Determining Household Obesity Status Using Scanner Data

Elina T. Page

Sabrina K. Young

Megan Sweitzer

Abigail Okrent

Economic Research Service

November 2, 2021

2021 FCSM Research and Policy Conference

The findings and conclusions in this presentation are those of the authors and should not be construed to represent any official USDA or U.S. Government determination or policy. The analysis, findings, and conclusions expressed in this presentation should also not be attributed to IRI.

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Diet is the Primary Contributor to Poor Health in the US

Source: US Burden of Disease Collaborators. The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States. JAMA 2018.

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Obesity in the United States

Current rate of obesity: 	40% of adults

		21% of youth

Obesity linked to increased risk of morbidity and mortality.

Economic burden of disease: $1.7 trillion

	$480.7 billion in direct expenditures 

	$1.24 trillion in lost productivity

Sources: 	Ogden et al. (2020)

	Waters and Graf (2018)

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Scanner Data

Household Scanner Data: 

	IRI Consumer Network

Itemized food purchase data for 120,000 households

Household demographics and survey weights

IRI Medprofiler

Opt-in survey on health and medical conditions

Includes self-reported height and weight

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Issue and Research Objective

Issue:

	Medprofiler height and weight are self-reported and may be biased.

Objective:

	Validate Medprofiler BMI distributions by comparing to 

self-reported and measured BMI distributions from NHANES 

and test methods of adjustment.

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Methods of Adjustment

Remove outliers: 

based on interquartile range  

based on range of values reported in NHANES

Correct misreporting using self-reported and measured BMI in NHANES and percentile ranking regressions. 

Percentile rank self-reported NHANES BMI

Regress measured weight on cubic splines of the percentile ranks

Apply estimated coefficients to self-reported Medprofiler BMI

Source: Courtemanche et al. (2015)

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|                              | Ages 20+ |             |
|------------------------------|----------|-------------|
|                              | NHANES   | MedProfiler |
| Sample size                  | 20,409   | 320,682     |
| Hispanic (%)                 | 14       | 13          |
| Non-Hispanic White (%)       | 66       | 70          |
| Non-Hispanic Black (%)       | 11       | 11          |
| Non-Hispanic Asian (%)       | 06       | 04          |
| Other (%)                    | 03       | 02          |
| Male (%)                     | 49       | 45          |
| Actual measurements          |          |             |
| Mean BMI (kg/m2)             | 29.23    | --          |
| Proportion underweight (%)   | 02       | --          |
| Proportion normal weight (%) | 27       | --          |
| Proportion overweight (%)    | 32       | --          |
| Proportion obese (%)         | 39       | --          |
| Self-reported measurements   |          |             |
| Mean BMI (kg/m2)             | 28.49    | 28.86       |
| Proportion underweight (%)   | 02       | 02          |
| Proportion normal weight (%) | 31       | 30          |
| Proportion overweight (%)    | 34       | 33          |
| Proportion obese (%)         | 34       | 35          |

Composition of NHANES and IRI MedProfiler Samples

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Self-Reported (MedProfiler) and Measured (NHANES) BMI for Adults (20+)

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Results: A Comparison of Methods

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Adult (Age 20+)

|                                              | Mean BMI (kg/m2) | Underweight (%) | Normal weight (%) | Overweight (%) | Obese (%) |
|----------------------------------------------|------------------|-----------------|-------------------|----------------|-----------|
| NHANES (Measured)                            | 29.23            | 02              | 27                | 32             | 39        |
| NHANES (Self-Reported)                       | 28.49            | 02              | 31                | 34             | 34        |
| MedProfiler (Unadjusted)                     | 28.86            | 02              | 30                | 33             | 35        |
| MedProfiler (NHANES Outliers Excluded)       | 28.81            | 02              | 30                | 33             | 35        |
| MedProfiler (IQR Outliers Excluded)          | 28.18            | 02              | 31                | 34             | 33        |
| MedProfiler (Percentile Ranking Regressions) | 29.26            | 01              | 28                | 32             | 39        |

Results: A Comparison of Methods

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Predicted BMI Using Percentile Ranking Regressions:Hispanic Adults

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Predicted BMI Using Percentile Ranking Regressions:Non-Hispanic White Adults

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Predicted BMI Using Percentile Ranking Regressions:Non-Hispanic Black Adults

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Predicted BMI Using Percentile Ranking Regressions:Non-Hispanic Asian Adults

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Next Steps

Finalize guidance for researchers:

For adjusting BMI.

For defining household obesity.

Analyze household food purchases by household obesity status.

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Thank you!

elina.t.page@usda.gov

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