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Spatiotemporal Predictions of Obesity Prevalence in Chinese Children and Adolescents: Based on Analyses of Obesogenic Environmental Variability and Bayesian Model

OBJECTIVE: To find variations in Chinese obesogenic environmental priorities from 2000 to 2011, predict spatiotemporal distribution of obesity prevalence aged 7–17 years in 31 provinces, and provide foundations for policy-makers to reduce obesity in children and adolescents. METHODS: Based on data e...

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Autores principales: Guo, C, Wang, H, Feng, G, Li, J, Su, C, Zhang, J, Wang, Z, Du, W, Zhang, B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584073/
https://www.ncbi.nlm.nih.gov/pubmed/30568273
http://dx.doi.org/10.1038/s41366-018-0301-0
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author Guo, C
Wang, H
Feng, G
Li, J
Su, C
Zhang, J
Wang, Z
Du, W
Zhang, B
author_facet Guo, C
Wang, H
Feng, G
Li, J
Su, C
Zhang, J
Wang, Z
Du, W
Zhang, B
author_sort Guo, C
collection PubMed
description OBJECTIVE: To find variations in Chinese obesogenic environmental priorities from 2000 to 2011, predict spatiotemporal distribution of obesity prevalence aged 7–17 years in 31 provinces, and provide foundations for policy-makers to reduce obesity in children and adolescents. METHODS: Based on data examination of provincial obesity prevalence aged 7–17 years from 3 rounds of China Health and Nutrition Surveys (in 9 [2000], 9 [2006], and 12 [2011] provinces) and corresponding years’ environments in 31 provinces from China Statistical Yearbooks and other sources, 12 predictors were selected. We used 30 surveyed provinces in 3 rounds as training samples to fit three analytic models with partial least square regressions and prioritized predictors by Variable Importance Projection to find variations. And fitted a spatiotemporal prediction model with Bayesian analysis to infer in space-time. RESULTS: Variations of obesogenic environmental priorities were found at different times. A Bayesian spatiotemporal prediction model with deviance information criterion of 155.60 and statistically significant (P <0.05) parameter estimates of intercept (−717.0400, 95% confidence intervals [CI]: −1186.0300, −248.0480), year (0.3584, CI: 0.1245, 0.5924), square of food-industry level (0.0003, CI: 0.0002, 0.0004), and log (healthcare) (5.3742, CI: 2.5138, 8.2347) was optimized. Totally inferred average obesity prevalence among children and adolescents were 2.23%, 5.11%, 10.77%, 12.20%, 13.99%, and 17.58% in 31 provinces in China in 2000, 2006, 2011, 2015, 2020, and 2030, respectively. Obesity in north and east of China clusters on predicted maps. CONCLUSIONS: Obesity prevalence in children and adolescents in China is rapidly increasing, growing at 0.3584% annually from 2000 to 2011. From longitudinal observation, prevalence was significantly influenced by food industry (“Amplifier”) and healthcare service (“Balancer”). Targeted interventions in north and east of China are pressing. Further researches on the mechanisms underlying the influence of food industry, healthcare service and so on in children and adolescents are needed.
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spelling pubmed-65840732019-07-05 Spatiotemporal Predictions of Obesity Prevalence in Chinese Children and Adolescents: Based on Analyses of Obesogenic Environmental Variability and Bayesian Model Guo, C Wang, H Feng, G Li, J Su, C Zhang, J Wang, Z Du, W Zhang, B Int J Obes (Lond) Article OBJECTIVE: To find variations in Chinese obesogenic environmental priorities from 2000 to 2011, predict spatiotemporal distribution of obesity prevalence aged 7–17 years in 31 provinces, and provide foundations for policy-makers to reduce obesity in children and adolescents. METHODS: Based on data examination of provincial obesity prevalence aged 7–17 years from 3 rounds of China Health and Nutrition Surveys (in 9 [2000], 9 [2006], and 12 [2011] provinces) and corresponding years’ environments in 31 provinces from China Statistical Yearbooks and other sources, 12 predictors were selected. We used 30 surveyed provinces in 3 rounds as training samples to fit three analytic models with partial least square regressions and prioritized predictors by Variable Importance Projection to find variations. And fitted a spatiotemporal prediction model with Bayesian analysis to infer in space-time. RESULTS: Variations of obesogenic environmental priorities were found at different times. A Bayesian spatiotemporal prediction model with deviance information criterion of 155.60 and statistically significant (P <0.05) parameter estimates of intercept (−717.0400, 95% confidence intervals [CI]: −1186.0300, −248.0480), year (0.3584, CI: 0.1245, 0.5924), square of food-industry level (0.0003, CI: 0.0002, 0.0004), and log (healthcare) (5.3742, CI: 2.5138, 8.2347) was optimized. Totally inferred average obesity prevalence among children and adolescents were 2.23%, 5.11%, 10.77%, 12.20%, 13.99%, and 17.58% in 31 provinces in China in 2000, 2006, 2011, 2015, 2020, and 2030, respectively. Obesity in north and east of China clusters on predicted maps. CONCLUSIONS: Obesity prevalence in children and adolescents in China is rapidly increasing, growing at 0.3584% annually from 2000 to 2011. From longitudinal observation, prevalence was significantly influenced by food industry (“Amplifier”) and healthcare service (“Balancer”). Targeted interventions in north and east of China are pressing. Further researches on the mechanisms underlying the influence of food industry, healthcare service and so on in children and adolescents are needed. 2018-12-19 2019-07 /pmc/articles/PMC6584073/ /pubmed/30568273 http://dx.doi.org/10.1038/s41366-018-0301-0 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Guo, C
Wang, H
Feng, G
Li, J
Su, C
Zhang, J
Wang, Z
Du, W
Zhang, B
Spatiotemporal Predictions of Obesity Prevalence in Chinese Children and Adolescents: Based on Analyses of Obesogenic Environmental Variability and Bayesian Model
title Spatiotemporal Predictions of Obesity Prevalence in Chinese Children and Adolescents: Based on Analyses of Obesogenic Environmental Variability and Bayesian Model
title_full Spatiotemporal Predictions of Obesity Prevalence in Chinese Children and Adolescents: Based on Analyses of Obesogenic Environmental Variability and Bayesian Model
title_fullStr Spatiotemporal Predictions of Obesity Prevalence in Chinese Children and Adolescents: Based on Analyses of Obesogenic Environmental Variability and Bayesian Model
title_full_unstemmed Spatiotemporal Predictions of Obesity Prevalence in Chinese Children and Adolescents: Based on Analyses of Obesogenic Environmental Variability and Bayesian Model
title_short Spatiotemporal Predictions of Obesity Prevalence in Chinese Children and Adolescents: Based on Analyses of Obesogenic Environmental Variability and Bayesian Model
title_sort spatiotemporal predictions of obesity prevalence in chinese children and adolescents: based on analyses of obesogenic environmental variability and bayesian model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584073/
https://www.ncbi.nlm.nih.gov/pubmed/30568273
http://dx.doi.org/10.1038/s41366-018-0301-0
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