Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts
Objectives: Prevention of obesity should start as early as possible after birth. We aimed to build clinically useful equations estimating the risk of later obesity in newborns, as a first step towards focused early prevention against the global obesity epidemic. Methods: We analyzed the lifetime Nor...
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Online Access: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:10612548 https://doi.org/10.1371/journal.pone.0049919 |
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ftharvardudash:oai:dash.harvard.edu:1/10612548 2023-05-15T17:42:53+02:00 Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts Morandi, Anita Meyre, David Lobbens, Stéphane Kaakinen, Marika Vatin, Vincent Gaget, Stefan Pouta, Anneli Hartikainen, Anna-Liisa Laitinen, Jaana Ruokonen, Aimo Das, Shikta Khan, Anokhi Ali Elliott, Paul Maffeis, Claudio Järvelin, Marjo-Riitta Froguel, Philippe Kleinman, Ken Paul Rifas-Shiman, Sheryl Lynn Gillman, Matthew William 2012 application/pdf http://nrs.harvard.edu/urn-3:HUL.InstRepos:10612548 https://doi.org/10.1371/journal.pone.0049919 en_US eng Public Library of Science doi:10.1371/journal.pone.0049919 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3509134/pdf/ PLoS ONE Morandi, Anita, David Meyre, Stéphane Lobbens, Ken Paul Kleinman, Marika Kaakinen, Sheryl Lynn Rifas-Shiman, Vincent Vatin, et al. 2012. Estimation of newborn risk for child or adolescent obesity: Lessons from longitudinal birth cohorts. PLoS ONE 7(11): e49919. 1932-6203 http://nrs.harvard.edu/urn-3:HUL.InstRepos:10612548 Medicine Clinical Genetics Clinical Research Design Cohort Studies Endocrinology Pediatric Endocrinology Epidemiology Cardiovascular Disease Epidemiology Pediatric Epidemiology Non-Clinical Medicine Health Care Policy Health Risk Analysis Nutrition Obesity Pediatrics Neonatology Journal Article 2012 ftharvardudash https://doi.org/10.1371/journal.pone.0049919 2022-04-04T12:45:46Z Objectives: Prevention of obesity should start as early as possible after birth. We aimed to build clinically useful equations estimating the risk of later obesity in newborns, as a first step towards focused early prevention against the global obesity epidemic. Methods: We analyzed the lifetime Northern Finland Birth Cohort 1986 (NFBC1986) (N = 4,032) to draw predictive equations for childhood and adolescent obesity from traditional risk factors (parental BMI, birth weight, maternal gestational weight gain, behaviour and social indicators), and a genetic score built from 39 BMI/obesity-associated polymorphisms. We performed validation analyses in a retrospective cohort of 1,503 Italian children and in a prospective cohort of 1,032 U.S. children. Results: In the NFBC1986, the cumulative accuracy of traditional risk factors predicting childhood obesity, adolescent obesity, and childhood obesity persistent into adolescence was good: AUROC = 0·78[0·74–0.82], 0·75[0·71–0·79] and 0·85[0·80–0·90] respectively (all p<0·001). Adding the genetic score produced discrimination improvements ≤1%. The NFBC1986 equation for childhood obesity remained acceptably accurate when applied to the Italian and the U.S. cohort (AUROC = 0·70[0·63–0·77] and 0·73[0·67–0·80] respectively) and the two additional equations for childhood obesity newly drawn from the Italian and the U.S. datasets showed good accuracy in respective cohorts (AUROC = 0·74[0·69–0·79] and 0·79[0·73–0·84]) (all p<0·001). The three equations for childhood obesity were converted into simple Excel risk calculators for potential clinical use. Conclusion: This study provides the first example of handy tools for predicting childhood obesity in newborns by means of easily recorded information, while it shows that currently known genetic variants have very little usefulness for such prediction. Version of Record Article in Journal/Newspaper Northern Finland Harvard University: DASH - Digital Access to Scholarship at Harvard PLoS ONE 7 11 e49919 |
institution |
Open Polar |
collection |
Harvard University: DASH - Digital Access to Scholarship at Harvard |
op_collection_id |
ftharvardudash |
language |
English |
topic |
Medicine Clinical Genetics Clinical Research Design Cohort Studies Endocrinology Pediatric Endocrinology Epidemiology Cardiovascular Disease Epidemiology Pediatric Epidemiology Non-Clinical Medicine Health Care Policy Health Risk Analysis Nutrition Obesity Pediatrics Neonatology |
spellingShingle |
