderate and vigorous intensity physical activity (generated from a subsample of Actigraph data using cut points from Butte et al.). Parental weight and height were self-reported and parental physical activity was assessed by the validated questionnaire SQUASH.

Results: In total 1554 children (age 3.9 ± 0.1 years, BMI 15.8 ± 1.3 kg/m2 and waist circumference 52.4 ± 3.5 cm) were included. Eleven percent were overweight or obese. A higher maternal BMI was related to higher levels of children's sedentary activity (r = 0.120, p = 0.04 and to lower levels of children's total and moderate physical activity (r = -0.158, p = 0.007 and r = -0.154, p = 0.008, respectively). Parental BMI was positively correlated with children's BMI and waist circumference (r = 0.20-0.27, p < 0.001). Higher maternal total physical activity levels were not related to children's total physical activity level, but were related to higher levels of children's moderate and vigorous physical activity (ρ = 0.132, p = 0.046 and ρ = 0.132, p = 0.046, respectively). No correlations between total, moderate or vigorous physical activity levels of the parents with the child's BMI or waist circumference were found. Looking at physical activity domains maternal physical activity in active commuting, either walking or biking, showed a negative correlation with BMI of the child (ρ = -0.062, p = 0.042).

Conclusions: Higher maternal BMI and lower maternal physical activity levels were related to lower levels of children's physical activity. More active commuting by the mother and a lower parental BMI were related to a lower BMI of the children. Energy-balance related behavior of the parents may contribute to a healthier BMI of both preschool children and their parents.
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October 2015

SORTA: a system for ontology-based re-coding and technical annotation of biomedical phenotype data.

Database (Oxford) 2015 18;2015. Epub 2015 Sep 18.

University of Groningen, University Medical Centre Groningen, Genomics Coordination Centre, Department of Genetics, Groningen, The Netherlands, University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands and LifeLines Cohort Study and Biobank, Groningen, The Netherlands

There is an urgent need to standardize the semantics of biomedical data values, such as phenotypes, to enable comparative and integrative analyses. However, it is unlikely that all studies will use the same data collection protocols. As a result, retrospective standardization is often required, which involves matching of original (unstructured or locally coded) data to widely used coding or ontology systems such as SNOMED CT (clinical terms), ICD-10 (International Classification of Disease) and HPO (Human Phenotype Ontology). This data curation process is usually a time-consuming process performed by a human expert. To help mechanize this process, we have developed SORTA, a computer-aided system for rapidly encoding free text or locally coded values to a formal coding system or ontology. SORTA matches original data values (uploaded in semicolon delimited format) to a target coding system (uploaded in Excel spreadsheet, OWL ontology web language or OBO open biomedical ontologies format). It then semi- automatically shortlists candidate codes for each data value using Lucene and n-gram based matching algorithms, and can also learn from matches chosen by human experts. We evaluated SORTA's applicability in two use cases. For the LifeLines biobank, we used SORTA to recode 90 000 free text values (including 5211 unique values) about physical exercise to MET (Metabolic Equivalent of Task) codes. For the CINEAS clinical symptom coding system, we used SORTA to map to HPO, enriching HPO when necessary (315 terms matched so far). Out of the shortlists at rank 1, we found a precision/recall of 0.97/0.98 in LifeLines and of 0.58/0.45 in CINEAS. More importantly, users found the tool both a major time saver and a quality improvement because SORTA reduced the chances of human mistakes. Thus, SORTA can dramatically ease data (re)coding tasks and we believe it will prove useful for many more projects. Database URL: or as an open source download from
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May 2016

Television, sleep, outdoor play and BMI in young children: the GECKO Drenthe cohort.

Eur J Pediatr 2015 May 1;174(5):631-9. Epub 2014 Nov 1.

