Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-22T13:57:54.779Z Has data issue: false hasContentIssue false

Fruit and vegetable consumption among migrants in Switzerland

Published online by Cambridge University Press:  14 May 2012

Thomas Volken*
Affiliation:
School of Health Professions, Zurich University of Applied Sciences, Technikumstrasse 71, POB 8401, Winterthur, Switzerland
Peter Rüesch
Affiliation:
School of Health Professions, Zurich University of Applied Sciences, Technikumstrasse 71, POB 8401, Winterthur, Switzerland
Jürg Guggisberg
Affiliation:
Büro für Arbeits- und Sozialpolitische Studien BASS, Bern, Switzerland
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Objective

To assess the relative risk of low daily fruit and vegetable consumption for six large migrant groups in Switzerland.

Design

Cross-sectional health survey carried out 2007 (Swiss Health Survey) and 2010 (Swiss Migrant Health Survey) in Switzerland. Multinomial logistic regression models were used to estimate relative risk rates (RRR) of migrants relative to Swiss nationals.

Setting

Data obtained from representative samples of Swiss and foreign nationals living in Switzerland.

Subjects

A random sample (n 14637) of the Portuguese, German, Italian, Turkish, Serbian, Kosovan and Swiss permanent resident adult population (17–64 years old) was interviewed.

Results

The proportion of participants who adhered to the recommended fruit and vegetable consumption was below one-third in all study populations. Compared with Swiss nationals, the relative risk of low daily fruit and vegetable intake relative to recommended intake was higher in Turkish nationals (RRR = 2·92, 95 % CI 1·91, 4·48; P = 0·0000) and Kosovan nationals (RRR = 4·76, 95 % CI 3·01, 7·55; P = 0·0000). The respective relative risks of Portuguese, Serbian, German and Italian nationals were not significantly different from the Swiss reference group.

Conclusions

Initiatives for the promotion of fruit and vegetable consumption should continue to address the population at large. At the same time, programmes that are tailored to the specific needs of migrants from Turkey and Kosovo should be considered.

Type
Special groups
Copyright
Copyright © The Authors 2012

Non-communicable diseases, especially CVD, cancer, obesity and type 2 diabetes mellitus, currently kill more people every year than any other cause of death. Fruit and vegetables are an important component of a healthy diet and, if consumed daily in sufficient amounts, could help prevent major diseases such as CVD and certain cancers(1).

Several studies have found associations between a higher intake of fruit and vegetables and a reduced risk of CVD mortality(Reference Crowe, Roddam and Key2Reference Zhang, Shu and Xiang8). Similarly, a higher daily intake of fruit and vegetables is associated with a reduced risk of some types of cancer(Reference Zhang, Ho and Fu9Reference Bravi, Polesel and Bosetti14).

In 2001, the Swiss Cancer League, supported by the Swiss Federal Office of Public Health and Health Promotion Switzerland started an ongoing prevention campaign ‘Five servings of fruit and vegetables a day’ in order to promote an adequate daily consumption of fruit and vegetables among the population of Switzerland. In 2007, 29·3 % of the Swiss population aged 15 years and older reported to consume the recommended five portions daily(Reference Lamprecht and Stamm15). Comparably little is known about the factors that are associated with fruit and vegetable consumption in Switzerland. There is some evidence that women and older age cohorts have a higher propensity to consume fruit and vegetables compared with men and younger age cohorts(Reference Lamprecht and Stamm15, Reference Eichholzer, Bernasconi and Jordan16). To our knowledge, no population-based study so far has assessed the fruit and vegetable consumption of adult migrants in Switzerland, despite the fact that migrants accounted for 1·7 million people or 22 % of the permanent resident population of Switzerland in 2009(17). Migrants are an important group and prevention campaigns may need to be tailored to specific migrant groups and their needs. A large body of literature on migration and health suggests that cultural patterns shape physical activity, body images, dietary intake and food preferences(Reference Caperchione, Kolt and Mummery18Reference Nicolaou, Doak and van Dam24). However, the evidence on dietary patterns is mixed(Reference Landman and Cruickshank25). While some studies report that migrant status is associated with a low daily intake of fruit and vegetables or adverse dietary patterns(Reference Mejean, Deschamps and Bellin-Lestienne26, Reference Labree, van de Mheen and Rutten27), others report that migrant status is associated with a higher daily intake or beneficial dietary patterns compared with the native population of the host country(Reference Kumar, Yu and Akinremi28Reference Satia-Abouta, Patterson and Kristal32). Given that the mixed evidence partially reflects culture-specific dietary practices as well as acculturation to the dietary practices of the host countries, we may expect different patterns of fruit and vegetable consumption among migrants in Switzerland as well. The aim of the present study was to assess the risk of low daily intake of fruit and vegetables among six large migrant groups in Switzerland and thereby serve as a guide for effective fruit and vegetable promotion interventions.

Methods

Study design

The study is a population-based cross-sectional health survey carried out in 2007 and 2010 in Switzerland. Ethical approval for the study was not required.

