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Article

Effect of Tourism Pressure on the Mediterranean Diet Pattern

1
Department of Quantitative Methods for Economics and Management, University of Las Palmas de Gran Canaria, 35017 Las Palmas, Spain
2
Service of Preventive Medicine, Complejo Hospitalario Universitario Insular Materno-Infantil, Canary Health Service, Las Palmas de Gran Canaria, 35016 Las Palmas, Spain
3
Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria, 35016 Las Palmas, Spain
4
Department of Applied Economics and Quantitative Methods, University of La Laguna, 38200 Santa Cruz de Tenerife, Spain
*
Author to whom correspondence should be addressed.
Nutrients 2018, 10(10), 1338; https://doi.org/10.3390/nu10101338
Received: 16 August 2018 / Revised: 15 September 2018 / Accepted: 18 September 2018 / Published: 20 September 2018

Abstract

:
Despite proposed conceptual frameworks of eating behaviors, little is known about environmental factors contributing to changes in food habits. Few studies have reported the external influence of tourism on the inhabitants’ eating patterns. The present study aimed to investigate whether tourism pressure affects Canary Islands inhabitants’ adherence to the Mediterranean diet pattern. Data were obtained from a health and lifestyle population-based survey conducted in 2009 and 2015. From the reported intake frequency, a Mediterranean diet score was defined (0 to 11 points). Tourist overnight stays, which were stratified by nationality and area of destination, were used as a proxy variable to measure tourism pressure. A multilevel linear regression analysis by restricted maximum likelihood estimation was performed to examine the relationship between tourism pressure and the Mediterranean diet score. A significant negative association between the Mediterranean diet score and British tourism pressure was observed (β = −0.0064, p = 0.010), whereas German tourism pressure increased inhabitants’ adherence (β = 0.0092, p = 0.042). The socioeconomic level of tourists seems to play a role in differences in the tourism pressure effect by nationality. Further investigation of other highly touristic destinations is needed to confirm these findings that could contribute to a shift in tourism and public health nutrition policies.

Graphical Abstract

1. Introduction

Tourism can have either a positive or a negative social effect on a host society. High tourist inflows could enhance a rapid change in local lifestyles [1,2,3], affecting people’s habits, daily routines, social lives, beliefs and values [4]. In small regions, especially if population density is high, cross-cultural tourism encounters are even more frequent and intense [2,5].
The most common tourist destination in the EU for non-residents is Spain (269 million nights spent in tourist accommodation establishments in 2015), and the Spanish region with the highest number of tourist overnight stays is the Canary Islands (94 million nights), which accounted for 3.4% of the total nights spent in the whole of the EU, 28 [6]. In contrast to other tourist destinations, the inflow of tourists is stable all year round in these Spanish islands, as the main reason for traveling to this highly specialized sun and beach tourism destination is its mild subtropical climate [7,8]. Regarding tourism intensity, defined as the ratio of nights spent at a tourist accommodation establishment relative to the total permanent resident population of the area [9], the Canary Islands recorded a ratio of 44,219 nights spent per 1000 inhabitants in 2015 [6], which indicates that the magnitude of incoming tourists in relation to the population in this outermost region of the EU is quite remarkable. However, the Canarian population consider tourism as a resource and their support toward tourism has grown in the last years [10,11].
As tourists are viewed as agents of change [2,3,5], and their food choices and preferences have a significant impact on local food supply [12], tourism could have an effect on the eating patterns of the inhabitants [13,14,15].
During the latter half of the 20th century, globalization drove food production and consumption [13,16,17,18,19,20,21], resulting in a nutrition transition phenomenon worldwide that has led to the westernization of food consumption patterns [17,18,22,23,24]. In the Mediterranean countries, these eating pattern shifts could compromise both the beneficial effects in terms of the health and well-being of the Mediterranean dietary pattern [14,25,26,27] and its quality as a sustainable diet model [22,28]. Although the geographical isolation of islands is seen as a barrier that retains cultural and social features, the nutrition transition has also been described in islands of the Mediterranean countries [14,15,29]. As these islands are frequent tourist destinations, the acculturation process, explained as the interaction of groups that fosters the exchange of cultural elements, might be an explanation for these findings [2,5,18]. Thus, the external influence of the incoming tourists on eating patterns needs to be assessed while taking into account tourists’ nationality, as substantial differences due to food cultures might be found [12,30].
Therefore, the aim of the present study was to investigate whether tourist pressure affects Canary Islands inhabitants’ adherence to the Mediterranean diet.

2. Materials and Methods

2.1. Dataset

Data were obtained from a health and lifestyle population-based survey conducted in the Canary Islands in 2009 and 2015 [31,32], which consisted of a stratified randomly selected sample of 5984 and 5703 individuals, respectively. Excluding subjects below the age of 16 or from the islands of La Gomera and El Hierro, where no tourist inflow data were available, the final sample consisted of 8303 individuals living in nine areas. Areas were defined as north, metropolitan and south of Gran Canaria and Tenerife, respectively, and the islands of Fuerteventura, Lanzarote and La Palma.

