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Rating 7.7 Million Meals To Learn...

...that we think pizza is WAY healthier than it really is! From Massive Health (via Forbes Magazine): "Massive Health Analyzes 1/2 Million Meals to Understand Our Eating Habits [Infographics]."
"Over the past 5 months, Massive Health has collected over 7.68 million food ratings from people in 50 countries through The Eatery, an iPhone app that helps users track and analyze their eating patterns. Today, they are releasing some of their key findings about when people eat, where people eat, what they eat, and who they eat with, as a series of infographics. For more information about the company and to see the infographic detailing at how people think they eat (and how healthy they actually eat) click here.

"Key Finding on When We Eat

  • We eat 1.7 percent less healthy after each hour that passes in the day
  • Breakfast is the healthiest meal of the day. Dinner is 15.9 percent less healthy
  • People who eat breakfast eat 12.3 percent healthier during the day
  • On the weekend, we eat more unhealthy foods – including 1.4 times as many croissants and 1.6 times as much beer."
Can this self-reported 'crowdsourced' data be trusted? More, here, from foodandtechconnect.com:
"Collecting large-scale, real-time data about people’s diets, not just self-reported details about their eating habits, is nearly impossible. Yet, this data could help us and the medical community better address the rising obesity and diabetes epidemics. Over the past 5 months, Massive Health has collected over 7.68 million food ratings from people in 50 countries. Today, they are releasing some of their key findings about how people think they eat (and how healthy they actually eat), where people eat, what they eat, when they eat, and who they eat with, as a series of infographics.
“Famously, one of the most accurate ways to guess the number of jellybeans in a jar is to average the guesses of everyone in the room,” writes Massive Health co-founder and CTO Aza Raskin on the company blog. “The crowd-sourced method beats much more advanced algorithms. To test our hunch that the same applied in nutrition, we looked at the aggregate Eatery scores for all meals eaten in a city versus the published obesity level in that city. It turns out there’s a strong correlation. Eatery data can accurately predict obesity levels of cities in the United States. That is, Eatery data strongly correlates with the healthiness of its users.”
Now pardon me while I eat some oatmeal.

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