Department of Epidemiology (FA40), University of Groningen, University Medical Center Groningen, P.O. Box 30.001, 9700 RG, Groningen, The Netherlands,

Unlabelled: In this study, we investigated the interplay between screen time, sleep duration, outdoor play, having a television in the bedroom and the number of televisions at home and their association with body mass index (BMI) in preschool children. All participants, 3-4 years of age (n = 759), were part of the Groningen expert center for kids with obesity (GECKO) Drenthe birth cohort. Weight and height were measured. Total screen time, number of televisions at home, a television in the bedroom, sleep duration and time of outdoor play were self-reported by parents in a questionnaire. Ordinary least square (OLS) regression-based path analysis was used to estimate direct and indirect effects on BMI in mediation models. A television in the bedroom or more televisions at home gave a higher screen time, which were associated with decreased sleep duration and resulted in higher BMI (indirect effect = 0.0115, 95% bootstrap interval = 0.0016; 0.0368 and indirect effect = 0.0026, 95% bootstrap interval = 0.0004; 0.0078, respectively). In contrast to the direct effect of screen time, sleep duration and a television in the bedroom on BMI, no direct effect was found for outdoor play and number or televisions at home on BMI.

Conclusions: Short sleep duration, long screen time and a television in the bedroom were associated with the presence of overweight in preschool children.
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May 2015

Energy requirements for maintenance and growth in 3- to 4-year-olds may be overestimated by existing equations.

J Pediatr Gastroenterol Nutr 2014 May;58(5):642-6

*Department of Epidemiology †Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

Objectives: To give appropriate dietary advice to preschool children, an estimation of their energy requirements for both maintenance and activity is needed. We compared energy requirements for maintenance, measured by indirect calorimetry against existing equations predicting these requirements in 3- to 4-year-old children.

Methods: In 30 children (age 3.4 ± 0.3) from the GECKO Drenthe cohort, height, weight, evening sleeping metabolic rate (SMR) (by indirect calorimetry), fat mass (FM), and fat-free mass (FFM) (by isotope dilution) were measured. For 25 children, a valid evening SMR was available as a measure for energy used for maintenance and growth. This SMR was compared with existing equations (Schofield, FAO/WHO/UNU, Oxford and Harris-Benedict). Correlations among SMR and weight, height, FM, and FFM were also calculated.

Results: From the existing equations, significant higher values, ranging from 58 to 144 kcal/day, were calculated for the BMR compared with the measured SMR results, indicating 8% to 19% overestimation. This overestimation is higher at lower ranges of energy requirement. SMR was positively related to weight (r = 0.488, P = 0.013), height (r = 0.499, P = 0.011), and FFM (r = 0.482, P = 0.027), but not to FM (r = 0.211, P = 0.358).

Conclusions: Existing equations show higher values for the energy used for maintenance in young children compared to the results of our measurements of the SMR. Energy used for maintenance is correlated with FFM and not with FM.
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May 2014

Waist-to-height ratio, waist circumference and BMI as indicators of percentage fat mass and cardiometabolic risk factors in children aged 3-7 years.

Clin Nutr 2014 Apr 23;33(2):311-5. Epub 2013 May 23.

Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. Electronic address:

Objective: To assess whether waist-to-height-ratio (WHtR) is a better estimate of body fat percentage (BF%) and a better indicator of cardiometabolic risk factors than BMI or waist circumference (WC) in young children.

Methods: WHtR, WC and BMI were measured by trained staff according to standardized procedures. (2)H2O and (2)H2(18)O isotope dilution were used to assess BF% in 61 children (3-7 years) from the general population, and bioelectrical impedance (Horlick equation) was used to assess BF% in 75 overweight/obese children (3-5 years). Cardiometabolic risk factors, including diastolic and systolic blood pressure, HOMA2-IR, leptin, adiponectin, triglycerides, total cholesterol, HDL- and LDL-cholesterol, TNFα and IL-6 were determined in the overweight/obese children.

Results: In the children from the general population, after adjustments for age and gender, BMI had the highest explained variance for BF% compared to WC and WHtR (R(2) = 0.32, 0.31 and 0.23, respectively). In the overweight/obese children, BMI and WC had a higher explained variance for BF% compared to WHtR (R(2) = 0.68, 0.70 and 0.50, respectively). In the overweight/obese children, WHtR, WC and BMI were all significantly positively correlated with systolic blood pressure (r = 0.23, 0.30, 0.36, respectively), HOMA2-IR (r = 0.53, 0.62, 0.63, respectively), leptin (r = 0.70, 0.77, 0.78, respectively) and triglycerides (r = 0.33, 0.36, 0.24, respectively), but not consistently with other parameters.