2.2. Adherence to the Mediterranean Dietary Pattern

The survey assessed intake frequency of fresh fruits, vegetables, cereals, dairy products, fish, eggs, legumes, meat, cold meat and sausages, sweets and soft drinks as daily, three or more times per week, one to two times per week, less than once a week and never/almost never. A Mediterranean diet score was defined based on the Mediterranean diet eating pattern recommendations [16]: daily intake of vegetables, fruits, cereals and dairy products; intake of fish, legumes and eggs three times a week; intake of meat one to two times a week; intake of cold meat/sausages, sweets and soft drinks less than once a week. If the condition was met, 1 point was recorded for the category so that the final score ranged from 0 to 11.

2.3. Tourist Inflow

The arrival of tourists and their average stay, stratified by tourist nationality and area of destination, were obtained from the tourist expenditure database of the Canarian Institute for Statistics [33]. Overnight stays were calculated and used as a proxy variable to measure tourist pressure.

2.4. Statistical Analysis

Descriptive characteristics were summarized by calculating means and standard deviations for continuous variables and frequencies for categorical values. As the variables were not normally distributed, medians and interquartile ranges are also reported. Multilevel linear regression analysis by restricted maximum likelihood estimation [34] was performed to examine the relationship between tourist pressure and the Mediterranean diet score. The year of the survey and other individual-level variables were tentatively included as fixed-effect variables. The Wald test was used to decide variable permanence in the model in a forward strategy of specification (explanatory variables that failed to reach a significantly better fit than the previous model were dropped). The final model can be written as Equation (1):
y i j = β 0 + β 1 x 1 j + β 2 x 2 j + β 3 x 3 j + β K z K i j + u j + e i j ,
where y i j is the Mediterranean diet score estimate for an individual i living in an area j ; x 1 j , x 2 j and x 3 j are, respectively, British, German and other nationalities tourists overnight stays in an area area j ; β , the fixed-effect regression coefficients; z K i j , the fixed-effect individual explanatory variables (age, sex, civil status, educational level, BMI (Body Mass Index), smoking, alcohol, VAS-HRQL (Visual Analogue Scale-Health Related Quality of Life), employment status and year of survey); u j , the area-level random error; and, e i j , the individual-level random residual error. Subsequently, β 1 , β 2 and β 3 coefficients were the focus of interest. Intra-class correlation was also estimated to measure the proportion of total variance attributable to differences between areas.
Statistical analyses were performed using the statistical software Stata/SE version 14 (Stata Corp., College Station, TX, USA).

3. Results

3.1. Participant Characteristics

Details regarding the age, sex, place of birth, civil status, educational level, BMI, smoking status, alcohol consumption, VAS-HRQL, labour market status, and survey cohort characteristics of the study population are shown in Table 1. The mean Mediterranean diet score slightly decreased between cohorts; 5.20 (SD 1.66) in 2009 and 5.17 (SD 1.84) in 2015.

3.2. Tourism Pressure

Tourist overnight stays increased for all nationalities in the nine areas studied except for Spanish tourists. The largest increase was for British tourists, mainly in the north and metropolitan areas of Gran Canaria and in the metropolitan area of Tenerife (732.23%, 402.59% and 360.02%, respectively). Table 2 describes the number of tourist overnight stays per year and the percent change in the rate, by nationality and area of destination.

3.3. Mediterranean Diet Score and Tourist Pressure by Nationality

Hierarchical regression analysis of the MD-score with tourist pressure is shown in Table 3. A significant negative association between the MD-score and British tourists pressure was observed (β = −0.0064, p = 0.010), which means that 10 million British tourists’ overnight stays were associated with a 0.64 decrease in the MD-score in the local population. The opposite was observed with German tourist pressure, which showed a borderline significant positive association (β = 0.0092, p = 0.042). No significant relation was present with other tourist pressure. Between the 2009 and the 2015 cohort of participants, the MD-score significantly changed (β = −0.0214, p = 0.005). A significant relation was also present within all age groups; women; all education levels; moderate and heavy smokers; those who drink alcohol; those married; those employed or retired; those with pre-obesity, obesity class I or obesity class II; and with a VAS-HRQL score. The proportion of total variance attributable to differences between areas of destination was 4.21%.