Study population and data

Data from the 2010 Swiss Migrant Health Survey (SMHS) and the 2007 Swiss Health Survey (SHS) were obtained from the Swiss Federal Office of Public Health (www.bag.admin.ch). The SMHS is a cross-sectional, population-based telephone survey which intends to monitor health trends in a representative sample of migrants and has been carried out in 2004 and 2010 so far. Due to economic constraints, the SMHS is limited to a selected number of nationalities. The core study population in 2010 comprised permanent residents from Portugal, Turkey, Serbia and Kosovo (n 1800). Participants aged 17–74 years were chosen by stratified random sampling (gender, country of birth, duration of stay) from the database of the central immigration information system. The computer-aided telephone interviews were carried out in Portuguese, Turkish, Serbian, Albanian, German and French. Data on Swiss, German and Italian nationals from the 2007 SHS were pooled with the 2010 SMHS data. The SHS was first conducted in 1992 and is repeated every five years. The 2007 sample included over 19 000 participants aged 15 years or older. Participants were randomly selected within private households and computer-aided telephone interviews were conducted in German, French and Italian. People who did not speak any of these languages or people who had insufficient language skills were excluded from the SHS.

The pooled sample represents 58·2 % of the migrant population as well as nationals from Switzerland. Of the 1·7 million migrants in Switzerland, 17·0 % are Italian, 14·9 % are German, 12·0 % are Portuguese, 5·4 % are French, 3·6 % are Spanish, 6·9 % are Serbians, 4·1 % are Turkish and 3·3 % are Kosovan(33). Migrants from France and Spain were not included because of their small sample size in the SHS. Since all interviews of participants in the pooled sample were conducted in their respective native language, selection bias due to insufficient language skills has been mitigated; i.e. the selection process is less likely to favour migrants who are well-integrated, well-educated and have been living in Switzerland for a long period of time.

For the purposes of the present study, the initial pooled sample was further narrowed down to include only those aged 17–64 years because only a few migrants in the SMHS sample were over 64 years old. The total sample size amounts to 14 637. The sample size by nationality and further characteristics of the pooled SMHS and SHS sample is shown in Table 1.

Table 1 Frequency distribution and central tendency for variables in the sample of participants aged 17–64 years by nationality (2010 Swiss Migrant Health Survey 2010 and 2007 Swiss Health Survey)Footnote *

* Data refer to the number of participants and percentage or arithmetic mean and standard deviation within nationality.

One serving corresponds to approximately 120 g. In the case of juice, one serving corresponds to a medium size glass, approximately 150 ml.

Classification according to the Swiss Federal Statistical Office(Reference Schuler, Dessemontet and Joye61). Urban areas include isolated cities (≥10 000 inhabitants) and urban agglomerations (≥20 000 inhabitants).

Target outcome, predictor and covariates

Daily fruit and vegetable intake (FVI), the target outcome of the study, was derived from self-reported data. Participants were asked to estimate their average daily consumption of fruit by answering the question: ‘How many servings of fruit and fruit juice do you have on average per day? One serving corresponds to the size of your fist (approximately 120 g). In the case of fruit juice, one serving corresponds to a medium size glass’. Similarly, a question relating to the average consumption of vegetables was asked: ‘How many servings of vegetable and vegetable juice (without potatoes or sweet corn) do you have on average per day? One serving corresponds to the size of your fist (approximately 120 g). In the case of vegetable juice, one serving corresponds to a medium size glass’. The choice of answers included: (i) ‘none’; (ii) ‘less than 1 serving per day’; (iii) ‘1–2 servings per day’; (iv) ‘3–4 servings per day’; and (v) ‘5 or more servings per day’. FVI was calculated by adding up the self-reported frequency of fruit and vegetable consumptionFootnote *(Reference Lamprecht and Stamm15). Participants were then assigned to the following three categories: (i) recommended FVI (FVI ≥ 5 servings of fruit and vegetables/d)Footnote ; (ii) medium FVI (2 ≤ FVI ≤ 4); and (iii) low FVI (0 ≤ FVI < 2). Although these questions have been used before(Reference Lamprecht and Stamm15, Reference Eichholzer, Bernasconi and Jordan16, Reference Zwahlen, Keel and Zybach34), the construct and content validity of this instrument have not been formally assessed so far. We conducted a linguistic validation process that included a conceptual analysis of all original instruments in collaboration with the translators, as well as forward and backward translations and a review of the backward translation.

For the primary predictor, the country of origin, the following were considered: Portugal, Turkey, Serbia, Kosovo, Germany, Italy and Switzerland. Double citizens who acquired Swiss nationality through naturalization were considered Swiss. Covariates included: age, gender, socio-economic status (SES) and dwelling zone (rural/urban). SES comprised three indicators: education (basic, secondary and university), employment (economically active, no/yes) and housing situation (rooms per person).

