Influence of Socioeconomic Status on the Retail Food Environment in Alicante
by
, , ,
Iván Hernández-Caravaca
1
Alba Martínez-García
1,2,3,*
Eva María Trescastro-López
2,3,4,5
Ángel Plaza-Gavaldón
1,
Julio Martí-Cremades
1 and
Joaquín Moncho
11
Department of Community Nursing, Preventive Medicine and Public Health and History of Science, University of Alicante, 03690 Alicante, Spain
2
Balmis Research Group in History of Science, Health Care and Food, University of Alicante, 03690 Alicante, Spain
3
Research Group on Applied Dietetics, Nutrition and Body Composition, University of Alicante, 03690 Alicante, Spain
4
Department of Nursing, University of Alicante, 03690 Alicante, Spain
5
Alicante Institute for Health and Biomedical Research (ISABIAL), Group 23, 03550 Alicante, Spain
*
Author to whom correspondence should be addressed.
Nutrients 2024, 16(23), 4127; https://doi.org/10.3390/nu16234127
Submission received: 14 November 2024
/
Revised: 23 November 2024
/
Accepted: 27 November 2024
/
Published: 28 November 2024
(This article belongs to the Section Nutritional Policies and Education for Health Promotion)
Abstract
:Background/Objectives: Unhealthy dietary habits are associated with chronic non-communicable diseases and may contribute to increased mortality in all countries of the world. Food environments determine the accessibility, availability, and promotion of food, thus playing an important role in people’s diets, but they are context-dependent. The aim of this study was to evaluate the availability and accessibility of food in food outlets in different neighborhoods of the city of Alicante. Methods: Cross-sectional study. Trained researchers conducted food store audits using the validated Nutrition Environment Measures Survey in Stores for Mediterranean contexts (NEMS-S-MED) tool. Data were collected from food stores within a socioeconomically diverse sample in Alicante (n = 63). We compared the availability and affordability of “healthier–less healthy” food pairs, scores between food store types (supermarkets, specialized, convenience stores, and others), and socioeconomic levels in Alicante in 2022. Results: The present study highlights that the food stores with the greatest availability and accessibility to healthy foods are supermarkets, as opposed to specialized stores and convenience stores. In addition, differences were found in the accessibility and availability of healthy foods by neighborhoods with different income levels, being more accessible in the residential neighborhood with the highest income level. Tourism could explain the differences in the food retail environment, with a high-income neighborhood showing similar results to low-income neighborhoods. Conclusions: The results obtained invite reflection on the development and adoption of policy strategies that promote the availability and accessibility of healthy food in the most disadvantaged areas.
1. Introduction
Obesity and chronic non-communicable diseases (NCDs) have doubled both globally and in Spain in recent years [1,2,3]. This increase is concerning, as they are one of the leading causes of death in the world and represent genuine public health problems [4].
Unhealthy dietary habits are associated with these chronic pathologies and may contribute to increased mortality in all countries of the world [5]. For this reason, and due to the complexity of dietary behaviors and the wide range of influences that may be present in the diet of the population, improving diet requires the active collaboration of different elements involved in the food system [5].
The food environment determines the accessibility, availability, and promotion of food, thus playing an important role in people’s diets [6]. It can therefore influence a population’s food choices and encompass both foods consumed at home and foods obtained outside the home, including vending machines, takeaways, cafeterias, restaurants, supermarkets, and food stores [7]. There is also evidence of socioeconomic inequalities in access to food depending on the characteristics of the environment [8,9]. Hence, understanding food environments and how they differ between neighborhoods of different socioeconomic statuses can be a key part of tackling obesity and NCDs such as cancer, diabetes, or hypercholesterolemia.
Previous research has assessed the relationship between the consumer food environment and the health status of the population [9,10,11,12], but it is context-dependent, and therefore, more studies are needed to determine how this environment influences each country and/or city [12,13]. Nonetheless, there is little information on the characteristics of the retail food environment in different southern European countries and, more specifically, in those with a Mediterranean context. Particularly, there are no studies assessing the food environment of cities in the Valencian Community (Spain), which is characterized by its Mediterranean setting.
For this reason, in order to extend the existing evidence and to fill the gap in the knowledge of the retail food environment of Mediterranean cities, the aim of this study was to evaluate the availability and accessibility of food in food outlets in different neighborhoods of the city of Alicante, taking into account the income level of the population and the types of food stores.
2. Materials and Methods
2.1. Study Design and Sample
This is a cross-sectional descriptive observational study carried out in Alicante, a city on the Mediterranean coast of south-eastern Spain. According to the sources of the Spanish National Institute of Statistics (INE), Alicante is classified into 8 districts with different income levels [14].
In consideration of the mean income per capita and the mean household income, as reported by the National Institute of Statistics [14], four districts of Alicante exhibiting disparate income levels were selected. Of the selected districts, the lowest income brackets were identified in Districts 3 and 5, while Districts 1 and 4 exhibited the highest income levels. District 3 reported an average income per person of EUR 9803 and an average income per household of EUR 25,457; District 5 reported an average income per person of EUR 8655 and an average income per household of EUR 23,621. In contrast, District 1 exhibited an average income per person of EUR 1785 and an average income per household of EUR 38,709; District 4 had an average income per person of EUR 12,788 and an average income per household of EUR 34,235.
A neighborhood was selected within each district, with the objective of obtaining the most representative sample of the sociodemographic profile of the population. The selected neighborhoods were “Carolinas Altas” (District 3), “Virgen del Carmen” (District 5), “Centro” (District 1), and “Vistahermosa” (District 4).
