Our App will let you understand and interpret your Metabolic Health

If your BMI is over 25 or you sense that you are at risk for long-term disease, please consider enrolling in our study. We hope to find individuals who are at risk of serious long-term health consequences due to their current weight, but you are welcome to enroll regardless of your current health status, so long as you understand the consent process and study design

A ResearchKit App for tracking, plotting, and understanding your Metabolic Health

By looking at your own health metrics over time you not only benefit yourself, you contribute to medical science

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Enabling comparisons

You control the characteristics of your comparison group

Chart your Metabolic Health

Follow your changes over time, along with a comparison to others, both in table and in graphical formats.

Compare yourself to Others

You can filter based on age, weight, etc and let yourself see how you are doing relative to others in the study

Add food events by Siri

Track your food in the simplest way by entering food log events by using Siri

Correlate your data

By comparing, plotting, and analyzing you will be more aware of your current health status and how it is changing

Contribute to Medical Science

Your information will be securely protected. We separate personally identifiable information from aggregate data. You can track your own metabolic information on your iPhone and contribute with the comfort of knowing that you have added anonymous data to our medical study



Provides insight into your HealthKit Data

By seeing how you compare with others, you both contribute to medical science and enable yourself to compare with your peers. We let you see parts of your HealthKit data in a new context, both by knowing that you are contributing to medical science and partly by being able to compare your own metrics against those of others. This is similar to the growth charts that pediatricians use at well-baby visits to enable new parents to tell how well their children are growing.

Filter based on your initial weight, on your age, ...

You control the comparison points. You can change those comparisons as often as you want to provide many different views of how you are doing. By providing you with an ongoing context for viewing your personal changes you can decide whether you are doing well, poorly, or on average, the same, as your perceived compatriots.

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Siri Integration

Speak your food entries into an ongoing food log. This lets you track how long you are spending in eating and how long in fasting within each 24-hour period. Research has suggested that having a narrow eating window and a longer fasting period may lead to beneficial health effects.

Track your sleep, your exercise, your weight, your daily rhythms

Research has suggested that knowing when you eat, when you exercise, and how well you sleep can improve your health. At the same time that you benefit your own long-term health, you are making a real contribution to medical research.

Discover new Insights into your Health

By charting your progress you benefit both yourself and our knowledge of human metabolic health

iPhone App

Please visit the Apple App Store to download and begin the consent process. It is simple and straightforward to start the consent process and to begin the process of using our App. We have purposely chosen not to bother you with daily, weekly or even monthly survey polls or activities. Our study is the collective bringing together of information on metabolic health. You will be able to see the changes in your own metrics and to see the changes in the anonymous aggregate behavior of others. This study is being led by Professor Thomas Woolf (Johns Hopkins) and brings together twenty-six researchers across eight different institutions.

Our Team

We represent a breadth of researchers and their insights, spanning clinical work, through the basic sciences and into data systems

Clinical Correlations

Our clinical research work covers a broad spectrum of patients and we will be looking for correlations between our participants and their entrance into or their improvement from their initial entrance points

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Clinical

Jeanne Clark

Johns Hopkins University

Medicine and Epidemiology
Baltimore, MD

Leads our clinical insights team and has led several multi-center landmark public health trials: e.g. Diabetes Prevention Program.

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Clinical

Phyliss Zee

Northwestern

School of Medicine
Chicago, Ill

World expert on the neurology of sleep disorders and their impact on human health. Recent work on impact of light.

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Clinical

Vsevolod Polotsky

Johns Hopkins University

Pulmonary and Critical Care
Baltimore, MD

Leads research on chronic obstructive pulmonary disease, hypoxia, obesity and metabolic syndrome in mice and humans.

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Clinical

James Hamilton

Johns Hopkins University

Pulmonary and Critical Care
Baltimore, MD

Leads research and sees patients involved with fatty liver disease and helped plan the initial stages of this study.

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Clinical

Naresh Punjabi

Johns Hopkins University

Medicine and Epidemiology
Baltimore, MD

Leads research into the clinical manifestations of diabetes and sleep disorders: sleep apnea on cardiovascular outcomes.

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Clinical

Bob Eckel

University of Colorado

Endocrine & Diabetes
Denver, CO

Is exploring the connections between nutrition, insulin action, energy balance and body weight regulation in humans and mice

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Clinical

Ruth Patterson

University of California

Family Medicine & Public Health
San Diego, CA

Was co-PI of the Women's Health Initiative; pursuing clinical research on obesity and diabetic disease in the context of cancer

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Clinical

Dorothy Sears

University of California

Endrocrinology and Metabolism
San Diego, CA

Fascinated by genes and metabolites that are regulators of insulin resistance and looking for novel therapeutic targets.

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Clinical

Willa Hsueh

Ohio State University

Endocrinology & Metabolism
Columbus, OH

Working on clinical practice as well as research projects aimed at diabetes, hypertension and their complications in humans.

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Clinical

Rebecca Jackson

Ohio State University

Endocrinology & Metabolism
Columbus, OH

Fascinated by metabolic bone disease and its connections to human health: an expert in hormones & bone loss in women.

