Evidence map›Paper›PMID 39696158›Full record

ArticleBMC public health2024

Measuring associations between the food environment and dietary habits: comparing the proportion and density of food outlets.

Kamille Almer Bernsdorf, Henrik Bøggild, Mette Aadahl, Ulla Toft

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Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Kamille Almer BernsdorfCenter for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark. kamille.almer.bernsdorf.torp@regionh.dk.
Henrik BøggildPublic Health and Epidemiology, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
Mette AadahlCenter for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.
Ulla ToftCenter for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark.

Funding

The Danish Heart Association 16-R107-A6607-22027
6 · The paper itself

Abstract

backgroundThe food environment plays a crucial role in shaping our dietary choices and overall health. Spatial measures provide distinct perspectives on the physical food environment and its impact on diet. While proportion measures are theoretically considered to provide a more accurate representation of the overall physical food environment than density measures, it is important to recognize that the association between food environments and diet can vary depending on the context. Therefore, relying solely on one measure may not be appropriate.

methodsWe systematically assessed the density and proportion of multiple food outlet types (fast-food outlets, convenience stores, supermarkets, and restaurants) around individuals homes using a large cross-sectional Danish study (N = 71,840). Densities were modeled in separate multilevel linear regression models, incorporating random intercepts from linear splines for each of the four food outlet types. Proportions were modeled without splines. Through the association with a dietary quality score (DQS), we examined the impact of quantifying the foodscape from density versus proportion measures. Associations were compared using parameter estimates, p-values, Akaike Information Criterion (AIC) values, and Akaike weights.

resultsAIC values and Akaike weights were in favor of models including density measures. Across all outlet types, density measures were consistently negatively associated with the DQS until reaching densities of 3-5 (count/km2), at which point the direction of association became positive, indicating a shift towards a healthier DQS. After correcting for multiple comparisons, the most significant effect was observed for the sole significant proportion measure. A 10% increase in the proportion of fast-food outlets among "eating out options" was associated with a 7% decrease in the DQS, towards poorer dietary quality.

conclusionsThe associations highlight that choosing food outlet density versus proportions to quantify the foodscape impact findings of substantial importance when considering the significance level and direction of association. Findings suggests a threshold effect when using density measures indicating abundance of many food outlets, at which the association with dietary quality alters significantly towards healthier diet quality.

Indexed as

Fast FoodsFeeding BehaviorFood MarketsFood SupplyRestaurantsAdultCross-Sectional StudiesDenmarkFemaleHumansMaleMiddle AgedResidence CharacteristicsBuilt environmentCommunity food environmentDietary patternsGeographic Information SystemsRetail food environment

Identifiers

PMID39696158
PMCPMC11654021

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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.