2.2. Data Collection
Data collection was carried out in all food outlets in each neighborhood during business hours and on weekdays during the month of April 2022. The data were collected by two trained raters according to a protocol established for the completion of the survey. The following sales outlets were included: greengrocers, bakeries, butchers, and fishmongers, among others, or mixed sales outlets, such as convenience stores, hypermarkets, or supermarkets. Food markets and food galleries were excluded because standard tools for measuring healthy foods may not capture the effect of these retailers, following the procedure of previous studies [12,15].
The NEMS-S-MED survey [16] was used using mobile devices and the Google Forms platform. This survey, validated for Spain, assesses the availability and price of twelve food groups: fresh fruit, vegetables, nuts, beverages, bread, cereals and pastries, milk and dairy products, eggs, oil and butter, rice, pulses, and meat and fish [16].
2.3. Measures
The established NEMS-S-MED score [16] was used to analyze and evaluate the food establishments in the different districts. This score ranges from 0 to 49 points and takes into account both the availability of different food groups (0–37 points) and the price of food (0–12 points). The higher the score, the greater the availability and accessibility of healthy options in the establishment. The score was calculated for each food outlet in order to study differences by type of food store and neighborhood.
2.4. Data Analysis
A descriptive analysis was carried out by calculating means and standard deviations for quantitative variables (food prices) and frequencies and percentages for qualitative variables (food availability and healthy and less healthy food) by type of establishment and neighborhood.
For analysis, food stores were classified into supermarkets (including discounters), convenience stores (including gas stations), and traditional/specialized establishments (greengrocers, butchers, fishmongers, and bakers), based on previous research [12,16,17].
In order to study the differences in the availability of the different foods included in this study according to the type of establishment and neighborhood, the Chi-square test or Fisher’s exact test was used. Furthermore, for the analysis, foods were categorized according to their content (higher or lower) of fat, sugar, and salt (FSS). The McNemar test and the Wilcoxon rank test for paired samples were used to compare the availability of foods with higher or lower FSS content, as well as the price of these foods in the different establishments, respectively. The Kruskal–Wallis test was used to compare food prices by neighborhood. Finally, linear mixed models were fitted with the dependent variable NEMS-S-MED total score and availability score in each case and fixed effects: neighborhood and type of establishment. In both models, the possible interaction effect between the independent variables was tested. Values were considered significantly different when p < 0.05.
3. Results
3.1. Descriptive Data
Data were collected from 63 food stores. Of these, almost half of them were (49.3%, n = 31) specialized stores (butchers: 15.9%; bakeries: 15.9%; greengrocers 15.9%; and herbalists: 1.6%), followed by supermarkets (25.4%, n = 16) and convenience stores (25.4%, n = 16). The types of food stores by neighborhood and economic level are summarized in Table 1. No statistically significant differences were identified with regard to the types of food stores in each neighborhood (p = 0.545) or socioeconomic level (p = 0.140).
3.2. Food Availability and Price
Table 2 shows the availability of foods collected in the NEMS-S-MED survey by type of food store and by neighborhood. The products that showed an overall availability of more than 70% were eggs, cola, and commercial confectionery. Less common items were fresh fish (9.5%), processed and unprocessed frozen fish (19% and 20.6%, respectively), skimmed and sugar-free yogurts (19% and 22.2%, respectively), and whole rice (22.2%). Mean availability across all food items was 84.7% in supermarkets, 34.9% in convenience stores, and 24% in specialized stores. All the items studied (n = 38) showed statistically significant differences between the type of store and their availability (p < 0.05). However, the biggest differences between supermarkets and convenience stores were found in fresh fruit, fresh and frozen vegetables and nuts (88.8% average availability in supermarkets vs 18.8% in convenience stores), skimmed milk, skimmed yogurt and cheeses in general (92.2% vs. 26.6%), fresh meats in general (68.8% vs. 0%), and finally, in both unprocessed and processed frozen fish (68.8% vs. 6.3%).
When the availability of the items studied was compared among the different neighborhoods, statistically significant differences were found in fresh fruit, 100% juice, not-100% juice, whole bread, and low-sugar cereals, as well as in both unprocessed and processed frozen fish (p < 0.05). Differences were also observed for fresh vegetables, brown rice, and unsweetened/sweetener-free yogurts, which, although not significant at the usual level, showed a value of p < 0.07. The availability of all these items was higher in neighborhoods with higher socioeconomic status in almost all cases (Table 2).
Furthermore, the food items with more FSS showed a higher availability in products like salty nuts, not-100% juice, whole milk, white rice, regular cereals, and yogurt with sugar compared with the less FSS ones (p < 0.05). On the other hand, the majority (three out of four) of the prices that showed statistically significant differences were higher in the less FSS group (100% juice, olive oil, and whole rice) (Table 3).
When the prices were compared between the different neighborhoods, statistically significant differences were found in the price of the chicken (p = 0.045), as well as a trend in the price of semi-skimmed milk, showing high-level economic neighborhoods having the highest prices. For the rest of the food items, no differences were found (p > 0.05) (Supplementary Material Table S1).
3.3. NEMS-S-MED Score
Table 4 and Figure 1 and Figure 2 illustrate the outcomes of the linear mixed models, which were fitted with the total NEMS-S-MED score and the availability score as dependent variables.