4. Discussion

The literature has paid substantial attention to the identification of dietary patterns and their association with non-communicable diseases [35,36]. However, there are still gaps in the knowledge of factors contributing to changes in food habits. Proposed conceptual frameworks of eating behaviors [37,38,39,40] recognize the importance of the environmental context in which people live, where tourism, as a driver of change on local food supply and inhabitants’ lifestyles, could have an effect at the macro level food environment [4,12,39].
Our results regarding a decrease in adherence to the Mediterranean diet are in agreement with other studies [29,41]. Although the magnitude of the change is small between the Canarian population cohorts, this observation might be due to the relatively short period of time evaluated.
In accordance with previous studies, our results showed that the MD-score was higher in women [42,43,44,45,46,47], older generations [43,45,47], non-smokers [42,47] and higher educational levels [42,47,48,49,50]. An inverse correlation between BMI and adherence to the Mediterranean diet pattern was also found [44]. Although marital status was not related in some recent studies [42], our results are in agreement with others where those married show a higher MD-score than single subjects [46,50]. Though other studies assessed HRQL by using the SF-36 health survey [51,52], a significantly positive association between adherence to the Mediterranean diet and VAS-HRQL was also found in the present study. In contrast to our results where those who reported alcohol consumption seem to have a lower MD-score, other studies have found a greater consumption of alcohol in the most adherent group [43,44]. However, these results might be expected as regular and moderate alcohol consumption was considered in those studies as a component of the MD-score.
The external influence of tourists on the inhabitants’ eating patterns has been reported previously in some insular societies, where geographical isolation is seen as a barrier that retains food habits [14,15]. The present study is original in our methods for quantifying the tourist pressure effect, which, as we hypothesized, varies depending on tourists’ nationality. While British tourist pressure decreases inhabitants’ adherence to the Mediterranean diet pattern, Germans have a positive significant influence on the MD-score. Additionally, our results provide insight on the magnitude of the tourist pressure effect, as 10 million British tourist overnight stays appear to have the same negative effect size as other commonly studied explanatory variables, such as heavy smokers (β = −0.6068), and almost double that of others such as obesity type I (β = −0.2125), whereas an equivalent German tourist pressure is nearly three times the positive effect of a tertiary education level (β = 0.3335). These results might be related to differences in food culture or the profile of tourists.
Overall, there were significant differences in the characteristics of tourists between nationalities. German tourists were older, with a higher professional qualification and a higher income level, whereas the proportion of women was higher among the British tourists; these differences remain in each of the cohorts [7]. Hence, in addition to age and sex, tourist socioeconomic status seems to play a role in the direction of the tourist pressure effect.
Regarding food culture, an upward trend of adherence to the Mediterranean diet pattern in some Non-Mediterranean countries, such as the United Kingdom, has previously been reported [53]. However, depending on which MD-score is used, adherence seems to be either lower in Germany than in the UK or with no remarkable differences between these two countries [53,54]. Thus, as with a large body of epidemiological studies, where diet quality, and, in particular, the traditional Mediterranean diet pattern, follows a socioeconomic gradient [55,56,57,58], differences in tourism pressure by nationality might be related to the socioeconomic level of the tourists.
Tourists are also likely to be influenced by local food culture when on vacation, consuming foods from the regions visited [59]. Although 71.48% of British and German tourists who visited the Canary Islands reported to have tasted local food [7], there is no evidence about a major shift in their food habits during holidays. Furthermore, 17.30% of total expenditure on food establishments in this destination were made by tourists in 2016 [60] so, consequently, food supply might be in line with food preferences of tourists.
This study has both limitations and strengths. The main advantage is its population-based design and the availability of tourist inflow data collected at a matching time. Moreover, the hierarchical model used considers the presence of clustering, which means non-independence of the outcome variable among people from the same area. Additionally, the study population is located in a highly touristic and ultraperipheral region, which makes findings relevant to other insular or continental environments that are important tourist destinations. On the other hand, as a repeated cross-sectional design is used, no individual change can be studied, though it is useful to examine changes over time at a population level. Furthermore, dietary assessment method with food frequency questionnaires (FFQ) are not free of systematic and random errors, and the use of scores to measure adherence is subject to chosen cut-off points, which may influence research findings. Nevertheless, FFQs and scores are valuable tools to evaluate epidemiological associations [14,28,42,61,62]. Although tourist pressure seems to have an influence on adherence to the Mediterranean eating pattern, it is not possible to isolate the tourism effect from other external factors, such as urbanization, industrialization, food production and importation patterns, fast-food consumption or financial crisis [17,24,49,63].

5. Conclusions

In the present study, the importance of environmental context on diet is recognized, as tourist pressure has an effect on the inhabitants’ adherence to the Mediterranean diet pattern. The socioeconomic level of tourists seems to be a determinant in the direction of the effect, driving food habits of the inhabitants. However, further investigation of other highly touristic destinations is needed to confirm these findings that could contribute to a shift in tourism and public health nutrition policies.

Author Contributions

Conceptualization, B.G.L.-V. and L.S.-M.; Methodology, S.R.-M. and B.G.L.-V.; Formal Analysis, S.R.-M., B.G.L.-V. and A.H.-Y.; Investigation, S.R.-M., B.G.L.-V., L.S.-M., A.H.-Y., P.B.-P., J.P.-D., S.R.-F. and A.R.-C; Writing-Original Draft Preparation, S.R.-M.; Writing-Review & Editing, S.R.-M., B.G.L.-V., L.S.-M., A.H.-Y., P.B.-P., J.P.-D., S.R.-F. and A.R.-C.; Project Administration, B.G.L.-V.; Funding Acquisition, B.G.L.-V. and L.S.-M.

Funding

This research was funded by the Tricontinental Atlantic Campus (CEI2017-25), University of Las Palmas de Gran Canaria and the Agencia Estatal de Investigación/Fondo Europeo de Desarrollo Regional (ECO2017-83771-C3-2-R).

Acknowledgments

The authors would like to thank individuals from the Canarian Institute for Statistics who provided the dataset used in this study.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