Missing data

Missing data were generally rare on all variables. For the predictor and two covariates, no data were missing and for the remaining covariates 0·5 % or less of the data were missing within each nationality. Missing data on FVI, the dependent variable, amounted to 2·6 % and there were no substantial differences in the amount of missing data between nationalities. Overall, 3 % of the data were missing. Our analysis of missing-value patterns also revealed no systematic relationships between FVI and the predictor or the covariates. We therefore assumed that the data were missing completely at random and applied list-wise deletion which gives valid inferences under this assumption(Reference Allison35).

Weighting

The original expansion weights of the SMHS and SHS were used for all population estimates. The weights take into account the different sampling strategies which have been used to sample migrants and Swiss nationals and they allow correct estimates of population parameters for migrants and Swiss nationals.

Statistical analysis

We used the STATA statistical software package version 11·2 for all statistical analyses. We report relative risk ratios (RRR) for different nationalities from multinomial logistic regression models (mlogit) adjusting for age, gender, SES and dwelling zone. We also report corresponding 95 % confidence intervals and P values. To incorporate information on the appropriate weights and sampling units for correct variance estimation, all statistical analyses were carried out using STATA's command for complex surveys (svy prefix). Statistical significance was established at P ≤ 0·05.

Results

We found different prevalence rates of low, medium and recommended FVI between migrants and nationals of Switzerland (Table 2): 30·3 % (95 % CI 29·2, 31·3) of Swiss nationals adhered to the recommended FVI. The respective prevalence was significantly lower in nationals from Turkey (22·9 %; 95 % CI 18·2, 28·2; P = 0·0044), Serbia (22·4 %; 95 % CI 17·4, 28·2; P = 0·0046), Kosovo (18·3 %; 95 % CI 13·7, 24·0; P = 0·0000) and Italy (23·5 %; 95 % CI 18·5, 29·4; P = 0·0166). In contrast, the prevalence of recommended FVI of German (30·4 %; 95 % CI 24·5, 37·1; P = 0·9661) and Portuguese (28·2 %; 95 % CI 23·7, 33·2; P = 0·4029) nationals did not differ significantly from that of Swiss nationals.

Table 2 Population estimates of fruit and vegetable consumption of participants aged 17–64 years by nationality (2010 Swiss Migrant Health Survey and 2007 Swiss Health Survey 2007)Footnote *

* Data were weighted using the weights of the Swiss Migrant Health Survey/Swiss Health Survey.

One serving corresponds to approximately 120 g. In the case of juice, one serving corresponds to a medium size glass, approximately 150 ml.

Estimated number of participants in the population.

The proportion of Swiss nationals with medium FVI amounted to 62·6 % (95 % CI 61·5, 63·7). The respective proportion was found to be lower in Turkish nationals (52·9 %; 95 % CI 47·0, 58·8; P = 0·0015) and nationals from Kosovo (49·4 %; 95 % CI 42·8, 56·0; P = 0·0001), whereas the proportion of Swiss nationals with medium FVI was not different from nationals from Portugal (62·7 %; 95 % CI 57·4, 67·7; P = 0·9832), Serbia (67·1 %; 95 % CI 60·6, 73·1; P = 0·1637), Germany (63·6 %; 95 % CI 56·9, 69·8; P = 0·7768) and Italy (66·5 %; 95 % CI 60·1, 72·3; P = 0·2236).

Low FVI was more common in nationals from Turkey (24·2 %; 95 % CI 19·6, 29·5; P = 0·0000) and Kosovo (32·3 %; 95 % CI 26·5, 38·8; P = 0·0000) than in Swiss nationals (7·1 %; 95 % CI 6·5, 7·7). In contrast, the proportion of Swiss nationals with low FVI did not differ from Portuguese (9·1 %; 95 % CI 6·4, 12·9; P = 0·2211), Serbian (10·5 %; 95 % CI 7·1, 15·3; P = 0·1052), German (6·0 %; 95 % CI 3·8, 9·3; P = 0·4339) and Italian (10·0 %; 95 % CI 6·9, 14·4) nationals.

Multivariate analysis adjusting for age, gender, SES and dwelling zone generally confirmed these initial results (Table 3). Compared with Swiss nationals, the relative risk of low FVI v. recommended FVI was higher in Turkish nationals (RRR = 2·92, 95 % CI 1·91, 4·48; P = 0·0000) and Kosovo nationals (RRR = 4·76, 95 % CI 3·01, 7·55; P = 0·0000). The respective relative risks of Portuguese (RRR = 0·70, 95 % CI 0·42, 1·17; P = 0·1750), Serbian (RRR = 1·42, 95 % CI 0·82, 2·46; P = 0·2140), German (RRR = 0·87, 95 % CI 0·51, 1·50; P = 0·6180) and Italian (RRR = 1·32, 95 % CI 0·80, 2·18; P = 0·2740) nationals were not significantly different from the Swiss reference group.

