The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
The Generation R Study: design and cohort update 2017
Open accessAbstract
The Generation R Study is a population-based prospective cohort study from fetal life until adulthood. The study is designed to identify early environmental and genetic causes and causal pathways leading to normal and abnormal growth, development and health from fetal life, childhood and young adulthood. This multidisciplinary study focuses on several health outcomes including behaviour and cognition, body composition, eye development, growth, hearing, heart and vascular development, infectious disease and immunity, oral health and facial growth, respiratory health, allergy and skin disorders of children and their parents. Main exposures of interest include environmental, endocrine, genomic (genetic, epigenetic, microbiome), lifestyle related, nutritional and socio-demographic determinants. In total, 9778 mothers with a delivery date from April 2002 until January 2006 were enrolled in the study. Response at baseline was 61%, and general follow-up rates until the age of 10 years were around 80%. Data collection in children and their parents includes questionnaires, interviews, detailed physical and ultrasound examinations, behavioural observations, lung function, Magnetic Resonance Imaging and biological sampling. Genome and epigenome wide association screens are available. Eventually, results from the Generation R Study contribute to the development of strategies for optimizing health and healthcare for pregnant women and children.
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QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
The MOS 36-ltem Short-Form Health Survey (SF-36): I. Conceptual Framework and Item Selection
Ware, J. E., & Sherbourne, C. D. (1992) · Medical Care · doi:10.1097/00005650-199206000-00002 · Cited by 30,033
The Strengths and Difficulties Questionnaire: A research note
Goodman, R. (1997) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.1997.tb01545.x · Cited by 14,908
Detection of Postnatal Depression: Development of the 10-item Edinburgh Postnatal Depression Scale
Cox, J. L., Holden, J. M., & Sagovsky, R. (1987) · British Journal of Psychiatry · doi:10.1192/bjp.150.6.782 · Cited by 14,183
The brief symptom inventory: an introductory report.
Derogatis, L. R., & Melisaratos, N. (1983) · Psychological Medicine · doi:10.1017/s0033291700048017 · Cited by 6,650
Internet Addiction: The Emergence of a New Clinical Disorder
YOUNG, K. S. (1998) · CyberPsychology & Behavior · doi:10.1089/cpb.1998.1.237 · Cited by 5,513
Lloyd-Jones, D. M., Hong, Y., Labarthe, D., Mozaffarian, D., Appel, L. J., Van Horn, L., Greenlund, K., Daniels, S., Nichol, G., Tomaselli, G. F., et al. (2010) · Circulation · doi:10.1161/circulationaha.109.192703 · Cited by 4,750
TEST REVIEW behavior rating inventory of executive function.
Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000) · Child Neuropsychology · doi:10.1076/chin.6.3.235.3152 · Cited by 1,925
Constantino, J. N., Davis, S. A., Todd, R. D., Schindler, M. K., Gross, M. M., Brophy, S. L., Metzger, L. M., Shoushtari, C. S., Splinter, R., & Reich, W. (2003) · Journal of Autism and Developmental Disorders · doi:10.1023/a:1025014929212 · Cited by 1,611
Pain in children and adolescents: a common experience
Perquin, C. W., Hazebroek-Kampschreur, A. A. J. M., Hunfeld, J. A. M., Bohnen, A. M., van Suijlekom-Smit, L. W. A., Passchier, J., & van der Wouden, J. C. (2000) · Pain · doi:10.1016/s0304-3959(00)00269-4 · Cited by 1,114
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DNA methylation in newborns and maternal smoking in pregnancy: genome-wide consortium meta-analysis
Joubert, B. R., Felix, J. F., Yousefi, P., Bakulski, K. M., Just, A. C., Breton, C., Reese, S. E., Markunas, C. A., Richmond, R. C., Xu, C.-J., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.02.019 · Cited by 886
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Di Martino, A., O’Connor, D., Chen, B., Alaerts, K., Anderson, J. S., Assaf, M., Balsters, J. H., Baxter, L., Beggiato, A., Bernaerts, S., et al. (2017) · Scientific Data · doi:10.1038/sdata.2017.10 · Cited by 710
Risk factors and outcomes of maternal obesity and excessive weight gain during pregnancy
Gaillard, R., Durmuş, B., Hofman, A., Mackenbach, J. P., Steegers, E. A. P., & Jaddoe, V. W. V. (2013) · Obesity · doi:10.1002/oby.20088 · Cited by 490
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Kuriyama, S., Yaegashi, N., Nagami, F., Arai, T., Kawaguchi, Y., Osumi, N., Sakaida, M., Suzuki, Y., Nakayama, K., Hashizume, H., et al. (2016) · Journal of Epidemiology · doi:10.2188/jea.je20150268 · Cited by 359
Metadata
- Authors
- Kooijman, M. N., Kruithof, C. J., van Duijn, C. M., Duijts, L., Franco, O. H., van IJzendoorn, M. H., de Jongste, J. C., Klaver, C. C. W., van der Lugt, A., Mackenbach, J. P., Moll, H. A., Peeters, R. P., Raat, H., Rings, E. H. H. M., Rivadeneira, F., van der Schroeff, M. P., Steegers, E. A. P., Tiemeier, H., Uitterlinden, A. G., Verhulst, F. C., Wolvius, E., Felix, J. F., & Jaddoe, V. W. V.
- Venue
- European Journal of Epidemiology
- Published
- 2016-12
- Volume
- 31
- Issue
- 12
- Pages
- 1243-1264
- ISSN
- 0393-2990 (ISSN-L)
- 1573-7284
- OpenAlex
- W4210761116
- Cited by
- 1,214
- References
- 28
- FWCI
- 111.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Kooijman, M. N., Kruithof, C. J., van Duijn, C. M., Duijts, L., Franco, O. H., van IJzendoorn, M. H., de Jongste, J. C., Klaver, C. C. W., van der Lugt, A., Mackenbach, J. P., Moll, H. A., Peeters, R. P., Raat, H., Rings, E. H. H. M., Rivadeneira, F., van der Schroeff, M. P., Steegers, E. A. P., Tiemeier, H., Uitterlinden, A. G., . . . Jaddoe, V. W. V. (2016). The Generation R Study: design and cohort update 2017. European Journal of Epidemiology. https://doi.org/10.1007/s10654-016-0224-9
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.