The estimated marginal means (Figure 1) showed that supermarkets presented a higher total score (mean = 28.703; 95%CI: 25.511, 31.895) and availability score (mean = 25.163; 95%CI: 22.288, 28.038), followed by specialized stores (mean total score: 8.911; 95%CI: 6.332, 11.490; mean availability score: 8.138; 95%CI: 5.815, 10.461) and finally convenience stores (mean total score: 8.088; 95%CI: 4.841, 11.334; mean availability score: 6.762; 95%CI: 3.838, 9.686). In terms of scores by neighborhood (Figure 2), the high-income residential neighborhood “Vistahermosa” has the highest total and availability scores (mean total score: 21.471; 95%CI: 17.635, 25.306; mean availability score: 18.182; 95%CI: 14.727, 21.636), followed by the other neighborhoods with similar average scores (mean total score “Centro”: 12.713; “Carolinas altas”: 13.058; and “Virgen del Carmen”: 13.694).
The results of the linear mixed models demonstrate a statistically significant impact of food store type (p < 0.01) and neighborhood (p < 0.01) on both the total and availability scores of the NEMS-S-MED. The total NEMS-S-MED score for convenience and specialized stores was approximately 20 points lower than that for supermarkets (−20.6 and −19.8, respectively, p < 0.01), while the availability score was between 18.4 and 17 points lower (p < 0.01). No significant differences were observed in the scores obtained from convenience and specialized stores. The adjusted effect for the “Vistahermosa” neighborhood (characterized by high levels of wealth) was approximately 7.8 points higher than that observed in the “Virgen del Carmen” neighborhood (characterized by low levels of wealth) and approximately 7 points higher than in the other neighborhoods (p < 0.05). The neighborhoods of “Carolinas Altas” and “Centro” presented scores similar to those of “Virgen del Carmen”.
4. Discussion
This study evaluates the food retail food environment in Alicante (Spain) as an example of a Mediterranean city in southwestern Europe.
The present study demonstrates that supermarkets are the food stores with the greatest availability and accessibility to healthy foods, in contrast to specialized stores and convenience stores. Previous research carried out in different countries (Malta, China, UK, Germany, US, and Australia), as well as in Spain, has obtained similar results [12,18,19,20,21,22,23]. This is due to the fact that supermarkets generally offer a wider range of foods than single-product stores. However, as shown in the previous section, there is also greater availability of unhealthy and ultra-processed foods. Earlier research highlights the same issue, underlining that this offer can have an opposite or detrimental effect by offering both healthy and unhealthy foods [12,24].
On the other hand, specialized stores (butchers, fishmongers, greengrocers, etc.) offer fresh and healthy food and generally do not have a wide range of unhealthy food, as they sell the products they specialize in. Despite this, they have similar scores as convenience stores and lower scores than supermarkets. Therefore, encouraging people to shop in these types of establishments could be more useful in encouraging people to eat a healthier diet. Nevertheless, this strategy may be difficult to implement, as previous national studies have found an increase in supermarket shopping to the detriment of traditional small establishments [25,26]. Similarly, research has shown that due to the food transition and the “Westernization” of Mediterranean food environments, the number of supermarkets and hypermarkets has been increasing over the last decades [17,27,28]. Furthermore, marketing strategies are more prevalent in supermarkets than in specialized food stores and are primarily designed to boost the sale of unhealthy foods [25,28], which may lead to an increase in unhealthy product consumption.
Concerning convenience stores, according to our results, they offer more unhealthy products than other establishments and were the lowest rated according to the NEMS-S-MED survey. These results are in line with studies carried out in the USA and the UK [29,30], where fewer healthy products are available in convenience stores compared with supermarkets. Similarly, previous studies in Madrid and Barcelona show a similar trend [12,31].
In terms of the availability and price of products with higher or lower FSS content, in our study, it was observed that products with a less healthy profile, such as white rice, sweetened yogurts, or sugar-containing cereals, were more readily available and offered at a lower price point than wholegrain rice, sugar-free yogurt, and cereals. A similar trend is observed in studies carried out in Madrid [12], where it was found that most healthier foods (such as 100% juice versus not-100% juice, low-sugar cereals versus regular cereals, or whole rice versus white rice) were less available than their less healthy counterparts, suggesting that households with limited financial resources face greater challenges in accessing healthy foods. Previous research [32,33] has shown that this can directly influence food purchasing decisions between different socioeconomic levels, creating an economic barrier for low-income people who tend to choose less healthy options because of the price difference. This underscores the importance of considering these access and equity issues in healthy eating when formulating food policies and strategies. In this regard, food price policies are recommended as one of the most potentially effective public health measures to promote healthy diets [34].
Apart from the aforementioned, in the present study, it was observed that in neighborhoods with a high income level, the score was higher than in those with a lower income level. A similar effect has been observed in previous research in Malta [18], the UK [19], Australia [20], and Brazil [35], as well as in other cities [12,23]. Nevertheless, there is considerable variability in this aspect, which underscores the need for studies in different contexts to confirm existing results in different countries. It is also noteworthy that, despite comparable income levels, significant discrepancies in scores were observed between two neighborhoods with similar (high) income levels in our study. In this regard, it is pertinent to highlight the distinctive characteristics of the “Centro” neighborhood. Despite the high income level of the residents, the retailers in this area demonstrate performance outcomes that are comparable to those observed in low-income neighborhoods. This may be attributed to the fact that the “Centro” neighborhood experiences the highest influx of tourists in the city of Alicante, attracted by the cultural and leisure offerings, as well as the proximity to the beach, which characterizes this neighborhood. This phenomenon appears to be influencing the food supply in the area undergoing a process of “Westernization”, with results differing from those observed in other high-income neighborhoods (Vistahermosa). Consequently, future research should examine the impact of tourism on the food supply in greater depth in other areas worldwide.