References

  1. Goeldner, C.R.; Brent Ritchie, J.R. Sociology of tourism. In Tourism: Principles, Practices, Philosophies, 12th ed.; Wiley: Hoboken, NJ, USA, 2009; pp. 303–329. [Google Scholar]
  2. Reisinger, Y.; Dimanche, F. Cultural practices and tourism impacts on culture. In International Toursim Cultures and Behaviour, 1st ed.; Routledge: Abington, Thames, UK, 2008; pp. 67–82. [Google Scholar]
  3. Akis, A. The effects of mass tourism: A case study from Manavgat (Antalya-Turkey). Procedia Soc. Behav. Sci. 2011, 19, 289–296. [Google Scholar] [CrossRef]
  4. Doǧan, H.Z. Forms of adjustment. Ann. Tour. Res. 1989, 16, 216–236. [Google Scholar] [CrossRef]
  5. De Kadt, E. World Bank and Unesco. In Tourism: Passport to Development? 2nd ed.; Oxford University Press: Oxford, UK, 1979. [Google Scholar]
  6. Eurostat Regional Yearbook: 2017 edition. Available online: https://ec.europa.eu/eurostat/statistics-explained/index.php/Eurostat_regional_yearbook (accessed on 1 December 2017).
  7. Instituto Canario de Estadística Encuesta sobre el Gasto Turístico. Datos Publicados. Available online: http://www.gobiernodecanarias.org/istac/temas_estadisticos/sectorservicios/hosteleriayturismo/demanda/ (accessed on 20 September 2017).
  8. Instituto Nacional de Estadística Encuesta de Gasto Turístico. Resultados. Available online: http://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736177002&menu=resultados&idp=1254735576863 (accessed on 5 November 2017).
  9. Eurostat Tourism Glossary. Available online: http://ec.europa.eu/eurostat/statistics-explained/index.php/Category:Tourism_glossary (accessed on 5 November 2017).
  10. Garau-Vadell, J.B.; Díaz-Armas, R.; Gutierrez-Taño, D. Residents’ perceptions of tourism impacts on island destinations: A comparative analysis. Int. J. Tour. Res. 2014, 16, 578–585. [Google Scholar] [CrossRef]
  11. Garau-Vadell, J.B.; Gutierrez-Taño, D.; Diaz-Armas, R. Economic crisis and residents’ perception of the impacts of tourism in mass tourism destinations. J. Destin. Mark. Manag. 2018, 7, 68–75. [Google Scholar] [CrossRef]
  12. Mak, A.H.N.; Lumbers, M.; Eves, A. Globalisation and food consumption in tourism. Ann. Tour. Res. 2012, 39, 171–196. [Google Scholar] [CrossRef][Green Version]
  13. Romaguera, D.; Samman, N.; Rossi, A.; Miranda, C.; Pons, A.; Tur, J.A. Dietary patterns of the Andean population of Puna and Quebrada of Humahuaca, Jujuy, Argentina. Br. J. Nutr. 2008, 99, 390–397. [Google Scholar] [CrossRef] [PubMed]
  14. Romaguera, D.; Bamia, C.; Pons, A.; Tur, J.A.; Trichopoulou, A. Food patterns and Mediterranean diet in western and eastern Mediterranean islands. Public Health Nutr. 2009, 12, 1174–1181. [Google Scholar] [CrossRef] [PubMed]
  15. Tessier, S.; Gerber, M. Factors determining the nutrition transition in two Mediterranean islands: Sardinia and Malta. Public Health Nutr. 2005, 8, 1286–1292. [Google Scholar] [CrossRef] [PubMed]
  16. Bach-Faig, A.; Berry, E.M.; Lairon, D.; Reguant, J.; Trichopoulou, A.; Dernini, S.; Medina, F.X.; Battino, M.; Belahsen, R.; Miranda, G.; et al. Mediterranean diet pyramid today. Science and cultural updates. Public Health Nutr. 2011, 14, 2274–2284. [Google Scholar] [CrossRef] [PubMed][Green Version]
  17. Bermudez, O.I.; Tucker, K.L. Trends in dietary patterns of Latin American populations. Cad. Saude Publica 2003, 19, 87–99. [Google Scholar] [CrossRef]
  18. Satia, J.A. Dietary acculturation and the nutrition transition: An overview. In Can we identify culture-specific healthful dietary patterns among diverse populations undergoing nutrition transition? The CSCN-CSNS 2009 Conference. Appl. Physiol. Nutr. Metab. 2010, 35, 219–223. [Google Scholar] [CrossRef] [PubMed]
  19. Lang, T. The complexities of globalization: The UK as a case study of tensions within the food system and the challenge to food policy. Agric. Hum. Values 1999, 16, 169–185. [Google Scholar] [CrossRef]
  20. Wilhelmina, Q.; Joost, J.; George, E.; Guido, R. Globalization vs. localization: Global food challenges and local solutions. Int. J. Consum. Stud. 2010, 34, 357–366. [Google Scholar] [CrossRef]
  21. Oosterveer, P. Globalization and sustainable consumption of shrimp: Consumers and governance in the global space of flows. Int. J. Consum. Stud. 2006, 30, 465–476. [Google Scholar] [CrossRef]
  22. Donini, L.M.; Serra-Majem, L.; Bulló, M.; Gil, Á.; Salas-Salvadó, J. The Mediterranean diet: Culture, health and science. Br. J. Nutr. 2015, 113, S1–S3. [Google Scholar] [CrossRef] [PubMed]
  23. Popkin, B.M.; Horton, S.; Kim, S. The Nutrition Transition and Diet-related Chronic Diseases in Asia: Implications for Prevention; International Food Policy Research Insititute: Washington, DC, USA, 2001. [Google Scholar]
  24. Popkin, B.M. The nutrition transition: An overview of world patterns of change. Nutr. Rev. 2004, 62, 140–143. [Google Scholar] [CrossRef]
  25. Álvarez-León, E.; Henríquez, P.; Serra-Majem, L. Mediterranean diet and metabolic syndrome: A cross-sectional study in the Canary Islands. Public Health Nutr. 2006, 9, 1089–1098. [Google Scholar] [CrossRef] [PubMed]
  26. Martínez-González, M.A.; Salas-Salvadó, J.; Estruch, R.; Corella, D.; Fitó, M.; Ros, E. Benefits of the Mediterranean Diet: Insights from the PREDIMED Study. Prog. Cardiovasc. Dis. 2015, 58, 50–60. [Google Scholar] [CrossRef] [PubMed]
