Cargando…

Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health

This study aimed to construct a childhood obesity risk index based on predictors identified in pregnant women and 1-yr-old infants. The primary outcome was an identified obesity index of > 20% at 6–8 yr of age. Of a total sample size of 6,846 mother-child pairs, 80% and 20% were randomly allocate...

Descripción completa

Detalles Bibliográficos
Autores principales: Saijo, Yasuaki, Ito, Yoshiya, Yoshioka, Eiji, Sato, Yukihiro, Minatoya, Machiko, Araki, Atsuko, Miyashita, Chihiro, Kishi, Reiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Japanese Society for Pediatric Endocrinology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646240/
https://www.ncbi.nlm.nih.gov/pubmed/31384099
http://dx.doi.org/10.1297/cpe.28.81
_version_ 1783437529814401024
author Saijo, Yasuaki
Ito, Yoshiya
Yoshioka, Eiji
Sato, Yukihiro
Minatoya, Machiko
Araki, Atsuko
Miyashita, Chihiro
Kishi, Reiko
author_facet Saijo, Yasuaki
Ito, Yoshiya
Yoshioka, Eiji
Sato, Yukihiro
Minatoya, Machiko
Araki, Atsuko
Miyashita, Chihiro
Kishi, Reiko
author_sort Saijo, Yasuaki
collection PubMed
description This study aimed to construct a childhood obesity risk index based on predictors identified in pregnant women and 1-yr-old infants. The primary outcome was an identified obesity index of > 20% at 6–8 yr of age. Of a total sample size of 6,846 mother-child pairs, 80% and 20% were randomly allocated to the derivation and validation cohorts, respectively. For the derivation cohort, univariate and multivariate logistic regression analyses of data were conducted to identify the final predictors to determine the childhood obesity risk score algorithm. These included pre-pregnancy body mass index (BMI), child’s gender, smoking during pregnancy, education, and obesity index at one yr of age. The β coefficients for categories of predictor variables were each divided by the smallest value among them. The quotient was rounded off to the integer and assigned to the risk score, and a value of zero was assigned to reference categories. A total risk score was calculated for each individual. A cutoff point ≥ 16 had 22.2% and 21.8% positive predictive values in the derivation and validation cohorts, respectively. In conclusion, the childhood obesity risk score algorithm was constructed based on generic predictors that can be easily obtained from maternal and child health handbooks.
format Online
Article
Text
id pubmed-6646240
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher The Japanese Society for Pediatric Endocrinology
record_format MEDLINE/PubMed
spelling pubmed-66462402019-08-05 Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health Saijo, Yasuaki Ito, Yoshiya Yoshioka, Eiji Sato, Yukihiro Minatoya, Machiko Araki, Atsuko Miyashita, Chihiro Kishi, Reiko Clin Pediatr Endocrinol Original Article This study aimed to construct a childhood obesity risk index based on predictors identified in pregnant women and 1-yr-old infants. The primary outcome was an identified obesity index of > 20% at 6–8 yr of age. Of a total sample size of 6,846 mother-child pairs, 80% and 20% were randomly allocated to the derivation and validation cohorts, respectively. For the derivation cohort, univariate and multivariate logistic regression analyses of data were conducted to identify the final predictors to determine the childhood obesity risk score algorithm. These included pre-pregnancy body mass index (BMI), child’s gender, smoking during pregnancy, education, and obesity index at one yr of age. The β coefficients for categories of predictor variables were each divided by the smallest value among them. The quotient was rounded off to the integer and assigned to the risk score, and a value of zero was assigned to reference categories. A total risk score was calculated for each individual. A cutoff point ≥ 16 had 22.2% and 21.8% positive predictive values in the derivation and validation cohorts, respectively. In conclusion, the childhood obesity risk score algorithm was constructed based on generic predictors that can be easily obtained from maternal and child health handbooks. The Japanese Society for Pediatric Endocrinology 2019-07-20 2019 /pmc/articles/PMC6646240/ /pubmed/31384099 http://dx.doi.org/10.1297/cpe.28.81 Text en 2019©The Japanese Society for Pediatric Endocrinology This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (by-nc-nd) License. (CC-BY-NC-ND 4.0: http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Saijo, Yasuaki
Ito, Yoshiya
Yoshioka, Eiji
Sato, Yukihiro
Minatoya, Machiko
Araki, Atsuko
Miyashita, Chihiro
Kishi, Reiko
Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health
title Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health
title_full Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health
title_fullStr Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health
title_full_unstemmed Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health
title_short Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health
title_sort identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: an analysis of the data of the hokkaido study on environment and children’s health
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646240/
https://www.ncbi.nlm.nih.gov/pubmed/31384099
http://dx.doi.org/10.1297/cpe.28.81
work_keys_str_mv AT saijoyasuaki identifyingariskscoreforchildhoodobesitybasedonpredictorsidentifiedinpregnantwomenand1yearoldinfantsananalysisofthedataofthehokkaidostudyonenvironmentandchildrenshealth
AT itoyoshiya identifyingariskscoreforchildhoodobesitybasedonpredictorsidentifiedinpregnantwomenand1yearoldinfantsananalysisofthedataofthehokkaidostudyonenvironmentandchildrenshealth
AT yoshiokaeiji identifyingariskscoreforchildhoodobesitybasedonpredictorsidentifiedinpregnantwomenand1yearoldinfantsananalysisofthedataofthehokkaidostudyonenvironmentandchildrenshealth
AT satoyukihiro identifyingariskscoreforchildhoodobesitybasedonpredictorsidentifiedinpregnantwomenand1yearoldinfantsananalysisofthedataofthehokkaidostudyonenvironmentandchildrenshealth
AT minatoyamachiko identifyingariskscoreforchildhoodobesitybasedonpredictorsidentifiedinpregnantwomenand1yearoldinfantsananalysisofthedataofthehokkaidostudyonenvironmentandchildrenshealth
AT arakiatsuko identifyingariskscoreforchildhoodobesitybasedonpredictorsidentifiedinpregnantwomenand1yearoldinfantsananalysisofthedataofthehokkaidostudyonenvironmentandchildrenshealth
AT miyashitachihiro identifyingariskscoreforchildhoodobesitybasedonpredictorsidentifiedinpregnantwomenand1yearoldinfantsananalysisofthedataofthehokkaidostudyonenvironmentandchildrenshealth
AT kishireiko identifyingariskscoreforchildhoodobesitybasedonpredictorsidentifiedinpregnantwomenand1yearoldinfantsananalysisofthedataofthehokkaidostudyonenvironmentandchildrenshealth