Evidence map›Paper›PMID 33213423›Full record

ArticleBMC public health2020

Beyond the supermarket: analyzing household shopping trip patterns that include food at home and away from home retailers.

Jackie Yenerall, Wen You, Jennie Hill

Abstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jackie YenerallDepartment of Agricultural and Resource Economics, University of Tennessee, 2621 Morgan Circle, Knoxville, TN, 27996, USA. jyeneral@utk.edu.ORCID http://orcid.org/0000-0002-9428-5312
Wen YouDepartment of Public Health Sciences, University of Virginia, 200 Jeanette Lancaster Way, Charlottesville, VA, 22903, USA.
Jennie HillDepartment of Epidemiology, University of Nebraska Medical Center, 984395 Nebraska Medical Center, Omaha, NE, 68198, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundModifying a household's food environment by targeting a single retailer type, like supermarkets, has a limited impact on dietary outcomes. This may be because the food environment has a limited impact on shopping behaviors, or because households are not as reliant on supermarkets as we assume. However, our understanding of how households shop for food, especially when considering the use of both food at home (FAH) retailers, such as supermarkets, and away from home retailers (FAFH), such as restaurants, is limited. Thus, understanding how households shop for food is a necessary first step when developing programs to modify food purchasing behavior.

methodsK-means cluster analysis was used to identify weekly food shopping trip patterns based on the percentage of trips to FAH and FAFH retailers in the 2013 Food Acquisition and Purchase Survey (FoodAPS) dataset (n = 4665 households). Multinomial logistic regression was used to examine the relationship between shopping trip patterns, household and food environment characteristics.

resultsThree patterns emerged: primarily supermarket, primarily supercenter, or mix (i.e. no dominant retailer type, but high FAFH use). Households with incomes below 185% of the federal poverty line were evenly divided between patterns that rely primarily on FAH retailers, and the mix pattern. While nearly 70% of households with incomes above 185% of the federal poverty line are in the mix cluster. Supermarket and superstore availability significantly influenced the likelihood of belonging to those clusters respectively, while having a child, higher income, and attitudes towards healthy meal preparation time or taste significantly influenced the likelihood of belonging to the mix cluster.

conclusionAlthough lower-income households are more likely to rely primarily on FAH retailers, household's, regardless of income, that primarily utilize FAH retailers show a strong preference for either superstores or supermarkets suggesting a need for interventions to reach both retailer types. However, altering the food environment alone may not be sufficient to discourage use of FAFH retailers as households relying on FAFH retailers are significantly influenced by meal preparation time and healthy food taste.

Indexed as

Food MarketsFood SupplyChildCommerceFamily CharacteristicsHumansIncomeRestaurantsFood environmentFood shopping behaviorShopping trip patterns

Identifiers

PMID33213423
PMCPMC7678129

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.