Ubiquitous internet access is reshaping the way we live, but it is accompanied by unprecedented challenges to prevent chronic diseases planted in long exposure to unhealthy lifestyles. This paper proposes leveraging online shopping behaviors as a proxy for personal lifestyle choices to freshen chronic disease prevention literacy targeted for times when e-commerce user experience has been assimilated into most people's daily life . Here, retrospective longitudinal query logs and purchase records from millions of online shoppers were accessed, constructing a broad spectrum of lifestyle features covering assorted product categories and buyer personas. Using the lifestyle-related information preceding their first purchases of prescription drugs, we could determine associations between online shoppers' past lifestyle choices and if they suffered from a particular chronic disease  . Novel lifestyle risk factors were discovered in two exemplars -- depression and diabetes, most of which showed cognitive congruence with existing healthcare knowledge. Further, such empirical findings could be adopted to locate online shoppers at high risk of  chronic diseases with fair accuracy (e.g., area under the receiver operating characteristic curve%DIFDELCMD < ] %%% AUC=0.68 for depression and AUC=0.70 for diabetes) , closely matching the performance of screening surveys benchmarked against medical diagnosis. Unobtrusive chronic disease surveillance via e-commerce sites may soon meet consenting individuals in the digital space they already inhabit.
Ubiquitous internet access is reshaping the way we live, but it is accompanied by unprecedented challenges in preventing chronic diseases planted by long exposure to unhealthy lifestyles. This paper proposes leveraging online shopping behaviors as a proxy for personal lifestyle choices to improve chronic disease prevention literacy targeted for times when e-commerce user experience has been assimilated into most people's daily lives . Here, retrospective longitudinal query logs and purchase records from millions of online shoppers were accessed, constructing a broad spectrum of lifestyle features covering assorted product categories and buyer personas. Using the lifestyle-related information preceding their first purchases of prescription drugs, we could determine associations between online shoppers' past lifestyle choices and whether they suffered from a particular chronic disease or not . Novel lifestyle risk factors were discovered in two exemplars -- depression and diabetes, most of which showed cognitive congruence with existing healthcare knowledge. Further, such empirical findings could be adopted to locate online shoppers at high risk of these chronic diseases with fair accuracy %DIFDELCMD < ] %%% , closely matching the performance of screening surveys benchmarked against medical diagnosis. Unobtrusive chronic disease surveillance via e-commerce sites may soon meet consenting individuals in the digital space they already inhabit.
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to prevent
in preventing
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freshen
improve
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life
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(e.g.,
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area under the receiver operating characteristic curve
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AUC=0.68 for depression and AUC=0.70 for diabetes)