Research in different contexts that increases knowledge about the food retail environment can help to develop effective policies on a global scale that improve the situation and access to healthy food for the population, regardless of where they live. In Spain, in particular, there is a need for such food policies that act on the environment and not only at the level of individual education. For this reason, studies in different national contexts are important to know what is happening in each area.
In light of the above, it would therefore be interesting to promote the availability and accessibility of healthy food in the most disadvantaged areas through policy strategies that can enhance people’s ability to purchase better quality products, considering their economic, geographic, and cultural circumstances.
Limitations and Strengths
With regard to the limitations of this study, it should be noted that although the sample does not represent a large number, all the establishments present in the selected neighborhoods have been included. A larger sample would strengthen the findings and allow for more nuanced conclusions. On the other hand, a convenience sample was used in order to ensure socioeconomic diversity, so extrapolation of the results should be performed cautiously. In addition, this paper lacks direct data on consumer purchases or intake or the presence of in-store marketing campaigns. Future research, therefore, could be carried out taking into account the aspects mentioned above.
Notwithstanding, the present study has important strengths. First and foremost, it is the first study carried out in a medium-sized city such as Alicante. This study considers that the food supply in outlets is influenced not only by the economic level of the neighborhood but also by the offerings to tourists. In addition, a tool validated in the Mediterranean context has been used to describe and compare the availability and accessibility of food in the retail food environment and, at the same time, to compare it with previous studies carried out in other Spanish cities.
5. Conclusions
This study, carried out in the city of Alicante, shows that supermarkets have greater availability and accessibility to healthy foods than specialized establishments and convenience stores. In addition, differences were found in the accessibility and availability of healthy foods by neighborhoods with different income levels, being more accessible in the residential neighborhood with the highest income level.
The results suggest that tourism could influence the retail food environment, with high-income neighborhoods exhibiting comparable outcomes to those observed in low-income areas. Future research should investigate this aspect further in order to corroborate it.
The results obtained encourage reflection on the development and implementation of policy strategies that facilitate the availability and accessibility of healthy food in the most disadvantaged areas.
Supplementary Materials
The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/nu16234127/s1, Table S1: Comparison of food prices by neighborhood.
Author Contributions
Conceptualization, A.M.-G.; methodology, A.M.-G., I.H.-C., J.M. and E.M.T.-L.; software, J.M.; formal analysis, J.M.; investigation, A.M.-G., I.H.-C., J.M., E.M.T.-L., J.M.-C. and Á.P.-G.; data collection, J.M.-C. and Á.P.-G.; writing—original draft preparation, A.M.-G., I.H.-C., J.M. and E.M.T.-L.; writing—review and editing, A.M.-G., I.H.-C., J.M. and E.M.T.-L.; visualization, J.M.-C, and Á.P.-G.; supervision, A.M.-G. and I.H.-C.; project administration, A.M.-G.; funding acquisition, A.M.-G. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the Vice-rectorate for the Promotion of R+D+I at the University of Alicante, grant number Project ‘The role of collective catering in the development of obesogenic environment’ (reference GRE21-10A).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author. The data are not publicly available due to it has been collected in this study and there is no link or website to redirect to.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Abarca-Gómez, L.; Abdeen, Z.; Hamid, Z.A.; Abu-Rmeileh, N.; Acosta-Cazares, B.; Acuin, C.; Adams, R.; Aekplakorn, W.; Afsana, K.; Aguilar-Salinas, C.; et al. Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: A pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults. Lancet 2017, 390, 2627–2642. [Google Scholar] [CrossRef] [PubMed]
- World Health Organization: WHO. (1 March 2024). Fact Sheets. Obesity and Overweight. [Internet]. Available online: https://www.who.int/es/news-room/fact-sheets/detail/obesity-and-overweight (accessed on 1 March 2024).
- Ministerio de Sanidad, Consumo y Bienestar Social—Portal Estadístico del SNS—Encuesta Nacional de Salud de España 2017. (s. f.). Available online: https://www.mscbs.gob.es/estadEstudios/estadisticas/encuestaNacional/encuesta2017.htm (accessed on 1 March 2024).
