ILSI Energy Balance Study

Children's Mercy Hospital Kansas City

Status: Completed

Conditions: Physical Activity

Study type: Observational

Funder types: Other

Identifiers

NCT04142281

17030190

Details and patient eligibility

About

The purpose of this study is to apply measurement error techniques on consumer devices to assess rate of energy storage [ES] and energy expenditure [EE], then estimate EI using the intake-balance technique.

The goal of this study is to develop calibration models that will be able to be translated to other consumer devices with only minor modifications given common hardware (e.g. triaxial accelerometry), resulting in overall improved ability to assess energy balance and EI at a population level and positive health outcomes.

Full description

There are four stages in the proposed project: 1) We will validate EE and ES (hereafter, Fitbit_EE and Fitbit_ES) from a consumer physical activity monitor (Fitbit Alta HR™) and body composition analyzer (Fitbit Aria™) with gold-standard measures of DLW for EE and DXA for ES during a 14-day baseline period; 2) We will estimate EI using the intake-balance method during the 14-day baseline period; 3) We will calibrate daily Fitbit_EE and Fitbit_ES from consumer devices using a Bayesian semi-parametric measurement error modeling approach to estimate energy balance; 4) We will reassess our validation and calibration models of consumer devices during a 14-day post-study assessment period to evaluate changes associated with growth and development with gold-standard measures of DLW for EE and DXA for ES.

Aims of the proposed study are to:

Specific Aim 1. Validate and calibrate consumer devices to estimate energy balance using gold-standard methods and a Bayesian semi-parametric approach. Hypothesis 1: We will be able to jointly model measurement error for both EE and ES to create a calibration model that reduces bias and improves accuracy of consumer devices of EE and ES.

Specific Aim 2. Estimate energy intake using the intake-balance technique using consumer monitors. Hypothesis 2:We will use calibrated EE and ES from consumer monitors to estimate EI using the intake-balance technique, with values being superior to self-reported EI.

Enrollment: 24 patients

Sex: All

Ages: 8 to 90 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Healthy children and adults, aged 8-90.
• Able to be physically active.

Exclusion criteria

• History of restrained eating, eating disorders, bariatric surgery, or other significant medical diagnosis that could impact metabolism.
• Participants taking thyroid medications, beta blockers, or other stimulants (medications are known to affect metabolism).

Trial design