Basic Science Insight

Fundamental findings in lab animals led to the initial insights behind our Metabolic Compass App. We hope to continue to explore the implications of new findings based on our study and that this will inspire new experimental work. At the same time new, ongoing, experiments, will help us to further refine and understand our evolving insights into our human behaviors and outcomes

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Basic Sciences

Satchin Panda

Salk Institute

Regulatory Biology Laboratory
La Jolla, CA

Leads our basic science team; His lab's research on time restricted feeding in mice led to our collective curiousity.

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Basic Sciences

Ken Wright

University of Colorado

Integrative Physiology
Boulder, CO

Leads research into the impact of changes in our sleep schedules on human health; the impact of shift work on metabolic health

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Basic Sciences

Paolo Sassone Corsi

University of California

Biological Chemistry
Irvine, CA

A pioneer on the impact of circadian rhythms on animal health and wellbeing; has led conceptual understanding.

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Basic Sciences

Mark Mattson

NIH

Bayview Campus
Baltimore, MD

A world expert on the nervous system and aging, with major discoveries on cirdadian and timing aspects of neural health.

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Basic Sciences

Xianlin Han

Sanford-Burnham Research

Cardiovascular Metabolic
Orlando, FL

Has developed new methods for lipidomics and the associated profiles for active ingredients in blood for both mice and human.

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Basic Sciences

Will Wong

Johns Hopkins University

Physiology
Baltimore, MD

Research directed at the molecular mechanisms of weight control in the mouse; this has implications for human health.

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Basic Sciences

Svetlana Lutsenko

Johns Hopkins University

Physiology
Baltimore, MD

Pursuing the importance of copper, and, other metals in blood chemistry, liver disease and weight regulation and control

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Basic Sciences

Randy Nelson

Ohio State University

Neuroscience
Columbus, OH

Showed the impact of light levels, and circadian biology, on night sleep/work; continued research on the neuroscience of sleep

Data Sciences

We will be collecting data at a rate and with a volume that is outstanding for seeing progress towards our goals. But, seeing into this large dataset -- finding new trends and correlations -- is beyond the realm of traditional 'spreadsheet' statistics. Our data sciences team will be using ideas from machine learning to address our current hypothesis about the main variables that impact on metabolic health. In addition, maintaining and expanding our iOS platform and our data backend will require continuing effort from our Data Sciences Team.

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Data Sciences

Yanif Ahmad

Johns Hopkins University

Computer Science
Baltimore, MD

Leading our data systems team and instrumental in our initial code and database development; expert in streaming systems.

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Data Sciences

Suchi Saria

Johns Hopkins University

Computer Science
Baltimore, MD

A pioneer in the application of new algorithms for graphical models related to health systems and time domain systems.

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Data Sciences

Raman Arora

Johns Hopkins University

Computer Science
Baltimore, MD

An expert in machine learning and correlations in large datasets and in the design of algorithms to maximize use of large data

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Data Sciences

Ilya Shpitser

Johns Hopkins University

Computer Science
Baltimore, MD

Has developed analysis tools for dealing with and extracting causal connections from large clinically oriented datasets

Our combined efforts involve twenty-six investigators over eight different institutions.

The Consent Process

First download our App from the App Store and click the Welcome Screen

Checking your Appropriateness for the Study

You need to be over 18, residing in the United States, and comfortable with English

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Step 1: Eligibility

Starting the Consent Flow

We will then tell you more about the study, our approach to data collection, and your iphone

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Step 2: Informed consent

Final consent and consent document

After you've finished the consent process we send you an e-mail with your consent document and you create a new login account using our secure server, from this point on, you'll be able to contribute anonymously to our study. We will ask you to enable sharing of HealthKit data and to let us write new events into your iCal.

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Step 3: Consent signing

Our Goals

We hope to learn the differences in how you navigate your daily tasks; to assess whether mobile devices and sensors can help better measure and manage our lives; and to ultimately improve the quality of life for people. This study is unique in that it allows participants to step up as equal partners in both the monitoring and the sharing of their aggregate data as well as in the research process and analysis.

  • All Values Shared

  • You enable everything in HealthKit and items added to HealthKit
  • You add food/exercise/sleep daily
  • You view your progress on the App Dashboard
  • You filter your comparisons on the Dashboard View
  • You look graphically at your values over time
  • You compare one of your metrics vs another (e.g. sleep vs weight)
  • You use Siri for tracking when you eat
  • You share a subset of your Metabolic Measures

  • You control which items to share and when to share them
  • You can change your sharing options at any time in the study
  • You can enter eating times at the end of the day
  • You can compare your progress to your friends, if both of you are enrolled in the study
  • You can filter your comparison points to be very specific or very broad
  • You can use this App to change your approach to Metabolic Health
  • Begin now by starting the consent process

You can design how you want to contribute to the study and how you want to use the App

To Contact Us

Contact point: Thomas Woolf

Johns Hopkins University, School of Medicine
725 N. Wolfe St.
Baltimore, MD 21205