- Kent, S.; Fusco, F.; Gray, A.; Jebb, S.A.; Cairns, B.J.; Mihaylova, B. Body mass index and healthcare costs: A systematic literature review of individual participant data studies. Obes. Rev. 2017, 18, 869–879. [Google Scholar] [CrossRef] [PubMed]
- Afshin, A.; Sur, P.J.; Fay, K.A.; Cornaby, L.; Ferrara, G.; Salama, J.S.; Mullany, E.C.; Abate, K.H.; Abbafati, C.; Abebe, Z.; et al. Health effects of dietary risks in 195 countries, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2019, 393, 1958–1972. [Google Scholar] [CrossRef] [PubMed]
- Lake, A.; Townshend, T. Obesogenic environments: Exploring the built and food environments. J. R. Soc. Promot. Health 2006, 126, 262–267. [Google Scholar] [CrossRef] [PubMed]
- Townshend, T.; Lake, A. Obesogenic environments: Current evidence of the built and food environments. Perspect. Public Health 2017, 137, 38–44. [Google Scholar] [CrossRef] [PubMed]
- Friel, S.; Hattersley, L.; Ford, L.; O’Rourke, K. Addressing inequities in healthy eating. Health Promot. Int. 2015, 30 (Suppl. S2), ii77–ii88. [Google Scholar] [CrossRef] [PubMed]
- Black, C.; Moon, G.; Baird, J. Dietary inequalities: What is the evidence for the effect of the neighbourhood food environment? Health Place 2014, 27, 229–242. [Google Scholar] [CrossRef]
- Gustafson, A.; Hankins, S.; Jilcott, S. Measures of the consumer food store environment: A systematic review of the evidence 2000–2011. J. Community Health 2012, 37, 897–911. [Google Scholar] [CrossRef]
- Caspi, C.E.; Sorensen, G.; Subramanian, S.; Kawachi, I. The local food environment and diet: A systematic review. Health Place 2012, 18, 1172–1187. [Google Scholar] [CrossRef]
- Fernández-Escobar, C.; Díez, J.; Martínez-García, A.; Bilal, U.; O’Flaherty, M.; Franco, M. Food availability and affordability in a Mediterranean urban context: Associations by store type and area-level socio-economic status. Public Health Nutr. 2023, 26, 446–454. [Google Scholar] [CrossRef]
- Díez, J.; Bilal, U.; Cebrecos, A.; Buczynski, A.; Lawrence, R.S.; Glass, T.; Escobar, F.; Gittelsohn, J.; Franco, M. Understanding differences in the local food environment across countries: A case study in Madrid (Spain) and Baltimore (USA). Prev. Med. 2016, 89, 237–244. [Google Scholar] [CrossRef] [PubMed]
- INE—Instituto Nacional de Estadística. Indicadores de Renta Media y Mediana (30833). INE 2019. Available online: https://www.ine.es/jaxiT3/Tabla.htm?t=30833 (accessed on 13 February 2024).
- Bilal, U.; Díez, J.; Alfayate, S.; Gullón, P.; Del Cura, I.; Escobar, F.; Sandín, M.; Franco, M. Population cardiovascular health and urban environments: The Heart Healthy Hoods exploratory study in Madrid, Spain. BMC Med. Res. Methodol. 2016, 16, 104. [Google Scholar] [CrossRef]
- Martínez-García, A.; Díez, J.; Fernández-Escobar, C.; Trescastro-López, E.M.; Pereyra-Zamora, P.; Ariza, C.; Bilal, U.; Franco, M. Adaptation and Evaluation of the Nutrition Environment Measures Survey in Stores to Assess Mediterranean Food Environments (NEMS-S-MED). Int. J. Environ. Res. Public Health 2020, 17, 7031. [Google Scholar] [CrossRef] [PubMed]
- Díez, J.; Bilal, U.; Franco, M. Unique features of the Mediterranean food environment: Implications for the prevention of chronic diseases Rh: Mediterranean food environments. Eur. J. Clin. Nutr. 2018, 72, 71–75. [Google Scholar] [CrossRef]
- Cauchi, D.; Pliakas, T.; Knai, C. Food environments in Malta: Associations with store size and area-level deprivation. Food Policy 2017, 71, 39–47. [Google Scholar] [CrossRef]
- Harmer, G.; Jebb, S.A.; Ntani, G.; Vogel, C.; Piernas, C. Capturing the Healthfulness of the In-store Environments of United Kingdom Supermarket Stores Over 5 Months (January–May 2019). Am. J. Prev. Med. 2021, 61, e171–e179. [Google Scholar] [CrossRef]
- Millichamp, A.; Gallegos, D. Comparing the availability, price, variety and quality of fruits and vegetables across retail outlets and by area-level socio-economic position. Public Health Nutr. 2012, 16, 171–178. [Google Scholar] [CrossRef]
- Stroebele-Benschop, N.; Wolf, K.; Palmer, K.; Kelley, C.J.; Pitts, S.B.J. Comparison of food and beverage products’ availability, variety, price and quality in German and US supermarkets. Public Health Nutr. 2020, 23, 3387–3393. [Google Scholar] [CrossRef]
