definition of obesity

Electronic health records provide a unique source of data to monitor obesity rates. Our estimates use data from the electronic health records of over 1.8 million patients who had a body mass index (BMI) recorded during an outpatient visit. BMI is calculated by dividing a person’s weight in kilograms by the square of their height in meters.

BMI is equal to weight in kilograms divided by the square of height in meters.

BMI is easy to calculate and uses measurements that are easy to take during a doctor visit. While it is not a perfect measurement of body fat, research shows that BMI is related to some negative health outcomes and other measures of body fat that are harder and more expensive to make.1

As a condition, obesity is defined based on BMI. This definition is different for adults and children.

Adults: For adults ages 18 and over, we define obesity as having a BMI of 30 or above. For example, a six-foot-tall adult has obesity if they weigh 220 pounds or more, and a five-and-a-half-foot-tall adult has obesity if they weigh 185 pounds or more. To calculate BMI for an adult, click here to visit the CDC's Adult BMI Calculator.

Children: For children ages two and over, obesity is determined by comparing a child’s BMI to what we would expect for their age and sex. We use the CDC’s BMI-for-age growth chart to determine what BMI we would expect. Children who are at or above the 95th BMI percentile are considered to have obesity. To calculate BMI for a child or teen, click here to visit the CDC's Child and Teen BMI Percentile Calculator.

Calculating Obesity Rates

Throughout this website, we talk about obesity rates. An obesity rate is the percentage of people in a population who have obesity.

Obesity rate is equal to the number of patients with obesity divided by the number of patients with a recorded BMI.

Our estimates reflect unadjusted obesity rates among patients that had an outpatient visit with a participating healthcare system in 2015 or 2016.

We do not include overweight in these estimates. We also do not include pregnant women.

Data Acquisition and Processing

The Wisconsin Health Atlas obesity rate estimates use data on body mass index (BMI), age, sex, billing ZIP Code, and payer from individuals who visited a participating health care system in 2015 and 2016. BMI is recorded in health systems’ electronic health records as part of routine care. Health care systems securely transfer de-identified data to the Health Innovation Program (HIP), where the data are combined and stored on a secure server. Obesity Prevention Initiative staff prepare and aggregate data to create ZIP Code level estimates of obesity prevalence. These aggregated estimates are then removed from the HIP secure server for use on the Wisconsin Health Atlas website.

Data Quality

Participating health care systems review data for quality assurance before it is submitted to HIP for inclusion in the Wisconsin Health Atlas obesity rate estimates. Obesity Prevention Initiative (OPI) staff further review submitted data for compatibility across systems. One record per patient from each health care system is used to create the prevalence estimates.


Body Mass Index (BMI): Equal to weight in kilograms divided by height in meters squared.

Obesity: Obesity is defined differently for adults and children. For adults (ages 18 and over), obesity is defined as having a Body Mass Index of 30 or higher. For children (ages 5 to 17), obesity is defined based on the 2000 CDC Growth Charts. A child is considered to have obesity if their BMI is at or above the 95th percentile for their age in months and sex. For more information about obesity definitions, visit:

Numerator: The total number of individuals with a valid BMI value that classifies them as having obesity, for a given geographic location (ZIP Code or statewide), age group, and (if applicable), sex.

Denominator: The total number of individuals with a valid BMI value for a given geographic location (ZIP Code or statewide), age group, and (if applicable), sex.

Coverage: Estimates the percentage of a population that is included in the available, valid patient data. Coverage is calculated by dividing the total number of patients in a ZIP Code by the estimated population size of the ZIP Code. ZIP Code population sizes are approximated using the 2015 American Community Survey (ACS) 5-year population estimates for ZIP Code Tabulation Areas. Coverage is calculated separately for adults and children for each ZIP Code. For more information on the American Community Survey, visit:

Insufficient Data: ZIP Code estimates are not published when there is not enough data available to create an estimate. This helps us ensure patient anonymity and estimate stability. Insufficient data is defined in five ways:

  1. Coverage less than 10%: The number of included individuals is less than 10% of the ACS estimated population size for the age group, sex, and ZIP Code.
  2. Numerator less than 10: Estimates based on a numerator of less than 10 individuals.
  3. Denominator less than 30: Estimates based on a denominator of less than 30 individuals.
  4. Population size less than 30: The ACS estimated population size for the age group, sex and ZIP Code is less than 30 individuals.
  5. Relative Standard Error (RSE) greater than 30%: The standard error of the prevalence estimate is equal to or greater than 30% of the prevalence estimate.

Confidence Interval: 95% Wilson (score) confidence intervals are calculated for each prevalence estimate.

Unadjusted Obesity Prevalence Estimates: Gives the approximate percent of the population in the ZIP Code, age, and sex group with obesity.


These prevalence estimates are based on patient populations and reflect those who sought care from participating health care systems during 2015 and 2016. Only individuals who received care during the submitted period were included in these data, and estimates may not accurately reflect the prevalence of obesity in the Wisconsin population.

BMI values are based on heights and weights recorded during patient encounters. There are no standard practices for height and weight measurement across health systems and clinics. Some variation may occur in height and weight measurements based on the clothing and/or shoes that a patient wore during their height and weight measurement.

While estimates include only one visit per patient per health care system, it is possible that patients sought care from more than one reporting system. Such visits would be included as duplicate measurements.

Not all health care organizations that provide care to Wisconsin residents currently participate in this project. This results in limited or missing data for some ZIP Codes.

The geographies used to define coverage for ZIP Codes do not perfectly coincide. The ZIP Code Tabulation Area (ZCTA) boundaries are defined by the U.S. Census Bureau and are composed for Census blocks in which a majority of residents fall into a certain ZIP Code. For more information, see:


Because of limitations in the available data, unadjusted obesity prevalence estimates presented by the Wisconsin Health Atlas may not be representative of the true obesity prevalence in the population.

System Notes

These data represent individuals who visited a participating health care system during the included period and had a valid BMI measurement recorded. They may not be representative of the entire population of a ZIP Code.

Valid BMI measurements are based on visits during which a valid height and weight were recorded.

All data sharing and preparation was conducted in accordance with Health Insurance Portability and Accountability Act (HIPAA) regulations to ensure privacy and confidentiality.

Data Sources

We collaborate with healthcare systems throughout the state as part of the Wisconsin Obesity Surveillance Partnership. Currently contributing health care organizations include:

  • Aspirus
  • Ascension
  • Froedtert & The Medical College of Wisconsin
  • Gundersen Health System
  • Marshfield Clinic
  • Mayo Clinic Health System
  • Mercyhealth
  • Prevea Health
  • ProHealth Care
  • SSM Health
  • ThedaCare
  • UnityPoint Health
  • UW Health

Future contributing partners:

  • Holy Family Memorial
  • Wildwood Family Clinic

The Wisconsin Obesity Surveillance Partnership welcomes new data partners. For more information, please contact us at


Funding for this project was provided by the University of Wisconsin School of Medicine and Public Health through the Wisconsin Partnership Program.


  1. Division of Nutrition, Physical Activity, and Obesity NC for CDP and HP. Assessing Your Weight | About Adult BMI. Accessed May 3, 2018.