Year-Over-Year Body Mass Index Change Data

This dataset compiles the largest collection of year-over-year Body Mass Index (BMI) changes for analysis. It was created by John C. Lang to study the statistical mechanics of human weight change, including drift and diffusion dynamics. The data supports a stochastic mathematical model investigating BMI distribution shape and potential social influence effects.

Use Cases

• Analyze year-over-year BMI changes to model deterministic drift towards a natural set point.
• Study the magnitude of BMI fluctuations, which are linearly proportional to BMI, to understand diffusion from random lifestyle factors.
• Investigate the right-skewed broadening of BMI distributions over time using compiled longitudinal data.
• Test the hypothesis of peer-to-peer social influence on BMI dynamics by examining correlations among individuals with similar BMI.

Strengths

• Compiles the largest data set of year-over-year BMI changes available at the time of publication.
• Data is used to derive a theoretical shape for the BMI distribution based on a stochastic model.
• Supports analysis of both deterministic drift and random diffusion components in weight dynamics.

Limitations

• The specific sample size, number of rows, and column structure are not provided.
• Geographic and demographic coverage of the compiled data is unspecified.
• Data freshness is limited as the last update was in June 2020.

Provenance

Source

John C. Lang

Collection Method

Compiled from unspecified sources to create the largest dataset of year-over-year BMI changes.

Time Range

Temporal coverage spans at least 35 years prior to 2020, based on the description's context.

Freshness

Last updated 2020-06-24.