Vonthron Simon, Charreire Hélène, Perignon Marlène, Rollet Pascaline, Recchia Daisy, Mejean Caroline, Soulard Christophe-Toussaint, Perrin Coline
INNOVATION, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France.
MoISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, France.
PLoS One. 2025 Aug 1;20(8):e0329442. doi: 10.1371/journal.pone.0329442. eCollection 2025.
The food environment's impact on food behaviors is widely recognized, yet there is no consensus on how to measure individual exposure, potentially leading to inconsistent results. This study aimed to assess how the relationship between food environment exposure and household characteristics differs based on whether exposure is measured solely via buffers around the home or extended to cover activity spaces. Data from the Mont'Panier cross-sectional study, comprising 699 households in Montpellier city-region, France, were analyzed. We used multivariate multinomial regression models and multiple logistic regression models to explore the associations between household characteristics and five indicators of households' food environment exposure: number of food stores, number of restaurants, diversity of food stores, relative density of stores selling fruits and vegetables, and relative density of fast-food restaurants. Exposure was measured using two methods: (i) 500m network-buffers around household's home; and (ii) activity spaces delimited using the daily path area method. Our findings confirm that social disparities in food environment exposure can vary based on the defined exposure area. Variables such as 'employment status' and 'education', not associated with indicators of food environment exposure around the home, show associations in the activity space. Conversely, 'age' and 'car ownership' are associated with various indicators of food environment exposure around the home but not in the activity space. Additionally, our analysis reveals that the abundance and diversity of food outlets tend to decrease as household's distance from the city center increases. Combining measures of food exposure (residential area, activity space) presents a promising approach to understanding food environment dynamics. Future research should investigate whether and how the choice of exposure measures affects food behaviors relative to households' socioeconomic characteristics. Lastly, we propose two avenues for reflection concerning public policy.
食物环境对食物行为的影响已得到广泛认可，但在如何衡量个体暴露方面尚未达成共识，这可能导致结果不一致。本研究旨在评估根据食物环境暴露是仅通过家庭周边缓冲区域来衡量还是扩展至覆盖活动空间，食物环境暴露与家庭特征之间的关系会有何不同。对来自法国蒙彼利埃市地区的699户家庭的蒙特帕尼尔横断面研究数据进行了分析。我们使用多元多项回归模型和多元逻辑回归模型，探讨家庭特征与家庭食物环境暴露的五个指标之间的关联：食品店数量、餐馆数量、食品店多样性、蔬菜水果销售店的相对密度以及快餐店的相对密度。暴露采用两种方法进行衡量：(i) 家庭住所周围500米的网络缓冲区；(ii) 使用日常路径面积法划定的活动空间。我们的研究结果证实，食物环境暴露方面的社会差异可能因定义的暴露区域而异。诸如“就业状况”和“教育程度”等变量，在家居周边食物环境暴露指标中并无关联，但在活动空间中显示出相关性。相反，“年龄”和“汽车拥有情况”与家居周边食物环境暴露的各项指标相关，但在活动空间中并非如此。此外，我们的分析表明，随着家庭与市中心距离的增加，食品店铺的数量和多样性往往会减少。结合食物暴露的衡量指标（居住区、活动空间），是理解食物环境动态的一种有前景的方法。未来的研究应调查暴露衡量指标的选择是否以及如何影响与家庭社会经济特征相关的食物行为。最后，我们提出了两条关于公共政策的思考途径。