Table 3 Multinomial regression analysis of factors associated with daily fruit and vegetable consumption, participants aged 17–64 years (2010 Swiss Migrant Health Survey and 2007 Swiss Health Survey)Footnote *

RRR, relative risk ratio; ref., referent category.

* Data were weighted using the weights of the Swiss Migrant Health Survey/Swiss Health Survey.

One serving corresponds to approximately 120 g. In the case of juice, one serving corresponds to a medium size glass, approximately 150 ml.

Classification according to the Swiss Federal Statistical Office(Reference Schuler, Dessemontet and Joye61). Urban areas include isolated cities (≥10 000 inhabitants) and urban agglomerations (≥20 000 inhabitants).

Migrants from different nationalities and Swiss nationals showed similar relative risks of medium FVI v. recommended FVI; none of the nation-specific RRR attained statistical significance.

The relative risk of low FVI decreased with age (RRR = 0·98, 95 % CI 0·98, 0·99; P = 0·0000). That is, older participants were more likely to consume the recommended five portions daily. Similarly, women were more likely to eat greater amounts of fruits and vegetables than men. Correspondingly, women exhibited a lower risk for low or medium FVI v. recommended FVI (RRR = 0·22, 95 % CI 0·18, 0·26; P = 0·0000 and RRR = 0·41, 95 % CI 0·37, 0·45; P = 0·0000, respectively). Also, participants with secondary education or a university degree were more likely to consume greater amounts of fruits and vegetables than those with a basic education (secondary education: RRR = 0·47, 95 % CI 0·35, 0·62; P = 0·0000 and RRR = 0·75, 95 % CI 0·62, 0·90; P = 0·0020 for low and medium FVI, respectively, v. recommended FVI; university degree: RRR = 0·27, 95 % CI 0·19, 0·37; P = 0·0000 and RRR = 0·56, 95 % CI 0·46, 0·69; P = 0·0000 for low and medium FVI, respectively, v. recommended FVI). Economically active participants were slightly more likely to have a higher FVI than those who were not economically active (medium FVI: RRR = 1·19, 95 % CI 1·05, 1·35; P = 0·0050; low FVI: NS). Finally, neither housing situation nor the specific dwelling zone was significantly associated with low or medium FVI v. recommended FVI.

Several studies show that migrants often adopt the dietary practices of the host country(Reference Neuhouser, Thompson and Coronado30, Reference Sofianou, Fung and Tucker36Reference Gregory-Mercado, Staten and Ranger-Moore38). Consequently, fruit and vegetable consumption of migrants in Switzerland may also be influenced by dietary acculturation. In order to control for potential acculturation effects, length of time in Switzerland (years) was added as a covariate to the model previously discussed and the model was re-estimated using migrant data only. However, length of time in Switzerland had no statistically significant association with FVI (results not shown).

Discussion

So far, population-based studies on the fruit and vegetable consumption among migrants in Switzerland are rare and have been based mainly on data of the SHS(Reference Grossmann, Leventhal and Auer-Böer39). However, the SHS data have limitations with regard to the study of migrants. First, interviews are carried out only in German, French and Italian. Second, the sampling process does not include any migrant-specific characteristics, e.g. the country of origin. Consequently, the SHS data potentially favour well-integrated, well-educated and well-assimilated migrants and potentially omit vulnerable groups of migrants. Furthermore, the sample size for specific groups of migrants, e.g. Turkish migrants, tends to be very small.

To our knowledge, the present study is the first which uses the 2010 SMHS data to assess fruit and vegetable consumption among migrants and hence to use a survey that has been specially designed to collect public-health-related data on migrants in Switzerland. Since all SMHS interviews were conducted in the participants’ respective native languages, selection bias due to insufficient language skills has been mitigated.

Overall, the proportion of participants who ate five or more servings of fruit and vegetables daily was below one-third in all study groups. The highest rate of recommended FVI was little more than 30 % (German and Swiss nationals); the lowest rate amounted to little more than 18 % (Kosovo nationals). Hence, fruit and vegetable promotion initiatives should continue to address the population of Switzerland at large in order to increase fruit and vegetable consumption. Our results further suggest that some migrant groups are at particular risk of low daily fruit and vegetable consumption. For migrants from Turkey and Kosovo relative to Swiss nationals, the relative risk of low FVI v. recommended FVI was substantially higher. In contrast, the respective relative risk for German, Portuguese, Serbian and Italian nationals did not significantly differ from Swiss nationals. In sum, substantial differences in the relative risk for low FVI v. recommended FVI existed between Swiss nationals and migrants from Turkey and Kosovo, and these differences cannot be attributed to age, gender, SES or dwelling zone since we adjusted for these factors.

