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Web search activity data accurately predict population chronic disease risk in the USA
journal contribution
posted on 2015-01-01, 00:00 authored by Thin NguyenThin Nguyen, Truyen TranTruyen Tran, Wei LuoWei Luo, Sunil GuptaSunil Gupta, Santu RanaSantu Rana, Quoc-Dinh Phung, Melanie NicholsMelanie Nichols, Lynne Millar, Svetha VenkateshSvetha Venkatesh, Steven AllenderSteven AllenderBACKGROUND: The WHO framework for non-communicable disease (NCD) describes risks and outcomes comprising the majority of the global burden of disease. These factors are complex and interact at biological, behavioural, environmental and policy levels presenting challenges for population monitoring and intervention evaluation. This paper explores the utility of machine learning methods applied to population-level web search activity behaviour as a proxy for chronic disease risk factors. METHODS: Web activity output for each element of the WHO's Causes of NCD framework was used as a basis for identifying relevant web search activity from 2004 to 2013 for the USA. Multiple linear regression models with regularisation were used to generate predictive algorithms, mapping web search activity to Centers for Disease Control and Prevention (CDC) measured risk factor/disease prevalence. Predictions for subsequent target years not included in the model derivation were tested against CDC data from population surveys using Pearson correlation and Spearman's r. RESULTS: For 2011 and 2012, predicted prevalence was very strongly correlated with measured risk data ranging from fruits and vegetables consumed (r=0.81; 95% CI 0.68 to 0.89) to alcohol consumption (r=0.96; 95% CI 0.93 to 0.98). Mean difference between predicted and measured differences by State ranged from 0.03 to 2.16. Spearman's r for state-wise predicted versus measured prevalence varied from 0.82 to 0.93. CONCLUSIONS: The high predictive validity of web search activity for NCD risk has potential to provide real-time information on population risk during policy implementation and other population-level NCD prevention efforts.
History
Journal
Journal of epidemiology and community healthVolume
69Issue
7Pagination
693 - 699Publisher
BMJ Publishing GroupLocation
London, Eng.Publisher DOI
eISSN
1470-2738Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2015, BMJ Publishing GroupUsage metrics
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