Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys

Abstract Early childhood caries (ECC) is the most common chronic disease in young children. A reliable predictive model for ECC prevalence is needed in China as a decision supportive tool for planning health resources. In this study, we first established the autoregressive integrated moving average...

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Autores principales:	Xiaonan Zhang, Lei Zhang, Yonghong Zhang, Zhaoying Liao, Jinlin Song
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ae4388d51d604eb2afc638c6b033d5c4
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spelling	oai:doaj.org-article:ae4388d51d604eb2afc638c6b033d5c42021-12-02T12:32:42ZPredicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys10.1038/s41598-017-06626-w2045-2322https://doaj.org/article/ae4388d51d604eb2afc638c6b033d5c42017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-06626-whttps://doaj.org/toc/2045-2322Abstract Early childhood caries (ECC) is the most common chronic disease in young children. A reliable predictive model for ECC prevalence is needed in China as a decision supportive tool for planning health resources. In this study, we first established the autoregressive integrated moving average (ARIMA) model and grey predictive model (GM) based on the estimated national prevalence of ECC with meta-analysis from the published articles. The pooled data from 1988 to 2010 were used to establish the model, while the data from 2011 to 2013 were used to validate the models. The fitting and prediction accuracy of the two models were evaluated by mean absolute error (MAE) and mean absolute percentage error (MAPE). Then, we forecasted the annual prevalence from 2014 to 2018, which was 55.8%, 53.5%, 54.0%, 52.9%, 51.2% by ARIMA model and 52.8%, 52.0%, 51.2%, 50.4%, 49.6% by GM. The declining trend in ECC prevalence may be attributed to the socioeconomic developments and improved public health service in China. In conclusion, both ARIMA and GM models can be well applied to forecast and analyze the trend of ECC; the fitting and testing errors generated by the ARIMA model were lower than those obtained from GM.Xiaonan ZhangLei ZhangYonghong ZhangZhaoying LiaoJinlin SongNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaonan Zhang Lei Zhang Yonghong Zhang Zhaoying Liao Jinlin Song Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys
description	Abstract Early childhood caries (ECC) is the most common chronic disease in young children. A reliable predictive model for ECC prevalence is needed in China as a decision supportive tool for planning health resources. In this study, we first established the autoregressive integrated moving average (ARIMA) model and grey predictive model (GM) based on the estimated national prevalence of ECC with meta-analysis from the published articles. The pooled data from 1988 to 2010 were used to establish the model, while the data from 2011 to 2013 were used to validate the models. The fitting and prediction accuracy of the two models were evaluated by mean absolute error (MAE) and mean absolute percentage error (MAPE). Then, we forecasted the annual prevalence from 2014 to 2018, which was 55.8%, 53.5%, 54.0%, 52.9%, 51.2% by ARIMA model and 52.8%, 52.0%, 51.2%, 50.4%, 49.6% by GM. The declining trend in ECC prevalence may be attributed to the socioeconomic developments and improved public health service in China. In conclusion, both ARIMA and GM models can be well applied to forecast and analyze the trend of ECC; the fitting and testing errors generated by the ARIMA model were lower than those obtained from GM.
format	article
author	Xiaonan Zhang Lei Zhang Yonghong Zhang Zhaoying Liao Jinlin Song
author_facet	Xiaonan Zhang Lei Zhang Yonghong Zhang Zhaoying Liao Jinlin Song
author_sort	Xiaonan Zhang
title	Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys
title_short	Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys
title_full	Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys
title_fullStr	Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys
title_full_unstemmed	Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys
title_sort	predicting trend of early childhood caries in mainland china: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/ae4388d51d604eb2afc638c6b033d5c4
work_keys_str_mv	AT xiaonanzhang predictingtrendofearlychildhoodcariesinmainlandchinaacombinedmetaanalyticandmathematicalmodellingapproachbasedonepidemiologicalsurveys AT leizhang predictingtrendofearlychildhoodcariesinmainlandchinaacombinedmetaanalyticandmathematicalmodellingapproachbasedonepidemiologicalsurveys AT yonghongzhang predictingtrendofearlychildhoodcariesinmainlandchinaacombinedmetaanalyticandmathematicalmodellingapproachbasedonepidemiologicalsurveys AT zhaoyingliao predictingtrendofearlychildhoodcariesinmainlandchinaacombinedmetaanalyticandmathematicalmodellingapproachbasedonepidemiologicalsurveys AT jinlinsong predictingtrendofearlychildhoodcariesinmainlandchinaacombinedmetaanalyticandmathematicalmodellingapproachbasedonepidemiologicalsurveys
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Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys

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