The "Lifestyle-Data-Only" Problem

tldr: Standalone lifestyle data can be extremely misleading. DNA and blood data is far superior, with a blended approach representing maximal accuracy.

Lifestyle data only

When the concept of personalizing supplements first hit the market (primarily in the 2016-ish range), the key players were what we call "Lifestyle Quiz Companies.” This name comes from the fact that they use a lifestyle questionnaire (or "quiz") to gather basic information about a customer and determine which nutrients they may need more of or less of.

Back then, this was great first step. It was a landmark move towards personalization and it aligned with the available capabilities from a technology and manufacturing perspective. 

Fast-forward five years. The market is exploding with new brands popping up monthly. Yet, still about 90% of the companies in this space still personalize solely based on information obtained from a lifestyle quiz.

This is troubling for a few reasons.

Most importantly, without context a simple lifestyle assessment can provide extremely misleading recommendations about which nutrients are needed and which are not. Without the context provided by DNA and blood data (providing key information about what is going on in the body), this “lifestyle-only” approach lacks all information about how your body is absorbing, distributing, metabolizing, and excreting nutrients. This is the data that matters most.

This metabolic data is essential to generate accurate and precise nutrient recommendations. For this reason, Rootine built its algorithm around DNA and blood data first, with lifestyle analysis providing only a baseline, directional layer of data that is not overly represented in the total model.

In addition, it shows that these new and old brands care more about profit than delivering optimal health to their consumers. The technology to analyze and compare multiple data sources exists, so why not use it?

When choosing a personalized multivitamin, ensure your choice considers multiple types of data (not just lifestyle) for an accurate and precise nutrient recommendation.