- Liu, Y.; Song, S.; Gittelsohn, J.; Jiang, N.; Hu, J.; Ma, Y.; Wen, D. Adaptation and Validation of the Chinese Version of the Nutrition Environment Measurement Tool for Stores. Int. J. Environ. Res. Public Health 2019, 16, 782. [Google Scholar] [CrossRef]
- Londoño-Cañola, C.; Serral, G.; Díez, J.; Martínez-García, A.; Franco, M.; Artazcoz, L.; Ariza, C. Retail Food Environment around Schools in Barcelona by Neighborhood Socioeconomic Status: Implications for Local Food Policy. Int. J. Environ. Res. Public Health 2022, 20, 649. [Google Scholar] [CrossRef]
- Hawkes, C. Dietary Implications of Supermarket Development: A Global Perspective. Dev. Policy Rev. 2008, 26, 657–692. [Google Scholar] [CrossRef]
- Martínez-García, A.; Trescastro-López, E.M.; Galiana-Sánchez, M.E.; Llorens-Ivorra, C.; Pereyra-Zamora, P. Cultural Adaptation and Evaluation of the Perceived Nutrition Environment Measures Survey to the Mediterranean Spanish Context (NEMS-P-MED). Nutrients 2020, 12, 3257. [Google Scholar] [CrossRef]
- Bilal, U.; Jones-Smith, J.; Diez, J.; Lawrence, R.S.; Celentano, D.D.; Franco, M. Neighborhood social and economic change and retail food environment change in Madrid (Spain): The heart healthy hoods study. Health Place 2018, 51, 107–117. [Google Scholar] [CrossRef]
- Achón, M.; Serrano, M.; García-González, Á.; Alonso-Aperte, E.; Varela-Moreiras, G. Present Food Shopping Habits in the Spanish Adult Population: A Cross-Sectional Study. Nutrients 2017, 9, 508. [Google Scholar] [CrossRef]
- Shaw, S.C.; Ntani, G.; Baird, J.; A Vogel, C. A systematic review of the influences of food store product placement on dietary related outcomes. Nutr. Rev. 2020, 78, 1030–1045. [Google Scholar] [CrossRef]
- Bodor, J.N.; Rose, D.; Farley, T.A.; Swalm, C.; Scott, S.K. Neighbourhood fruit and vegetable availability and consumption: The role of small food stores in an urban environment. Public Health Nutr. 2008, 11, 413–420. [Google Scholar] [CrossRef]
- Black, C.; Ntani, G.; Inskip, H.; Cooper, C.; Cummins, S.; Moon, G.; Baird, J. Measuring the healthfulness of food retail stores: Variations by store type and neighbourhood deprivation. Int. J. Behav. Nutr. Phys. Act. 2014, 11, 69. [Google Scholar] [CrossRef]
- Goossensen, M.; Garcia, X.; Garcia-Sierra, M.; Calvet-Mir, L.; Domene, E. The role of convenience stores in healthy food environments: The case of Barcelona (Spain). Cities 2023, 133, 104118. [Google Scholar] [CrossRef]
- Pechey, R.; Monsivais, P. Supermarket Choice, Shopping Behavior, Socioeconomic Status, and Food Purchases. Am. J. Prev. Med. 2015, 49, 868–877. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
- Fernqvist, F.; Spendrup, S.; Tellström, R. Understanding food choice: A systematic review of reviews. Heliyon 2024, 10, e32492. [Google Scholar] [CrossRef]
- Thow, A.M.; Downs, S.M.; Mayes, C.; Trevena, H.; Waqanivalu, T.; Cawley, J. Fiscal policy to improve diets and prevent noncommunicable diseases: From recommendations to action. Bull. World Health Organ. 2018, 96, 201–210. [Google Scholar] [CrossRef] [PubMed]
- Gomes, C.S.; Silveira, E.A.; Velasquez-Melendez, G. Neighborhood environment is associated with unhealthy food intake in a Brazilian urban area. Appetite 2022, 172, 105972. [Google Scholar] [CrossRef]
Figure 1.
Total and availability scores from the NEMS-S-MED survey by type of food store.
Figure 2.
Total and availability scores from the NEMS-S-MED survey by neighborhood.
Table 1.
Percentage of types of food stores in each neighborhood and by socioeconomic level.
| Type of Food Store | Total | Neighborhood | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| High Economic Level | Low Economic Level | |||||||||
| Vistahermosa | Centro | Carolinas Altas | Virgen del Carmen | |||||||
| n | % | n | % | n | % | n | % | n | % | |
| Supermarkets | 16 | 25.4 | 4 | 40.0 | 5 | 41.7 | 6 | 16.7 | 1 | 20.0 |
| Convenience stores | 16 | 25.4 | 2 | 20.0 | 2 | 16.7 | 10 | 27.8 | 2 | 40.0 |
| Specialized stores | 31 | 49.3 | 4 | 40.0 | 5 | 41.7 | 20 | 55.6 | 2 | 40.0 |
| Total | 63 | 100 | 10 | 100 | 12 | 100 | 36 | 5 | 100 | |
Table 2.
Availability of the food items included in NEMS-S-MED by type of food store and neighborhood.
Table 2.
Availability of the food items included in NEMS-S-MED by type of food store and neighborhood.
| Food Item | Type of Food Store | Neighborhood | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Supermarket | Convenience Stores | Specialized Stores | Total | Sig | Vistahermosa | Centro | Carolinas Altas | Virgen del Carmen | Total | Sig (b) | |