  27. Ferro-Luzzi, A.; Branca, F. Mediterranean diet, Italian-style: Prototype of a healthy diet. Am. J. Clin. Nutr. 1995, 61, 1338S–1345S. [Google Scholar] [CrossRef] [PubMed]
  28. Sáez-Almendros, S.; Obrador, B.; Bach-Faig, A.; Serra-Majem, L. Environmental footprints of Mediterranean versus Western dietary patterns: Beyond the health benefits of the Mediterranean diet. Environ. Health 2013, 12, 118. [Google Scholar] [CrossRef] [PubMed]
  29. Serra Majem, L.; Cabrera León, A.; Sierra López, A. Conclusions of the Canary Islands nutrition survey (1997–1998). Foundations for a nutrition policy in Canary Islands. Arch. Latinoam. Nutr. 2000, 50, 62–70. [Google Scholar] [PubMed]
  30. Pearce, P.L. From culture shock and culture arrogance to culture exchange: Ideas towards sustainable socio-cultural tourism1. J. Sustain. Tour. 1995, 3, 143–154. [Google Scholar] [CrossRef]
  31. Instituto Canario de Estadística Encuesta de Salud de Canarias 2009 Metodología. Available online: http://www.gobiernodecanarias.org/opencms8/export/sites/istac/galerias/documentos/C00035A/ESC_2009_Metodologia.pdf (accessed on 5 November 2017).
  32. Instituto Canario de Estadística Encuesta de Salud de Canarias 2015 Metodología. Available online: http://www.gobiernodecanarias.org/istac/galerias/documentos/C00035A/ESC-2015-Metodologia.pdf (accessed on 5 November 2017).
  33. Instituto Canario de Estadística Encuesta sobre el Gasto Turístico Metodología. Available online: http://www.gobiernodecanarias.org/istac/galerias/documentos/C00028A/Metodologia_EGT_2009.pdf (accessed on 5 November 2017).
  34. Hox, J.J. Applied Multi-level Analysis, 2nd ed.; TT-Publikaties: Amsterdam, The Netherlands, 1995. [Google Scholar]
  35. Serra-Majem, L.; Bes-Rastrollo, M.; Román-Viñas, B.; Pfrimer, K.; Sánchez-Villegas, A.; Martínez-González, M.A. Dietary patterns and nutritional adequacy in a Mediterranean country. Br. J. Nutr. 2009, 101, S21–S28. [Google Scholar] [CrossRef] [PubMed]
  36. Bamia, C. Dietary patterns in association to cancer incidence and survival: Concept, current evidence, and suggestions for future research. Eur. J. Clin. Nutr. 2018, 72, 818–825. [Google Scholar] [CrossRef] [PubMed]
  37. Swinburn, B.; Sacks, G.; Vandevijvere, S.; Kumanyika, S.; Lobstein, T.; Neal, B.; Barquera, S.; Friel, S.; Hawkes, C.; Kelly, B.; et al. INFORMAS (International network for food and obesity/non-communicable diseases research, monitoring and action support): Overview and key principles. Obes. Rev. 2013, 14, 1–12. [Google Scholar] [CrossRef] [PubMed]
  38. Story, M.; Kaphingst, K.M.; Robinson-O’Brien, R.; Glanz, K. Creating healthy food and eating environments: Policy and environmental approaches. Annu. Rev. Public Health 2008, 29, 253–272. [Google Scholar] [CrossRef] [PubMed]
  39. Cauchi, D.; Rutter, H.; Knai, C. An obesogenic island in the Mediterranean: Mapping potential drivers of obesity in Malta. Public Health Nutr. 2015, 18, 3211–3223. [Google Scholar] [CrossRef] [PubMed]
  40. Stok, F.M.; Hoffmann, S.; Volkert, D.; Boeing, H.; Ensenauer, R.; Stelmach-Mardas, M.; Kiesswetter, E.; Weber, A.; Rohm, H.; Lien, N.; et al. The DONE framework: Creation, evaluation, and updating of an interdisciplinary, dynamic framework 2.0 of determinants of nutrition and eating. PLoS ONE 2017, 12, e0171077. [Google Scholar] [CrossRef] [PubMed]
  41. Bach-Faig, A.; Fuentes-Bol, C.; Ramos, D.; Carrasco, J.L.; Roman, B.; Bertomeu, I.F.; Cristià, E.; Geleva, D.; Serra-Majem, L. The Mediterranean diet in Spain: Adherence trends during the past two decades using the Mediterranean Adequacy Index. Public Health Nutr. 2011, 14, 622–628. [Google Scholar] [CrossRef] [PubMed]
  42. Tong, T.Y.N.; Imamura, F.; Monsivais, P.; Brage, S.; Griffin, S.J.; Wareham, N.J.; Forouhi, N.G. Dietary cost associated with adherence to the Mediterranean diet, and its variation by socio-economic factors in the UK Fenland Study. Br. J. Nutr. 2018, 119, 685–694. [Google Scholar] [CrossRef] [PubMed]
  43. Ferreira-Pêgo, C.; Babio, N.; Salas-Salvadó, J. A higher Mediterranean diet adherence and exercise practice are associated with a healthier drinking profile in a healthy Spanish adult population. Eur. J. Nutr. 2017, 56, 739–748. [Google Scholar] [CrossRef] [PubMed]
  44. Grosso, G.; Marventano, S.; Giorgianni, G.; Raciti, T.; Galvano, F.; Mistretta, A. Mediterranean diet adherence rates in Sicily, southern Italy. Public Health Nutr. 2014, 17, 2001–2009. [Google Scholar] [CrossRef] [PubMed]
  45. Sánchez-Villegas, A.; Martínez, J.A.; De Irala, J.; Martínez-González, M.A. Determinants of the adherence to an ‘a priori’ defined Mediterranean dietary pattern. Eur. J. Nutr. 2002, 41, 249–257. [Google Scholar] [CrossRef] [PubMed]
  46. Sánchez-Villegas, A.; Delgado-Rodríguez, M.; Martínez-González, M.Á.; de Irala-Estévez, J. Gender, age, socio-demographic and lifestyle factors associated with major dietary patterns in the Spanish Project SUN (Seguimiento Universidad de Navarra). Eur. J. Clin. Nutr. 2003, 57, 285–292. [Google Scholar] [CrossRef] [PubMed][Green Version]
