Summer 2018

Tufts Nutrition Top 10

How we're using big data to improve health.

By Helene Ragovin

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From fighting famine to improving food safety to providing a richer trove of material for researchers to mine, “big data” is transforming nutrition. But the name is something of a misnomer—volume is not the only important characteristic. According to Professor Elena Naumova, chair of the Nutrition Data Science division at the Friedman School, 21st century technology—particularly increased computing capacity—lets us get richer data than ever, delivered faster than ever. We can plumb an expanded variety of data forms, from spreadsheets to X-rays to videos. At the same time, as more of our daily activities generate information, access and security become paramount. “With big data comes big responsibility,” Naumova said. Here are some of the ways researchers are using big data for good.

Fighting Famine and Food Insecurity

Real-time monitoring of factors that contribute to food shortages—crop yields, weather and climate, fluctuation in food prices—can lead to interventions before a crisis. Naumova is leading a study, funded by the federal Intelligence Advanced Research Projects Activity program, that combines data from multiple sources to forecast famine alerts and trends in malnutrition. This team is also developing ways to use global surveillance systems to forecast infectious-disease outbreaks and their effect on famine.

Mining Data from Large-Scale Studies

Advanced computing and analysis lets researchers uncover significant patterns in epidemiological studies, and to pool the results of large numbers of studies. The Friedman School’s Renata Micha has analyzed individual-level records from two hundred and sixty-six surveys worldwide, to identify key challenges and opportunities for optimizing diets and informing policies on global health.

Expanding Data Collection with Everyday Devices

Devices and apps now let average people record continuous health and nutrition data, including that from personal medical devices, such as glucose meters. Apps help people keep track of how environmental factors affect their medical conditions. Smartphones can also improve the veracity of self-reported data— instead of keeping written food diaries, study subjects can send photographs of their meals directly to researchers. Nicola McKeown, an epidemiologist at the Human Nutrition Research Center on Aging, and her team enlisted writers and public figures with large social-media followings to recruit more than 14,000 potential participants for a study on dietary patterns.

Improving Productivity

Graham Jeffries, N18, a postdoctoral fellow at the Friedman School, has used remotely sensed data and agricultural modeling to predict crop productivity in Brazil, and to quantify the effect of climate change on soy production. Cargill, the agricultural conglomerate, has developed an app that lets dairy farmers analyze their herds, and reports that Italian users increased milk production on their farms by nearly 12 percent.

Predicting Agricultural Crises

Machine-learning can use past data to predict future conditions. After an analysis of a decade of weather and crop data in Colombia pointed to a looming 2014 drought, The International Center for Tropical Agriculture advised farmers to skip a rice-planting season—and saved them millions of dollars in lost crops. Recently, Friedman School doctoral student Aishwarya Venkat, EG18, compared data on groundwater in California’s overdrafted eastern San Joaquin Valley basin to understand trends in groundwater consumption, crop portfolios, and crop-switching practices during and after drought.

Monitoring Food Safety

Adjunct Assistant Professor Kenneth Kwon Ho Chui, MG05, NG05, NG09, and Naumova examined over 300 million hospitalization records to study the impact of USDA regulations for Salmonella testing in meat-processing plants. The World Health Organization’s FOSCOLLAB platform integrates data on chemical use, growth conditions of microorganisms, and weather, to alert farmers and authorities to the possible presence of biohazards before they enter the food chain.

Following Food through Supply Chains

Manufacturers, distributors, and vendors can follow their products from farm to factory to store, while also monitoring the condition of that food, such as temperature and shelf life. To help reduce food-safety hazards, Walmart can now remotely monitor the internal temperature of rotisserie chickens.

Tracking Outbreaks

Analysis of social media sites, such as Facebook and Yelp, can improve recall efficiency by providing real-time information about the spread of food poisoning. In preparation for the Nutrition Data Summit at the Friedman School, a student-led initiative scheduled for October, a team of students plans a hackathon to analyze about one million FoodNet outbreak reports to look for seasonal and geographical patterns.

Enabling Better Consumer Choices

Mobile support tools can improve food choices at home and away from it. As an example, the FoodSwitch smartphone app, developed by the George Institute for Global Health in Australia, lets users scan bar codes of packaged foods to obtain nutritional information and a list of healthier alternatives.

Combating Obesity

In 2010, the Healthy Weight Commitment Foundation obtained a pledge from sixteen leading food companies to eliminate 1.5 trillion calories from their products by 2015. To document their efforts, they used a system that linked commercial data on individual sales with nutrient profiles and dietary intake data from the National Health and Nutrition Examination Survey. According to this tracking, a total of 6.4 trillion calories was eventually removed from the products.

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