| Fresh fruit | 93.8% | 18.8% | 35.5% | 46.0% | <0.001 (a) | 70.0% | 66.7% | 30.6% | 60% | 46.0% | 0.037 |
| Fresh vegetables | 93.8% | 18.8% | 38.7% | 47.6% | <0.001 (a) | 70.0% | 66.7% | 33.3% | 60% | 47.6% | 0.067 |
| Potatoes | 93.8% | 12.5% | 41.9% | 47.6% | <0.001 (a) | 60.0% | 66.7% | 36.1% | 60% | 47.6% | 0.204 |
| Frozen vegetables | 75.0% | 18.8% | 9.7% | 28.6% | <0.001 (b) | 60.0% | 33.3% | 19.4% | 20% | 28.6% | 0.093 |
| Unprocessed nuts | 87.5% | 25.0% | 32.3% | 44.4% | <0.001 (a) | 80.0% | 33.3% | 41.7% | 20% | 44.4% | 0.079 |
| Salty nuts | 81.3% | 93.8% | 29.0% | 58.7% | <0.001 (a) | 80.0% | 41.7% | 58.3% | 60% | 58.7% | 0.353 |
| Light cola drink | 93.8% | 93.8% | 54.8% | 74.6% | 0.002 (b) | 70.0% | 66.7% | 80.6% | 60% | 74.6% | 0.553 |
| Regular cola drink | 93.8% | 93.8% | 61.3% | 77.8% | 0.012 (b) | 70.0% | 66.7% | 86.1% | 60% | 77.8% | 0.236 |
| Juice 100% | 68.8% | 12.5% | 9.7% | 25.4% | <0.001 (b) | 50.0% | 41.7% | 11.1% | 40% | 25.4% | 0.012 |
| Not-100% juice | 87.5% | 75.0% | 48.4% | 65.1% | 0.018 (a) | 70.0% | 33.3% | 77.8% | 40% | 65.1% | 0.041 |
| Whole bread | 81.3% | 25.0% | 35.5% | 44.4% | 0.002 (a) | 90.0% | 50.0% | 33.3% | 20% | 44.4% | 0.006 |
| Low sugar cereals | 56.3% | -- | 19.4% | 23.8% | <0.001 (b) | 30.0% | 41.7% | 19.4% | 0% | 23.8% | 0.270 |
| Regular cereals | 93.8% | 37.5% | 9.7% | 38.1% | <0.001 (a) | 60.0% | 50.0% | 30.6% | 20% | 38.1% | 0.248 |
| Confectionery | 93.8% | 100.0% | 54.8% | 76.2% | <0.001 (b) | 80.0% | 58.3% | 80.6% | 80% | 76.2% | 0.453 |
| Skimmed milk | 100.0% | 37.5% | 22.6% | 46.0% | <0.001 (a) | 70.0% | 58.3% | 38.9% | 20% | 46.0% | 0.185 |
| Semi-skimmed milk | 100.0% | 56.3% | 25.8% | 52.4% | <0.001 (a) | 70.0% | 66.7% | 47.2% | 20% | 52.4% | 0.210 |
| Whole milk | 100.0% | 75.0% | 29.0% | 58.7% | <0.001 (a) | 80.0% | 66.7% | 50.0% | 60% | 58.7% | 0.359 |
| Skimmed yogurt | 68.8% | -- | 3.2% | 19.0% | <0.001 (b) | 30.0% | 33.3% | 13.9% | 0% | 19.0% | 0.277 |
| Semi-hard cheese | 100.0% | 37.5% | 19.4% | 44.4% | <0.001 (a) | 70.0% | 50.0% | 33.3% | 60% | 44.4% | 0.156 |
| Fresh cheese | 100.0% | 31.3% | 22.6% | 44.4% | <0.001 (a) | 70.0% | 41.7% | 36.1% | 60% | 44.4% | 0.255 |
| Eggs | 100.0% | 62.5% | 77.4% | 79.4% | 0.018 (b) | 100.0% | 75.0% | 72.2% | 100% | 79.4% | 0.181 |
| Olive oil | 93.8% | 43.8% | 25.8% | 47.6% | <0.001 (a) | 80.0% | 41.7% | 38.9% | 60% | 47.6% | 0.124 |
| Sunflower oil | 75.0% | 37.5% | 19.4% | 38.1% | <0.001 (a) | 40.0% | 41.7% | 33.3% | 60% | 38.1% | 0.639 |
| Salt-free butter | 87.5% | 12.5% | 9.7% | 30.2% | <0.001 (b) | 40.0% | 41.7% | 25.0% | 20% | 30.2% | 0.605 |
| Regular butter | 93.8% | 50.0% | 12.9% | 42.9% | <0.001 (a) | 50.0% | 50.0% | 33.3% | 80% | 42.9% | 0.210 |
| Whole rice | 75.0% | 6.3% | 3.2% | 22.2% | <0.001 (b) | 40.0% | 33.3% | 11.1% | 40% | 22.2% | 0.054 |
| White rice | 100.0% | 75.0% | 29.0% | 58.7% | <0.001 (a) | 70.0% | 50.0% | 58.3% | 60% | 58.7% | 0.854 |
| Legumes | 100.0% | 75.0% | 41.9% | 65.1% | <0.001 (a) | 90.0% | 75.0% | 55.6% | 60% | 65.1% | 0.182 |
| Beef | 62.5% | -- | 29.0% | 30.2% | <0.001 (b) | 50.0% | 16.7% | 27.8% | 40% | 30.2% | 0.345 |
| Chicken | 75.0% | -- | 29.0% | 33.3% | <0.001 (a) | 50.0% | 25.0% | 30.6% | 40% | 33.3% | 0.628 |
| Sausage | 93.8% | 56.3% | 29.0% | 52.4% | <0.001 (a) | 70.0% | 58.3% | 41.7% | 80% | 52.4% | 0.225 |
| Fresh fish | 37.5% | -- | -- | 9.5% | <0.001 (b) | 20.0% | 8.3% | 8.3% | 0% | 9.5% | 0.640 |
| Unprocessed frozen fish | 68.8% | 6.3% | -- | 19.0% | <0.001 (b) | 50% | 25.0% | 8.3% | 20% | 19% | 0.018 |
| Processed frozen fish | 68.8% | 6.3% | 3.2% | 20.6% | <0.001 (b) | 50% | 25.0% | 11.1% | 20% | 20.6% | 0.045 |
| Canned tuna | 87.5% | 62.5% | 29.0% | 52.4% | <0.001 (a) | 80% | 50.0% | 44.4% | 60% | 52.4% | 0.242 |
| Plant-based beverage with added sugar | 87.5% | 18.8% | 3.2% | 28.6% | <0.001 (b) | 20% | 41.7% | 60% | 16.7% | 28.6% | 0.030 |
| Plant-based beverage without added sugar | 75.0% | 12.5% | 3.2% | 23.8% | <0.001 (b) | 20% | 33.3% | 50% | 13.9% | 23.8% | 0.074 |
| Yogurts without sugar/sweetener | 81.3% | 0% | 3.2% | 22.2% | <0.001 (b) | 40% | 41.7% | 13.9% | 0% | 22.2% | 0.061 |
| Yogurts with sugar | 87.5% | 31.3% | 16.1% | 38.1% | <0.001 (a) | 60% | 33.3% | 36.1% | 20% | 38.1% | 0.461 |
(a) Chisquare-test; (b) Fisher exact test.