  47. Costacou, T.; Bamia, C.; Ferrari, P.; Riboli, E.; Trichopoulos, D.; Trichopoulou, A. Tracing the Mediterranean diet through principal components and cluster analyses in the Greek population. Eur. J. Clin. Nutr. 2003, 57, 1378–1385. [Google Scholar] [CrossRef] [PubMed][Green Version]
  48. Marventano, S.; Godos, J.; Platania, A.; Galvano, F.; Mistretta, A.; Grosso, G. Mediterranean diet adherence in the Mediterranean healthy eating, aging and lifestyle (MEAL) study cohort. Int. J. Food Sci. Nutr. 2018, 69, 100–107. [Google Scholar] [CrossRef] [PubMed]
  49. Bonaccio, M.; Di Castelnuovo, A.; Bonanni, A.; Costanzo, S.; De Lucia, F.; Persichillo, M.; Zito, F.; Donati, M.B.; de Gaetano, G.; Iacoviello, L. Decline of the Mediterranean diet at a time of economic crisis. Results from the Moli-sani study. Nutr. Metab. Cardiovasc. Dis. 2014, 24, 853–860. [Google Scholar] [CrossRef] [PubMed]
  50. Papadaki, A.; Wood, L.; Sebire, S.J.; Jago, R. Adherence to the Mediterranean diet among employees in South West England: Formative research to inform a web-based, work-place nutrition intervention. Prev. Med. Rep. 2015, 2, 223–228. [Google Scholar] [CrossRef] [PubMed]
  51. Henríquez Sánchez, P.; Ruano, C.; de Irala, J.; Ruiz-Canela, M.; Martínez-González, M.A.; Sánchez-Villegas, A. Adherence to the Mediterranean diet and quality of life in the SUN Project. Eur. J. Clin. Nutr. 2012, 66, 360–368. [Google Scholar] [CrossRef] [PubMed]
  52. Muñoz, M.-A.; Fíto, M.; Marrugat, J.; Covas, M.-I.; Schröder, H. Adherence to the Mediterranean diet is associated with better mental and physical health. Br. J. Nutr. 2009, 101, 1821. [Google Scholar] [CrossRef] [PubMed]
  53. Da Silva, R.; Bach-Faig, A.; Raidó Quintana, B.; Buckland, G.; Vaz de Almeida, M.D.; Serra-Majem, L. Worldwide variation of adherence to the Mediterranean diet, in 1961–1965 and 2000–2003. Public Health Nutr. 2009, 12, 1676–1684. [Google Scholar] [CrossRef] [PubMed]
  54. Fallaize, R.; Livingstone, K.; Celis-Morales, C.; Macready, A.; San-Cristobal, R.; Navas-Carretero, S.; Marsaux, C.; O’Donovan, C.; Kolossa, S.; Moschonis, G.; et al. Association between Diet-Quality Scores, Adiposity, Total Cholesterol and Markers of Nutritional Status in European Adults: Findings from the Food4Me Study. Nutrients 2018, 10, 49. [Google Scholar] [CrossRef] [PubMed]
  55. Gutiérrez-Fisac, J.L.; Guallar-Castillón, P.; León-Muñoz, L.M.; Graciani, A.; Banegas, J.R.; Rodríguez-Artalejo, F. Prevalence of general and abdominal obesity in the adult population of Spain, 2008–2010: The ENRICA study. Obes. Rev. 2012, 13, 388–392. [Google Scholar] [CrossRef] [PubMed]
  56. Katsarou, A.; Tyrovolas, S.; Psaltopoulou, T.; Zeimbekis, A.; Tsakountakis, N.; Bountziouka, V.; Gotsis, E.; Metallinos, G.; Polychronopoulos, E.; Lionis, C.; et al. Socio-economic status, place of residence and dietary habits among the elderly: The Mediterranean islands study. Public Health Nutr. 2010, 13, 1614–1621. [Google Scholar] [CrossRef] [PubMed]
  57. Vlismas, K.; Stavrinos, V.; Panagiotakos, D.B. Socio-economic status, dietary habits and health-related outcomes in various parts of the world: A review. Cent. Eur. J. Public Health 2009, 17, 55–63. [Google Scholar] [CrossRef] [PubMed]
  58. Bonaccio, M.; Bonanni, A.E.; Di Castelnuovo, A.; De Lucia, F.; Donati, M.B.; de Gaetano, G.; Iacoviello, L. Low income is associated with poor adherence to a Mediterranean diet and a higher prevalence of obesity: Cross-sectional results from the Moli-sani study. BMJ Open 2012, 2, e001685. [Google Scholar] [CrossRef] [PubMed]
  59. Bessiere, J.; Tibere, L. Traditional food and tourism: French tourist experience and food heritage in rural spaces. J.Sci. Food Agric. 2013, 93, 3420–3425. [Google Scholar] [CrossRef] [PubMed]
  60. López-Valcárcel, B.G.; Serra-Majem, L.; Barber-Pérez, P.; Pinilla-Domínguez, J.; Rodríguez-Caro, A.; Rodríguez-Feijoo, S.; Rodríguez-Mireles, S. Alimentación y Salud. Distribución, Mercados y Precios. Análisis Detallado de Pescado, Frutas, Hortalizas y Legumbres (PFHL); Technical Report; University of Las Palmas de Gran Canaria: Las Palmas, Spain, 2018. [Google Scholar]
  61. Bach, A.; Serra-Majem, L.; Carrasco, J.L.; Roman, B.; Ngo, J.; Bertomeu, I.; Obrador, B. The use of indexes evaluating the adherence to the Mediterranean diet in epidemiological studies: A review. Public Health Nutr. 2006, 9, 132–146. [Google Scholar] [CrossRef] [PubMed]
  62. Vyncke, K.; Cruz Fernandez, E.; Fajó-Pascual, M.; Cuenca-García, M.; De Keyzer, W.; Gonzalez-Gross, M.; Moreno, L.A.; Beghin, L.; Breidenassel, C.; Kersting, M.; et al. Validation of the Diet Quality Index for Adolescents by comparison with biomarkers, nutrient and food intakes: The HELENA study. Br. J. Nutr. 2013, 109, 2067–2078. [Google Scholar] [CrossRef] [PubMed]
  63. Schröder, H.; Fïto, M.; Covas, M.I. Association of fast food consumption with energy intake, diet quality, body mass index and the risk of obesity in a representative Mediterranean population. Br. J. Nutr. 2007, 98, 1274–1280. [Google Scholar] [CrossRef] [PubMed]
Table 1. Characteristics of participants according to year of the survey.
Table 1. Characteristics of participants according to year of the survey.
Year of the Survey2009 (n = 4160)2015 (n = 4143)
