Literature DB >> 20948517

Factors associated with tracking of BMI: a meta-regression analysis on BMI tracking.

Otmar Bayer1, Helia Krüger, Rüdiger von Kries, André M Toschke.   

Abstract

Stable tracking of body composition is a prerequisite for the long-term effect of preventive measures against obesity and its harmful effects. As BMI tracking estimates reported by individual studies vary considerably, we performed a meta-regression analysis to provide a summary estimate and to assess determinants of BMI tracking. Using the Medline and EMBASE databases, a systematic review was conducted to identify publications reporting correlation coefficients as tracking estimates between BMI at baseline and follow-up measurements and the time interval between these measurements. Additional information recorded included age at baseline measurement, gender, and origin of the studied population. Based on the extracted data, a meta-regression analysis was performed using mixed effects models to account for multiple measurements of the same cohorts. Data on 55,072 individuals (797,094 person-years) extracted from 48 publications with follow-up times between 0.5 and 44 years entered the analysis. The overall estimates for the 1-year tracking correlation coefficient were strong (r = 0.78-0.86 depending on age at baseline measurement) and gradually decreasing over time (0.67-0.78 after 10 years, and 0.27-0.47 after 30 years). Study origin classified by continent was another significant predictor of BMI tracking whereas gender was not. In conclusion, this meta-regression analysis showed a high degree of BMI tracking across all age groups investigated and independent of BMI. Successful prevention in weight control is likely to have long term effects at any age, thereby being beneficial with respect to the associated risks of over- and underweight.

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Year:  2010        PMID: 20948517     DOI: 10.1038/oby.2010.250

Source DB:  PubMed          Journal:  Obesity (Silver Spring)        ISSN: 1930-7381            Impact factor:   5.002


  27 in total

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Review 3.  Drug interventions for the treatment of obesity in children and adolescents.

Authors:  Emma Mead; Greg Atkinson; Bernd Richter; Maria-Inti Metzendorf; Louise Baur; Nicholas Finer; Eva Corpeleijn; Claire O'Malley; Louisa J Ells
Journal:  Cochrane Database Syst Rev       Date:  2016-11-29

4.  Predicting the risk of childhood overweight and obesity at 4-5 years using population-level pregnancy and early-life healthcare data.

Authors:  Nida Ziauddeen; Sam Wilding; Paul J Roderick; Nicholas S Macklon; Dianna Smith; Debbie Chase; Nisreen A Alwan
Journal:  BMC Med       Date:  2020-05-11       Impact factor: 8.775

5.  The International Childhood Cardiovascular Cohort (i3C) consortium outcomes study of childhood cardiovascular risk factors and adult cardiovascular morbidity and mortality: Design and recruitment.

Authors:  Alan R Sinaiko; David R Jacobs; Jessica G Woo; Lydia Bazzano; Trudy Burns; Tian Hu; Markus Juonala; Ronald Prineas; Olli Raitakari; Julia Steinberger; Elaine Urbina; Alison Venn; Cashell Jaquish; Terry Dwyer
Journal:  Contemp Clin Trials       Date:  2018-04-22       Impact factor: 2.226

6.  Tracking of Obesity in Childhood into Adulthood: Effects on Body Mass Index and Fat Mass Index at Age 50.

Authors:  Andrew G Rundle; Pam Factor-Litvak; Shakira F Suglia; Ezra S Susser; Katrina L Kezios; Gina S Lovasi; Piera M Cirillo; Barbara A Cohn; Bruce G Link
Journal:  Child Obes       Date:  2020-04       Impact factor: 2.992

7.  Predicting childhood overweight and obesity using maternal and early life risk factors: a systematic review.

Authors:  N Ziauddeen; P J Roderick; N S Macklon; N A Alwan
Journal:  Obes Rev       Date:  2017-12-19       Impact factor: 9.213

8.  Subcutaneous fat mass in infancy and cardiovascular risk factors at school-age: The generation R study.

Authors:  Susana Santos; Romy Gaillard; Andreia Oliveira; Henrique Barros; Albert Hofman; Oscar H Franco; Vincent W V Jaddoe
Journal:  Obesity (Silver Spring)       Date:  2016-01-06       Impact factor: 5.002

9.  Anthropometry and the Risk of Lung Cancer in EPIC.

Authors:  Nikmah Utami Dewi; Hendriek C Boshuizen; Mattias Johansson; Paolo Vineis; Ellen Kampman; Annika Steffen; Anne Tjønneland; Jytte Halkjær; Kim Overvad; Gianluca Severi; Guy Fagherazzi; Marie-Christine Boutron-Ruault; Rudolf Kaaks; Kuanrong Li; Heiner Boeing; Antonia Trichopoulou; Christina Bamia; Eleni Klinaki; Rosario Tumino; Domenico Palli; Amalia Mattiello; Giovanna Tagliabue; Petra H Peeters; Roel Vermeulen; Elisabete Weiderpass; Inger Torhild Gram; José María Huerta; Antonio Agudo; María-José Sánchez; Eva Ardanaz; Miren Dorronsoro; José Ramón Quirós; Emily Sonestedt; Mikael Johansson; Kjell Grankvist; Tim Key; Kay-Tee Khaw; Nick Wareham; Amanda J Cross; Teresa Norat; Elio Riboli; Anouar Fanidi; David Muller; H Bas Bueno-de-Mesquita
Journal:  Am J Epidemiol       Date:  2016-07-01       Impact factor: 4.897

10.  Associations of Infant Subcutaneous Fat Mass with Total and Abdominal Fat Mass at School-Age: The Generation R Study.

Authors:  Susana Santos; Romy Gaillard; Andreia Oliveira; Henrique Barros; Marieke Abrahamse-Berkeveld; Eline M van der Beek; Albert Hofman; Vincent W V Jaddoe
Journal:  Paediatr Perinat Epidemiol       Date:  2016-05-26       Impact factor: 3.980

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