Previous studies reported that women and older age cohorts consume fruit and vegetables more often than men and younger age cohorts; and that participants with a higher level of education tend to consume more fruit and vegetables than those with a low level of education(Reference Lamprecht and Stamm15, Reference Eichholzer, Bernasconi and Jordan16, Reference Landman and Cruickshank25, Reference Figueiredo, Jaime and Monteiro40, Reference Dowler41). Generally, our findings correspond to the results of other studies. However, an increase in age by 1 year only reduced the relative risk for low FVI v. recommended FVI but did not significantly reduce the relative risk for low FVI v. medium FVI in our study. Secondary and university education relative to basic education substantially reduced the risk of both low FVI and medium FVI v. recommended FVI. With regard to sociodemographic factors and SES, these findings suggest that health promotion programmes should specifically address younger age cohorts, the male population and people with low education level.

Limitations of the study

The present study has several limitations inherent to all FFQ. First, reporting the amount of food consumption is a difficult cognitive task(Reference Agudo42). Although the SMHS and SHS questions on FVI included guidelines on size by specifying the weight of one serving (120 g of fruit/vegetables or one medium glass of fruit/vegetable juice), it remains unclear to what extent participants were able to adequately assess the size and weight of food consumed. Second, recalling the average servings of fruit and vegetables consumed each day is also a difficult task. Memory can be quite unreliable or may be influenced by more recent intakes of fruit and vegetables. Third, social desirability may be an issue. Participants may over-report their daily fruit and vegetable consumption because high intake is promoted as a healthy habit. Finally, questions on fruit and vegetables could be culture-sensitive(Reference MacIntyre, Venter and Vorster43), i.e. the concepts of fruit and vegetables may be different or there may be systematic covariations of cultural background and the potential sources of bias mentioned above. More specifically, fruit and vegetables in mixed dishes could not have been considered by some individuals. The European Prospective Investigation into Cancer and Nutrition (EPIC) showed that the intake of vegetables from mixed vegetable dishes varies substantially by country (12–54 %)(Reference Agudo42, Reference Agudo, Slimani and Ocke44) and a review of brief fruit and vegetable surveys concluded that inclusion of the consumption of mixed vegetable dishes may enhance the validity of the intruments(Reference Kim and Holowaty45). Several validation studies came to the conclusion that FFQ tend to overestimate the mean intake as compared with repeated 24 h dietary recalls, which served as the reference method for assessing intake(Reference Ocke, Bueno-de-Mesquita and Goddijn46, Reference Pisani, Faggiano and Krogh47). These potential biases suggest that the present results should be interpreted with caution. However, although FFQ may be affected by scaling biases and random error when estimating absolute FVI, they seem to be valid as means of ranking participants by level of FVI. Finally, it is also plausible that mixed dishes, where the major components are fruit or vegetables, are considered when participants report their consumption in FFQ(Reference Agudo42).

Potential interventions

Eating behaviour is highly complex and has been described as resulting from the interplay of individual motivation, ability and environmental factors(Reference Brug48). So far, the reasons why Turks and Kosovans have a higher risk of low FVI are unclear and more research is needed. However, we assume that limited access to healthy food in general is not an issue in Switzerland (physical environment). A dense network of supermarkets and local grocers offers fresh fruit and vegetables at reasonable prices. It is also well known that energy-dense diets are associated with lower diet costs(Reference Darmon, Briend and Drewnowski49, Reference Dibsdall, Lambert and Bobbin50). But fruit and vegetables are generally affordable for those with small household budgets(Reference Lamprecht and Stamm15) (economic environment) and a major supermarket chain, which supports the Five a Day campaign of the Swiss Federal Office of Health, regularly makes special offers on fruit and vegetables. Moreover, it seems unlikely that migrants from Turkey and the Kosovo are less aware of FVI than other migrant groups or native Swiss because information and materials are available in foreign languages. However, diet-related public health initiatives which address migrants specifically do not exist to date. Since neither awareness nor the physical or economic environment appears to be a barrier specific to migrants from Turkey and Kosovo, we propose that nutrition education initiatives embedded in migrant cultural clubs may be a promising approach to increase fruit and vegetable consumption. These clubs could serve as a basis for peer health educators who offer cookery courses, food tasting and other activities which revive the healthy cooking traditions of Turkey and Kosovo. Food tasting and cookery courses, in conjunction with the proposed social setting, target different but complementing determinants of FVI which are now discussed briefly.

First, there is evidence that food preferences can be learned(Reference Birch51Reference Wardle, Herrera and Cooke55). The opportunity to repeatedly taste traditional and novel fruit and vegetable dishes can increase the liking for these dishes. Hence food tastings can help to change food preferences and can increase the motivation to consume more fruit and vegetables. Second, several studies that systematically review the determinants of FVI show that self-efficacy, i.e. people's belief in their ability to succeed in certain situations(Reference Bandura56), and nutritional knowledge are positively associated with FVI(Reference Brug48, Reference Rasmussen, Krolner and Klepp57Reference Guillaumie, Godin and Vezina-Im59). Cookery courses can increase practical knowledge on how to prepare novel fruit and vegetable dishes and healthier variations of traditional dishes (healthy alternatives). Similarly, they can increase knowledge on recommended intake levels and awareness of personal intake. Cookery courses help to enable voluntary dietary change by enhancing people's ability, i.e. skills and capabilities. Third, food tasting and cookery courses take place in migrant cultural clubs. The latter can be considered a micro-environmental setting of the sociocultural environment, which refers to the migrant community's attitudes, beliefs and values related to food and physical activity(Reference Swinburn, Egger and Raza60). Food-related activities within these micro-environmental settings may not only change people's motivation and ability, but may also help to develop and foster new dietary norms and cooking traditions when people start to incorporate the new dietary practices into their everyday life. Moreover, peer social networks may help to further diffuse new dietary practices into the broader sociocultural environment when families, friends and neighbours are regularly confronted with healthy fruit and vegetable dishes.