Age, yearsmean (SD)47.63(17.25)50.79(16.76)
median (IQR)45.00(35.00–61.00)50.00(38.00–64.00)
Sex, womenn (%)2436(58.56)2343(56.55)
Place of birth, Spainn (%)3642(87.55)3776(91.14)
Civil statusn (%)
Single 1093(26.27)1225(29.57)
Married 2014(48.41)1803(43.52)
Widowed 376(9.04)448(10.81)
Divorced/Separated 387(9.30)480(11.59)
Registered partnership 290(6.97)187(4.51)
Education leveln (%)
Primary education 1442(34.66)1195(28.96)
Lower secondary education 1012(24.33)974(23.60)
Upper secondary education 1070(25.72)1236(29.95)
Tertiary education 636(15.29)722(17.49)
BMI, kg/m2mean (SD)26.20(4.83)26.21(4.71)
median (IQR)25.53(22.84–35.09)25.56(23.01–28.73)
VAS-HRQLmean (SD)72.90(20.57)72.90(20.22)
median (IQR)80.00(60.00–90.00)80.00(60.00–90.00)
Smoking statusn (%)
Non-smoker 2309(55.85)2352(57.93)
Former smoker 678(16.40)683(16.82)
Occasional smoker 95(2.30)104(2.56)
Light smoker 228(5.52)242(5.96)
Moderate smoker 669(16.18)569(14.01)
Heavy smoker 155(3.75)110(2.71)
Alcohol consumption, non-abstinentn (%)2391(57.48)2464(59.47)
Labour market statusn (%)
Active worker 1697(40.79)1634(39.53)
Unemployed 868(20.87)892(21.58)
Early retired/Retired 920(22.12)1097(26.54)
Homemaker 431(10.36)267(6.46)
Other 244(5.87)244(5.90)
Smoking status was classified as: non-smoker; former smoker; occasional smoker (<1 cigarette/day); light smoker (<10 cigarettes/day); moderate smoker (10–20 cigarettes/day); heavy smoker (>20 cigarettes/day). Abbreviations: SD, standard deviation; IQR, interquartile range; BMI, Body Mass Index; VAS-HRQL, Visual Analogue Scale-Health Related Quality of Life.
Table 2. Tourist overnight stays (thousands) and percent change in the rate between 2009 and 2015 by nationality and area of destination.
Table 2. Tourist overnight stays (thousands) and percent change in the rate between 2009 and 2015 by nationality and area of destination.
British TouristsGerman TouristsSpanish TouristsOther Tourists
20092015Variation20092015Variation20092015Variation20092015Variation
nn%nn%nn%nn%
Area 12492.744152.5466.596142.387570.6123.25952.10844.11−11.342569.894682.5582.21
Area 211.7397.59732.2360.74111.4983.55157.38469.62198.4053.90262.98387.89
Area 361.78310.49402.59211.531439.55580.54883.971526.0972.64491.771673.80240.36
Area 43773.804463.8018.286416.246634.003.391521.971855.2721.9010686.5815211.4242.34
Area 55656.739644.4170.492695.613030.5912.431707.951674.11−1.983274.675840.9678.37
Area 6147.03232.5858.19690.23756.999.67364.51329.52−9.60362.21419.7815.89
Area 7514.42535.904.181847.511859.730.661753.991256.14−28.381116.541516.4235.81
Area 891.79422.26360.02132.04177.6834.57389.25420.658.07158.72351.52121.47
Area 98909.6712451.6439.753107.743329.047.122075.201856.54−10.548666.6611591.6933.75
Total21659.6932311.2049.1821304.0224909.6816.929806.3110232.064.3427380.9441551.1251.75
Area 1, Fuerteventura. Area 2, North Gran Canaria. Area 3, Metropolitan Gran Canaria. Area 4, South Gran Canaria. Area 5, Lanzarote. Area 6, La Palma. Area 7, North Tenerife. Area 8, Metropolitan Tenerife. Area 9, South Tenerife.
Table 3. Association between Mediterranean diet score (MD-score) and tourist pressure by nationality and characteristics of participants.
Table 3. Association between Mediterranean diet score (MD-score) and tourist pressure by nationality and characteristics of participants.
MD-Score n = 8303
β95% CIp
Tourist pressure *
British tourists−0.0064−0.0112−0.00150.010
German tourists0.00920.00030.01810.042
Other tourists−0.0001−0.00470.00450.964
Cohort, 2015−0.0214−0.0365−0.00630.005
Sex, women0.25540.17680.3340<0.001
Age, years
16–24.9Ref.Ref.Ref.
25–34.90.35150.17000.5330<0.001
35–49.90.78380.60620.9615<0.001
50–64.91.33371.14501.5223<0.001
65–79.91.53151.31191.7512<0.001
≥801.39101.12361.6585<0.001
Civil status
SingleRef.Ref.Ref.
Married0.13270.03070.23460.011
Widowed0.0733−0.09110.23770.382
Divorced/Separated0.0227−0.11710.16250.750
Registered partnership−0.1217−0.28760.04420.151
Education level
Primary educationRef.Ref.Ref.
Lower secondary education−0.1136−0.2181-0.00900.033
Upper secondary education0.11760.01180.22330.029
Tertiary education0.33350.21190.4551<0.001
BMI
<18.5 (kg/m2)−0.1631−0.41320.08710.201
18.5–24.9 (kg/m2)Ref.Ref.Ref.
25–29.9 (kg/m2)−0.0995−0.1812−0.01770.017
30–34.9 (kg/m2)−0.1634−0.2754−0.05140.004
35–39.9 (kg/m2)−0.2135−0.4133−0.01370.036
≥40 (kg/m2)−0.2936−0.61100.02370.070
VAS-HRQL0.00260.00070.00450.007
Smoking status
Non-smokerRef.Ref.Ref.
Former smoker0.0556−0.04650.15770.286
Occasional smoker−0.1073−0.24230.02760.119
Light smoker−0.4052−0.5114−0.2991<0.001
Heavy smoker−0.6068−0.8135−0.4001<0.001
Alcohol consumption, non-abstinent−0.2094−0.2854−0.1334<0.001
Labour market status
Active workerRef.Ref.Ref.
Unemployed0.0428−0.05400.13950.386
Early retired/Retired0.31640.18240.4505<0.001
Homemaker0.22480.07280.37680.004
Other0.24340.05960.42720.009
Tourist pressure *, Overnight stays/100,000. Smoking status was classified as: non-smoker; former smoker; occasional smoker (<1 cigarette/day); light smoker (<10 cigarettes/day); moderate smoker (10–20 cigarettes/day); heavy smoker (> 20 cigarettes/day). Abbreviations: Ref., Reference category; BMI, Body Mass Index; VAS-HRQL, Visual Analogue Scale-Health Related Quality of Life.

