Who Participates in Household Scanning Panels?

Lusk, Jayson L.; Brooks, Kathleen R.

doi:10.1093/ajae/aaq123

Cited by 63 publications

(41 citation statements)

References 40 publications

(42 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the household level analysis, it has been previously reported that the Homescan sample does not perfectly match the US population based on demographics, and that males and individuals with low education are underrepresented. 33 Ideally, the sample should represent the population of US food/beverage shoppers rather than the overall US population. Without knowledge of the true US food/beverage shopper population, generalizing the results from this sample of shoppers should be made with caution.…”

Section: Discussionmentioning

confidence: 99%

“…Without knowledge of the true US food/beverage shopper population, generalizing the results from this sample of shoppers should be made with caution. Finally, given that households volunteered to participate, there is always the possibility of participation bias; 33 therefore, when possible, it is important to compare the results of Homescan with other dietary surveys (e.g., NHANES).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Monitoring Changes in the Nutritional Content of Ready-To-Eat Grain-Based Dessert Products Manufactured and Purchased between 2005 and 2012

Mathias¹,

Ng²,

Popkin³

2015

Journal of the Academy of Nutrition and Dietetics

View full text Add to dashboard Cite

Background Monitoring changes in the nutritional content of food/beverage products and shifts in consumer purchasing behaviors is needed to measure the effectiveness of efforts by both food manufacturers and policy makers to improve dietary quality in the United States. Objective Examine changes in the nutritional content (e.g., energy, saturated fat, and sugar density) of Ready-To-Eat (RTE) Grain-Based Dessert (GBD) products manufactured and purchased between 2005 and 2012. Design Nutrition facts panel information from commercial databases was linked to RTE GBD products purchased by households (n=134,128) in the Nielsen Homescan longitudinal dataset 2005–2012. Statistical Analysis Linear regression models were utilized to examine changes in the energy, saturated fat, and sugar density of RTE GBD products manufactured in each year between 2005 and 2012. Random effects models controlling for demographics, household composition/size, and geographic location were utilized to examine changes in household purchases of RTE GBD products (grams) and the average energy, saturated fat, and sugar density of RTE GBD products purchased. Results The saturated fat density (g/100 g) of RTE GBD products increased significantly from 6.5 ± 0.2 in 2005 to 7.3 ± 0.2 and 7.9 ± 0.2 for pre-existing and newly introduced products in 2012, respectively. Between 2005 and 2012, the energy density (kcal/100 g) of RTE GBD products purchased decreased significantly from 433 ± 0.2 to 422 ± 0.2, the saturated fat density (g/100 g) of products purchased increased significantly from 6.3 ± 0.01 to 6.6 ± 0.01, the sugar density (g/100 g) of products purchased decreased significantly from 32.4 ± 0.03 to 31.3 ± 0.02, and household purchases of RTE GBD products (grams) decreased by 24.1 ± 0.4%. Conclusions These results highlight an opportunity for both food manufacturers and public health officials to develop new strategies to shift consumer purchases towards products with lower energy, saturated fat, and sugar densities in addition to decreasing overall purchases of RTE GBDs.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Monitoring Changes in the Nutritional Content of Ready-To-Eat Grain-Based Dessert Products Manufactured and Purchased between 2005 and 2012

Mathias¹,

Ng²,

Popkin³

2015

Journal of the Academy of Nutrition and Dietetics

View full text Add to dashboard Cite

show abstract

“…Findings from our sample may not be generalizable to the US population because of potential selection bias or nonresponse related to participant burden (37). Because our sample of relatively high-income households is not nationally representative and the distribution of income across racial/ethnic groups does not match that of the US population, all models were adjusted for income; results were interpreted with caution as associations between purchases and race/ethnicity independent of income, which potentially might reflect differences in food preferences, time constraints, or cultural traditions.…”

Section: Figurementioning

confidence: 94%

“…This analysis used data from the 2000-2012 Nielsen Homescan Panel, a nationwide study of CPG food and beverage purchases by US households (35)(36)(37)(38). Household members are given barcode scanners and are instructed to scan the barcodes on all foods and beverages purchased from grocery, drug, mass-merchandise, supercenter, and convenience stores and supermarkets.…”

Section: Study Populationmentioning

confidence: 99%

Highly Processed and Ready-to-Eat Packaged Food and Beverage Purchases Differ by Race/Ethnicity among US Households

Poti

Mendez

2016

The Journal of Nutrition

View full text Add to dashboard Cite

show abstract

“…A fascinating paper by Lusk and Brooks (2011) suggests that households in two large US scanner samples, Homescan and IRI, appear to be more price responsive than the population at large. They take random samples from the scanner surveys and from a random-digit-dialing survey of all households, and use webbased questionnaires to elicit a series of discrete choices over grocery products from which elasticity estimates are derived.…”

Section: Previous Researchmentioning

confidence: 99%

How might in-home scanner technology be used in budget surveys?

Leicester¹

2012

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. We find that levels of spending are significantly lower in scanner data. A large part (but not all) of the gap is explained by weeks in which no spending at all is recorded in scanner data. Demographic differences between the surveys accentuate rather than close the gap. We also demonstrate that patterns of expenditure across the surveys are much more similar, as are Engel curves relating food commodity budget shares to total food expenditures. A key finding is that the period over which we observe households in the scanner data significantly alters the distribution, but not the average, of weekly food expenditures and budget shares, which has important implications for whether two-week spending diaries common to budget surveys are giving a truly accurate reflection of a household's typical spending patterns. A second, more involved use of scanner data would be to impute detailed commodity-level expenditure patterns given only information on total expenditures, as a way of reducing respondent burden in budget surveys. We find that observable demographics in the scanner data explain little of the variation in store-specific expenditure patterns, and so caution against relying too heavily on imputation. Terms of use: Documents inJEL Classifications: C81, C83, D12

show abstract

Who Participates in Household Scanning Panels?

Cited by 63 publications

References 40 publications

Monitoring Changes in the Nutritional Content of Ready-To-Eat Grain-Based Dessert Products Manufactured and Purchased between 2005 and 2012

Monitoring Changes in the Nutritional Content of Ready-To-Eat Grain-Based Dessert Products Manufactured and Purchased between 2005 and 2012

Highly Processed and Ready-to-Eat Packaged Food and Beverage Purchases Differ by Race/Ethnicity among US Households

How might in-home scanner technology be used in budget surveys?

Contact Info

Product

Resources

About