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Researchers Adjust Self-Reported Estimates of Obesity in Scanner Data

Author

Listed:
  • Okrent, Abigail
  • Sweitzer, Megan
  • Young, Sabrina
  • Page, Elina T.

Abstract

The prevalence and incidence of obesity continue to rise in the United States, with less healthy diets being a primary contributing factor. Monitoring how U.S. obesity evolves over time and across socioeconomic groups with shifting dietary patterns helps inform policies to mitigate increases in obesity. The body mass index (BMI), constructed using the relationship between height and weight, is a commonly used measurement of adult obesity. BMI is defined as a person’s weight in kilograms divided by height in meters squared (kg/m2). A BMI of more than 30 kg/m2 indicates obesity, a BMI of less than 18.5 signals underweight status, and a BMI from 25.0 to 29.9 means a person qualifies as overweight. Anyone with a BMI between the underweight and overweight BMIs falls in the healthy weight status. However, self-reported height and weight often are misreported in surveys; individuals tend to overreport their height and underreport their weight, resulting in a lower BMI than if it were based on measured height and weight. Most surveys rely on self-reported height and weight data because of the cost and burden of collecting measurements from respondents, but the National Health and Nutrition Examination Survey (NHANES) measures both. Comparing self-reported and measured heights and weights from NHANES is useful to understand measurement error in self-reported data.

Suggested Citation

  • Okrent, Abigail & Sweitzer, Megan & Young, Sabrina & Page, Elina T., 2023. "Researchers Adjust Self-Reported Estimates of Obesity in Scanner Data," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, vol. 2023, November.
  • Handle: RePEc:ags:uersaw:338939
    DOI: 10.22004/ag.econ.338939
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