Conclusions

In summary, the proportion of participants who adhered to the recommended fruit and vegetable consumption was below one-third in all study populations. Migrants from Turkey and Kosovo relative to Swiss nationals are at particular risk of low daily fruit and vegetable consumption relative to the recommended daily intake. Initiatives for the promotion of fruit and vegetable consumption should continue to address the population at large. At the same time, programmes that are tailored to the specific needs of migrants from Turkey and Kosovo should be considered.

Acknowledgements

This study was supported by the Swiss Federal Office of Public Health and the Swiss Federal Office for Migration, grant number 09.005923/704.0001/-330. The authors declare that they have no conflict of interest. T.V. contributed most of the writing and the analysis. P.R. and J.G. contributed to the writing and editorial review.

Footnotes

* For the summation process the following values were assigned to the categories: 0 = ‘none’; 0·5 = ‘less than 1 serving per day’; 1·5 = ‘1–2 servings per day’; 3·5 = ‘3–4 servings per day’; and 5 = ‘5 or more servings per day’.

The category ‘recommended FVI’ reflects the amount of daily fruit and vegetable intake which is currently promoted by the Swiss Federal Office of Public Health (http://www.bag.admin.ch/themen/ernaehrung_bewegung) and the Swiss Cancer League.

References

1.World Health Organization/Food and Agriculture Organization of the United Nations (2005) Fruit and Vegetables for Health. Report of a Joint FAO/WHO Workshop, 1–3 September 2004, Kobe, Japan. Geneva: WHO and FAO.Google Scholar
2.Crowe, FL, Roddam, AW, Key, TJet al. (2011) Fruit and vegetable intake and mortality from ischaemic heart disease: results from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Heart study. Eur Heart J 32, 12351243.CrossRefGoogle ScholarPubMed
3.Dauchet, L, Montaye, M, Ruidavets, JBet al. (2010) Association between the frequency of fruit and vegetable consumption and cardiovascular disease in male smokers and non-smokers. Eur J Clin Nutr 64, 578586.CrossRefGoogle ScholarPubMed
4.Dauchet, L, Amouyel, P & Dallongeville, J (2009) Fruits, vegetables and coronary heart disease. Nat Rev Cardiol 6, 599608.CrossRefGoogle ScholarPubMed
5.Oude Griep, LM, Geleijnse, JM, Kromhout, Det al. (2010) Raw and processed fruit and vegetable consumption and 10-year coronary heart disease incidence in a population-based cohort study in the Netherlands. PLoS One 5, e13609.CrossRefGoogle Scholar
6.Scarborough, P, Nnoaham, KE, Clarke, Det al. (2012) Modelling the impact of a healthy diet on cardiovascular disease and cancer mortality. J Epidemiol Community Health 66, 420426.CrossRefGoogle ScholarPubMed
7.Tyrovolas, S & Panagiotakos, DB (2010) The role of Mediterranean type of diet on the development of cancer and cardiovascular disease, in the elderly: a systematic review. Maturitas 65, 122130.CrossRefGoogle ScholarPubMed
8.Zhang, X, Shu, XO, Xiang, YBet al. (2011) Cruciferous vegetable consumption is associated with a reduced risk of total and cardiovascular disease mortality. Am J Clin Nutr 94, 240246.CrossRefGoogle ScholarPubMed
9.Zhang, CX, Ho, SC, Fu, JHet al. (2011) Dietary patterns and breast cancer risk among Chinese women. Cancer Causes Control 22, 115124.CrossRefGoogle ScholarPubMed
10.Steevens, J, Schouten, LJ, Goldbohm, RAet al. (2011) Vegetables and fruits consumption and risk of esophageal and gastric cancer subtypes in the Netherlands Cohort Study. Int J Cancer 129, 26812683.CrossRefGoogle ScholarPubMed
11.Richman, EL, Carroll, PR & Chan, JM (2012) Vegetable and fruit intake after diagnosis and risk of prostate cancer progression. Int J Cancer 131, 201210.CrossRefGoogle ScholarPubMed
12.Ott, JJ, Ullrich, A, Mascarenhas, Met al. (2011) Global cancer incidence and mortality caused by behavior and infection. J Public Health (Oxf) 33, 223233.CrossRefGoogle ScholarPubMed
13.Aune, D, Lau, R, Chan, DSet al. (2011) Nonlinear reduction in risk for colorectal cancer by fruit and vegetable intake based on meta-analysis of prospective studies. Gastroenterology 141, 106118.CrossRefGoogle ScholarPubMed