Medicine Clinical Genetics Clinical Research Design Cohort Studies Endocrinology Pediatric Endocrinology Epidemiology Cardiovascular Disease Epidemiology Pediatric Epidemiology Non-Clinical Medicine Health Care Policy Health Risk Analysis Nutrition Obesity Pediatrics Neonatology Morandi, Anita Meyre, David Lobbens, Stéphane Kaakinen, Marika Vatin, Vincent Gaget, Stefan Pouta, Anneli Hartikainen, Anna-Liisa Laitinen, Jaana Ruokonen, Aimo Das, Shikta Khan, Anokhi Ali Elliott, Paul Maffeis, Claudio Järvelin, Marjo-Riitta Froguel, Philippe Kleinman, Ken Paul Rifas-Shiman, Sheryl Lynn Gillman, Matthew William Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts |
topic_facet |
Medicine Clinical Genetics Clinical Research Design Cohort Studies Endocrinology Pediatric Endocrinology Epidemiology Cardiovascular Disease Epidemiology Pediatric Epidemiology Non-Clinical Medicine Health Care Policy Health Risk Analysis Nutrition Obesity Pediatrics Neonatology |
description |
Objectives: Prevention of obesity should start as early as possible after birth. We aimed to build clinically useful equations estimating the risk of later obesity in newborns, as a first step towards focused early prevention against the global obesity epidemic. Methods: We analyzed the lifetime Northern Finland Birth Cohort 1986 (NFBC1986) (N = 4,032) to draw predictive equations for childhood and adolescent obesity from traditional risk factors (parental BMI, birth weight, maternal gestational weight gain, behaviour and social indicators), and a genetic score built from 39 BMI/obesity-associated polymorphisms. We performed validation analyses in a retrospective cohort of 1,503 Italian children and in a prospective cohort of 1,032 U.S. children. Results: In the NFBC1986, the cumulative accuracy of traditional risk factors predicting childhood obesity, adolescent obesity, and childhood obesity persistent into adolescence was good: AUROC = 0·78[0·74–0.82], 0·75[0·71–0·79] and 0·85[0·80–0·90] respectively (all p<0·001). Adding the genetic score produced discrimination improvements ≤1%. The NFBC1986 equation for childhood obesity remained acceptably accurate when applied to the Italian and the U.S. cohort (AUROC = 0·70[0·63–0·77] and 0·73[0·67–0·80] respectively) and the two additional equations for childhood obesity newly drawn from the Italian and the U.S. datasets showed good accuracy in respective cohorts (AUROC = 0·74[0·69–0·79] and 0·79[0·73–0·84]) (all p<0·001). The three equations for childhood obesity were converted into simple Excel risk calculators for potential clinical use. Conclusion: This study provides the first example of handy tools for predicting childhood obesity in newborns by means of easily recorded information, while it shows that currently known genetic variants have very little usefulness for such prediction. Version of Record |
format |
Article in Journal/Newspaper |
author |
Morandi, Anita Meyre, David Lobbens, Stéphane Kaakinen, Marika Vatin, Vincent Gaget, Stefan Pouta, Anneli Hartikainen, Anna-Liisa Laitinen, Jaana Ruokonen, Aimo Das, Shikta Khan, Anokhi Ali Elliott, Paul Maffeis, Claudio Järvelin, Marjo-Riitta Froguel, Philippe Kleinman, Ken Paul Rifas-Shiman, Sheryl Lynn Gillman, Matthew William |
author_facet |
Morandi, Anita Meyre, David Lobbens, Stéphane Kaakinen, Marika Vatin, Vincent Gaget, Stefan Pouta, Anneli Hartikainen, Anna-Liisa Laitinen, Jaana Ruokonen, Aimo Das, Shikta Khan, Anokhi Ali Elliott, Paul Maffeis, Claudio Järvelin, Marjo-Riitta Froguel, Philippe Kleinman, Ken Paul Rifas-Shiman, Sheryl Lynn Gillman, Matthew William |
author_sort |
Morandi, Anita |
title |
Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts |
title_short |
Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts |
title_full |
Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts |
title_fullStr |
Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts |
title_full_unstemmed |
Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts |
title_sort |
estimation of newborn risk for child or adolescent obesity: lessons from longitudinal birth cohorts |
publisher |
Public Library of Science |
publishDate |
2012 |
url |
http://nrs.harvard.edu/urn-3:HUL.InstRepos:10612548 https://doi.org/10.1371/journal.pone.0049919 |
genre |
Northern Finland |
genre_facet |
Northern Finland |
op_relation |
doi:10.1371/journal.pone.0049919 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3509134/pdf/ PLoS ONE Morandi, Anita, David Meyre, Stéphane Lobbens, Ken Paul Kleinman, Marika Kaakinen, Sheryl Lynn Rifas-Shiman, Vincent Vatin, et al. 2012. Estimation of newborn risk for child or adolescent obesity: Lessons from longitudinal birth cohorts. PLoS ONE 7(11): e49919. 1932-6203 http://nrs.harvard.edu/urn-3:HUL.InstRepos:10612548 |
op_doi |
https://doi.org/10.1371/journal.pone.0049919 |
container_title |
PLoS ONE |
container_volume |
7 |
container_issue |
11 |
container_start_page |
e49919 |
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1766144805235064832 |