Table 3.
Comparison of availability and price of food items divided by its composition in more or less content of saturated fat, salt, and sugar.
Table 3.
Comparison of availability and price of food items divided by its composition in more or less content of saturated fat, salt, and sugar.
| Availability | Price | |||||||
|---|---|---|---|---|---|---|---|---|
| Less FSS (1) | High FSS (1) | Difference | p-Value (2) | Less FSS (1) | High FSS (1) | Difference | p-Value (2) | |
| Nuts (unprocessed vs. salty) | 44.44% | 58.73% | −14.29% | 0.049 | - | - | - | - |
| Juice (100% vs. not 100%) | 25.40% | 65.08% | −39.68% | <0.001 | 2.32 (1.34) | 1.92 (0.94) | 0.40 | 0.037 |
| Cola (light vs. regular) | 74.60% | 77.8% | −3.17% | 0.500 | 2.06 (0.87) | 2.21 (0.99) | −0.15 | 0.317 |
| Milk (Skimmed vs. whole) | 46.03% | 58.73% | −12.70% | 0.021 | 1 (0.00) | 1.14 (0.55) | −0.14 | 1.000 |
| Cheese (Fresh vs. semi-hard) | 44.44% | 44.44% | 0.00% | 1 | - | - | - | - |
| Oil (olive vs. sunflower) | 47.62% | 38.10% | 9.52% | 0.146 | 5.36 (1.36) | 3.75 (1.59) | 1.61 | 0.000 |
| Rice (whole vs. white) | 22.22% | 58.73% | −36.51% | <0.001 | 2.11 (1.23) | 1.51 (0.77) | 0.60 | 0.004 |
| Meat (chicken vs. beef) | 33.33% | 30.16% | 3.17% | 0.5 | 6.60 (1.74) | 12.76 (2.73) | −6.16 | 0.000 |
| Frozen fish (unprocessed vs. processed) | 19.05% | 20.63% | −1.59% | 1 | - | - | - | |
| Cereals (Low sugar vs. regular) | 15.87% | 38.10% | −22.22% | 0.001 | - | - | - | |
| Yogurts (without sugar/sweetener vs. with sugar) | 22.22% | 38.10% | −15.87% | 0.006 | 3.60 (3.66) | 2.95 (1.91) | 0.65 | 0.092 |
| Plant-based beverage (without added sugar vs. with added sugar) | 23.81% | 28.57% | −4.76% | 0.25 | 1.62 (0.53) | 1.41 (0.54) | 0.21 | 0.209 |
(1) FSS (saturated fat, salt, and sugar); (2) McNemar test.
Table 4.
Linear mixed model for the NEMS-S-MED total and availability scores.
| Parameter | NEMS-S-MED Total | NEMS-S-MED Availability | ||
|---|---|---|---|---|
| Fixed Effects | Estimate | 95%CI | Estimate | 95%CI |
| Type of food retailer (a) | ||||
| Supermarket (Base) | ||||
| Convenience store | −20.615 (a) | −24.996, −16.235 | −18.401 (a) | −22.347, −14.455 |
| Specialized stores | −19.792 (a) | −23.608, −15.976 | −17.025 (a) | −20.462, −13.588 |
| Neighborhood by economic level (a) | ||||
| Low—Virgen del Carmen (Base) | ||||
| Low—Carolinas altas | −0.635 | −6.401, 5.130 | −1.556 | −6.750, 3.637 |
| High—Vistahermosa | 7.777 (b) | 1.128, 14.426 | 5.420 | −0.569, 11.409 |
| High—Centro | −0.980 | −7.461, 5.500 | −1.493 | −7.330, 4.344 |
(a) p < 0.01 (b) p < 0.05.
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Hernández-Caravaca, I.; Martínez-García, A.; Trescastro-López, E.M.; Plaza-Gavaldón, Á.; Martí-Cremades, J.; Moncho, J. Influence of Socioeconomic Status on the Retail Food Environment in Alicante. Nutrients 2024, 16, 4127. https://doi.org/10.3390/nu16234127
AMA Style
Hernández-Caravaca I, Martínez-García A, Trescastro-López EM, Plaza-Gavaldón Á, Martí-Cremades J, Moncho J. Influence of Socioeconomic Status on the Retail Food Environment in Alicante. Nutrients. 2024; 16(23):4127. https://doi.org/10.3390/nu16234127
Chicago/Turabian StyleHernández-Caravaca, Iván, Alba Martínez-García, Eva María Trescastro-López, Ángel Plaza-Gavaldón, Julio Martí-Cremades, and Joaquín Moncho. 2024. "Influence of Socioeconomic Status on the Retail Food Environment in Alicante" Nutrients 16, no. 23: 4127. https://doi.org/10.3390/nu16234127
APA StyleHernández-Caravaca, I., Martínez-García, A., Trescastro-López, E. M., Plaza-Gavaldón, Á., Martí-Cremades, J., & Moncho, J. (2024). Influence of Socioeconomic Status on the Retail Food Environment in Alicante. Nutrients, 16(23), 4127. https://doi.org/10.3390/nu16234127
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