14.Bravi, F, Polesel, J, Bosetti, Cet al. (2011) Dietary intake of selected micronutrients and the risk of pancreatic cancer: an Italian case–control study. Ann Oncol 22, 202206.CrossRefGoogle ScholarPubMed
15.Lamprecht, M & Stamm, H (2009) Monitoring der langfristigen Strategie von Gesundheitsförderung Schweiz. Indikatoren zum Bereich ,,Gesundes Körpergewicht“. Bern: Health Promotion Switzerland.Google Scholar
16.Eichholzer, M, Bernasconi, F, Jordan, Pet al. (2005) Ernährung in der Schweiz. Resultate der Schweizerischen Gesundheitsbefragung 2002. Praxis 94, 17131721.CrossRefGoogle ScholarPubMed
17.Bundesamt für Statistik (2010) Die Bevölkerung der Schweiz 2009. Neuchâtel: Swiss Federal Statistical Office.Google Scholar
18.Caperchione, CM, Kolt, GS & Mummery, WK (2009) Physical activity in culturally and linguistically diverse migrant groups to Western society: a review of barriers, enablers and experiences. Sports Med 39, 167177.CrossRefGoogle ScholarPubMed
19.Ceballos, N & Czyzewska, M (2010) Body image in Hispanic/Latino vs. European American adolescents: implications for treatment and prevention of obesity in underserved populations. J Health Care Poor Underserved 21, 823838.CrossRefGoogle ScholarPubMed
20.Kolcic, I & Polasek, O (2009) Healthy migrant effect within Croatia. Coll Antropol 33, Suppl. 1, 141145.Google ScholarPubMed
21.Liu, JH, Probst, JC, Harun, Net al. (2009) Acculturation, physical activity, and obesity among Hispanic adolescents. Ethn Health 14, 509525.CrossRefGoogle ScholarPubMed
22.Park, SY, Murphy, SP, Sharma, Set al. (2005) Dietary intakes and health-related behaviours of Korean American women born in the USA and Korea: the multiethnic cohort study. Public Health Nutr 8, 904911.CrossRefGoogle ScholarPubMed
23.Olvera, N, Suminski, R & Power, TG (2005) Intergenerational perceptions of body image in Hispanics: role of BMI, gender, and acculturation. Obes Res 13, 19701979.CrossRefGoogle ScholarPubMed
24.Nicolaou, M, Doak, CM, van Dam, RMet al. (2009) Cultural and social influences on food consumption in Dutch residents of Turkish and Moroccan origin: a qualiltative study. J Nutr Educ Behav 41, 232241.CrossRefGoogle ScholarPubMed
25.Landman, J & Cruickshank, JK (2001) A review of ethnicity, health and nutrition-related diseases in relation to migration in the United Kingdom. Public Health Nutr 4, 647657.CrossRefGoogle ScholarPubMed
26.Mejean, C, Deschamps, V, Bellin-Lestienne, Cet al. (2010) Associations of socioeconomic factors with inadequate dietary intake in food aid users in France (the ABENA study 2004–2005). Eur J Clin Nutr 64, 374382.CrossRefGoogle ScholarPubMed
27.Labree, LJ, van de Mheen, H, Rutten, FFet al. (2011) Differences in overweight and obesity among children from migrant and native origin: a systematic review of the European literature. Obes Rev 12, e535e547.CrossRefGoogle ScholarPubMed
28.Kumar, NB, Yu, D, Akinremi, TOet al. (2009) Comparing dietary and other lifestyle factors among immigrant Nigerian men living in the US and indigenous men from Nigeria: potential implications for prostate cancer risk reduction. J Immigr Minor Health 11, 391399.CrossRefGoogle ScholarPubMed
29.Harriss, LR, English, DR, Powles, Jet al. (2007) Dietary patterns and cardiovascular mortality in the Melbourne Collaborative Cohort Study. Am J Clin Nutr 86, 221229.CrossRefGoogle ScholarPubMed
30.Neuhouser, ML, Thompson, B, Coronado, GDet al. (2004) Higher fat intake and lower fruit and vegetables intakes are associated with greater acculturation among Mexicans living in Washington State. J Am Diet Assoc 104, 5157.CrossRefGoogle ScholarPubMed
31.Renzaho, AM, Swinburn, B & Burns, C (2008) Maintenance of traditional cultural orientation is associated with lower rates of obesity and sedentary behaviours among African migrant children to Australia. Int J Obes (Lond) 32, 594600.CrossRefGoogle ScholarPubMed
32.Satia-Abouta, J, Patterson, RE, Kristal, ARet al. (2002) Psychosocial predictors of diet and acculturation in Chinese American and Chinese Canadian women. Ethn Health 7, 2139.CrossRefGoogle ScholarPubMed