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Rodríguez-Mireles, S.; López-Valcárcel, B.G.; Serra-Majem, L.; Hernández-Yumar, A.; Barber-Pérez, P.; Pinilla-Domínguez, J.; Rodríguez-Feijoo, S.; Rodríguez-Caro, A. Effect of Tourism Pressure on the Mediterranean Diet Pattern. Nutrients 2018, 10, 1338. https://doi.org/10.3390/nu10101338

AMA Style

Rodríguez-Mireles S, López-Valcárcel BG, Serra-Majem L, Hernández-Yumar A, Barber-Pérez P, Pinilla-Domínguez J, Rodríguez-Feijoo S, Rodríguez-Caro A. Effect of Tourism Pressure on the Mediterranean Diet Pattern. Nutrients. 2018; 10(10):1338. https://doi.org/10.3390/nu10101338

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Rodríguez-Mireles, Silvia, Beatriz G. López-Valcárcel, Lluís Serra-Majem, Aránzazu Hernández-Yumar, Patricia Barber-Pérez, Jaime Pinilla-Domínguez, Santiago Rodríguez-Feijoo, and Alejandro Rodríguez-Caro. 2018. "Effect of Tourism Pressure on the Mediterranean Diet Pattern" Nutrients 10, no. 10: 1338. https://doi.org/10.3390/nu10101338

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