Disclaimer: The purpose of the Open Case Studies project is to demonstrate the use of various data science methods, tools, and software in the context of messy, real-world data. A given case study does not cover all aspects of the research process, is not claiming to be the most appropriate way to analyze a given dataset, and should not be used in the context of making policy decisions without external consultation from scientific experts.

This work is licensed under the Creative Commons Attribution-NonCommercial 3.0 (CC BY-NC 3.0) United States License.

To cite this case study please use:

Wright, Carrie and Meng, Qier and Jager, Leah and Taub, Margaret and Hicks, Stephanie. (2020). https://github.com/opencasestudies/ocs-bp-rural-and-urban-obesity. Exploring global patterns of obesity across rural and urban regions (Version v1.0.0).

To access the GitHub Repository for this case study see here: https://github.com/opencasestudies/ocs-bp-rural-and-urban-obesity.

You may also access and download the data using our OCSdata package. To learn more about this package including examples, see this link. Here is how you would install this package:

install.packages("OCSdata")

This case study is part of a series of public health case studies for the Bloomberg American Health Initiative.

The total reading time for this case study is calculated via koRpus and shown below:

Reading Time Method
72 minutes koRpus

Readability Score:

A readability index estimates the reading difficulty level of a particular text. Flesch-Kincaid, FORCAST, and SMOG are three common readability indices that were calculated for this case study via koRpus. These indices provide an estimation of the minimum reading level required to comprehend this case study by grade and age.

Text language: en
index grade age
Flesch-Kincaid 9 14
FORCAST 10 15
SMOG 11 16

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Motivation

Body mass index (BMI) is often used as a proxy for adiposity (the condition of having excess body fat) and is measured as an individual’s weight in kilograms (kg) or pounds (lbs) divided by the individual’s height in meters (\(m^2\)) squared.

There are different categories of weight defined using different BMI thresholds as defined by the World Health Organization (WHO), the Centers for Disease Control and Prevention, and the National Institutes of Health. For example, these are the categories defined by the WHO:

[source]

The following chart can help you identify your estimate of BMI: