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Nutrients 2017, 9(12), 1285;

The Prevalence of Vitamin A Deficiency in Chinese Children: A Systematic Review and Bayesian Meta-Analysis

Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, China
Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
Institute of Medical Humanities, Peking University, Beijing 100191, China
School of Foundational Education, Peking University, Beijing 100191, China
Author to whom correspondence should be addressed.
Received: 29 October 2017 / Revised: 19 November 2017 / Accepted: 21 November 2017 / Published: 25 November 2017
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Vitamin A deficiency (VAD), a leading cause of preventable childhood blindness, has been recognized as an important public health problem in many developing countries. In this study, we conducted a systematic review to identify all population-based studies of VAD and marginal VAD (MVAD) in Chinese children published from 1990 onwards. Hierarchical Bayesian meta-regressions were performed to examine the effects of age, sex, setting and year on the prevalence of VAD and MVAD, separately. The estimated prevalence was applied to the Chinese pediatric population in the year 2015 to generate prevalence estimates of VAD and MVAD for defined age groups, with 95% credible intervals (CrIs). Fifty-four studies met the inclusion criteria. The prevalence of VAD and MVAD both decreased with increasing age, and rural children had a higher prevalence of VAD and MVAD than urban children. In 2015, the prevalence of VAD was 5.16% (95% CrI: 1.95–12.64) and that of MVAD was 24.29% (95% CrI: 12.69–41.27) in Chinese children aged 12 years and under. VAD remains a public health problem in China. Efforts to reduce VAD in younger children are needed, especially for those in rural areas. View Full-Text
Keywords: Vitamin A deficiency; children; China Vitamin A deficiency; children; China

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Song, P.; Wang, J.; Wei, W.; Chang, X.; Wang, M.; An, L. The Prevalence of Vitamin A Deficiency in Chinese Children: A Systematic Review and Bayesian Meta-Analysis. Nutrients 2017, 9, 1285.

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