Conclusion: In young children, WHtR is not superior to WC or BMI in estimating BF%, nor is WHtR better correlated with cardiometabolic risk factors than WC or BMI in overweight/obese children. These data do not support the use of WHtR in young children.
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April 2014

Infant movement opportunities are related to early growth--GECKO Drenthe cohort.

Early Hum Dev 2013 Jul 28;89(7):457-61. Epub 2013 Apr 28.

Department of Epidemiology of the University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

Background: Movement by an infant during the first year of life might influence its activity level and thereby influence growth in early childhood.

Aim: To examine whether the time that an infant is able to move unrestrictedly and time spent in baby seats are related to weight and waist circumference at age 9 months and growth from 9 to 24 months.

Methods: In the GECKO Drenthe birth cohort, weight and height were measured in Well Baby Clinics at the ages of 9 and 24 months. Time spent moving unrestrictedly and time spent in baby seats were reported on a questionnaire at age 9 months. Children born <37 weeks or with a low birthweight (<2500 g) were excluded. Outcomes were defined as the Z-scores for weight-for-height, weight-for-age, and waist circumference-for-age at the ages of 9 and 24 months, and changes in Z-scores as between 9 and 24 months of age.

Results: The time an infant is able to move unrestrictedly at age 9 months was inversely related to Z-score waist circumference at 9 months, and the change in Z-scores weight-for-height and weight-for-age between the ages 9 and 24 months. For time spent in baby seats, 'never users' showed a decline in Z-score weight-for-height as compared to those who used baby seats. On the contrary, Z-score waist circumference-for-age declined in children sitting for 1h or more in baby seats.

Conclusion: More time spent moving unrestrictedly in infancy may contribute to a healthy growth pattern.
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July 2013

Validation of the TracmorD triaxial accelerometer to assess physical activity in preschool children.

Obesity (Silver Spring) 2013 Sep 2;21(9):1877-83. Epub 2013 Jul 2.

Department of Epidemiology, University of Groningen, UMCG, Groningen, The Netherlands.

Objectives: To assess validity evidence of TracmorD to determine energy used for physical activity in 3-4-year-old children.

Design And Methods: Participants were randomly selected from GECKO Drenthe cohort (n = 30, age 3.4 ± 0.3 years). Total energy expenditure (TEE) was measured using the doubly labeled water method. Sleeping metabolic rate (SMR) was measured by indirect calorimetry (Deltatrac). TEE and SMR were used to calculate physical activity level (PAL) and activity energy expenditure (AEE). Physical activity was monitored using a DirectLife triaxial accelerometer, TracmorD with activity counts per minute (ACM) and activity counts per day (ACD) as outcome measures.

Results: The best predictor for PAL was ACM with gender and weight, the best predictor for AEE was ACM alone (backward regression, R(2) = 0.50, P = 0.010 and R2 = 0.31, P = 0.011, respectively). With ACD, the prediction model for PAL included ACD, height, gender, and sleep duration (R2 = 0.48, P = 0.033), the prediction model for AEE included ACD, gender and sleep duration (R2 = 0.39, P = 0.042). The accelerometer was worn for 5 days, but 3 days did not give a different estimated PAL.

Conclusion: TracmorD provides moderate-to-strong validity evidence that supports its use to evaluate energy used for physical activity in 3-4-year-old children.
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September 2013

Is directly measured physical activity related to adiposity in preschool children?

Int J Pediatr Obes 2011 Oct 11;6(5-6):389-400. Epub 2011 Aug 11.

Department of Epidemiology, University Medical Center Groningen , University of Groningen,Groningen, Netherlands.

This review summarizes the association between directly assessed physical activity and adiposity in preschool children (age 1.5-6 years). It includes 17 cross-sectional and longitudinal studies that were published between January 1999 and February 2010. The association between physical activity and obesity seems to depend on the outcome measure of adiposity. In 60% (3/5) of the studies using percentage body fat, an inverse significant relationship with physical activity was found against 18% (2/11) of the studies that used body mass index as method to assess adiposity. Physical activity is inversely related to percentage body fat in preschool children. The associations between physical activity and body mass index as a measure of adiposity in preschool children remain elusive. Further studies using directly measured physical activity and percentage body fat to define adiposity are needed to draw more firm conclusions.
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October 2011