33.Bundesamt für Statistik (2010) Statistik der Bevölkerung und der Haushalte (STATPOP). Neuchâtel: Swiss Federal Statistical Office.Google Scholar
34.Zwahlen, M, Keel, F, Zybach, U (2006) Evaluation. Früchte- und Gemüsekonsum in der Schweiz 2005 mit einem Vergleich zur ,,Stichtagserhebung zum täglichen Früchte- und Gemüsekonsum 2011/2002“ und zum ,,Food and Beverage Monitor“ 2002. http://www.5amtag.ch/wp-content/uploads/2010/03/Bericht-Evaluation-Früchte-Gemüsekonsum-2005.pdf (accessed September 2011).Google Scholar
35.Allison, PD (2001) Missing Data. Thousand Oaks, CA: Sage.Google Scholar
36.Sofianou, A, Fung, TT & Tucker, KL (2011) Differences in diet pattern adherence by nativity and duration of US residence in the Mexican-American population. J Am Diet Assoc 111, 15631569.CrossRefGoogle ScholarPubMed
37.Shin, CN & Lach, H (2011) Nutritional issues of Korean Americans. Clin Nurs Res 20, 162180.CrossRefGoogle ScholarPubMed
38.Gregory-Mercado, KY, Staten, LK, Ranger-Moore, Jet al. (2006) Fruit and vegetable consumption of older Mexican-American women is associated with their acculturation level. Ethn Dis 16, 8995.Google ScholarPubMed
39.Grossmann, F, Leventhal, ME, Auer-Böer, Bet al. (2011) Self-reported cardiovascular risk factors in immigrants and Swiss nationals. Public Health Nurs 28, 129139.CrossRefGoogle ScholarPubMed
40.Figueiredo, I, Jaime, PC & Monteiro, CA (2008) Factors associated with fruit and vegetable intake among adults of the city of São Paulo, Southeastern Brazil. Rev Saude Publica 42, 18.Google Scholar
41.Dowler, E (2001) Inequalities in diet and physical activity in Europe. Public Health Nutr 4, 701709.CrossRefGoogle ScholarPubMed
42.Agudo, A (2005) Measuring Intake of Fruit and Vegetable. Background Paper for the Joint FAO/WHO Workshop on Fruit and Vegetables for Health, 1–3 September 2004, Kobe, Japan. Geneva: WHO.Google Scholar
43.MacIntyre, U, Venter, C & Vorster, H (2001) A culture-sensitive quantiative food frequency questionnaire used in an African population: 2. Relative validation by 7-day weighted records and biomarkers. Public Health Nutr 4, 6371.CrossRefGoogle Scholar
44.Agudo, A, Slimani, N, Ocke, MCet al. (2002) Consumption of vegetables, fruit and other plant foods in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts from 10 European countries. Public Health Nutr 5, 11791196.CrossRefGoogle ScholarPubMed
45.Kim, DJ & Holowaty, EJ (2003) Brief, validated survey instruments for the measurement of fruit and vegetable intakes in adults: a review. Prev Med 36, 440447.CrossRefGoogle ScholarPubMed
46.Ocke, MC, Bueno-de-Mesquita, H, Goddijn, Het al. (1997) The Dutch EPIC food frequency questionnaire. I. Description of the questionnaire, and relative validity and reproducibility for food groups. Int J Epidemiol 26, Suppl. 1, S37S48.CrossRefGoogle ScholarPubMed
47.Pisani, P, Faggiano, F, Krogh, Vet al. (1997) Relative validity and reproducibility of a food frequency dietary questionnaire for use in the Italian EPIC centres. Int J Epidemiol 26, Suppl. 1, S152S160.CrossRefGoogle ScholarPubMed
48.Brug, J (2008) Determinants of healthy eating: motivation, abilities and environmental opportunities. Fam Pract 25, Suppl. 1, i50i55.CrossRefGoogle ScholarPubMed
49.Darmon, N, Briend, A & Drewnowski, A (2004) Energy-dense diets are associated with lower diet costs: a community study of French adults. Public Health Nutr 7, 2127.CrossRefGoogle ScholarPubMed
50.Dibsdall, LA, Lambert, N, Bobbin, RFet al. (2003) Low-income consumers’ attitudes and behaviour towards access, availability and motivation to eat fruit and vegetables. Public Health Nutr 6, 159168.CrossRefGoogle ScholarPubMed
51.Birch, LL (1998) Development of food acceptance patterns in the first years of life. Proc Nutr Soc 57, 617624.CrossRefGoogle ScholarPubMed
52.Birch, LL & Fisher, JO (1998) Development of eating behaviors among children and adolescents. Pediatrics 101, 539549.CrossRefGoogle ScholarPubMed
53.Birch, LL, Gunder, L, Grimm-Thomas, Ket al. (1998) Infants’ consumption of a new food enhances acceptance of similar foods. Appetite 30, 283295.CrossRefGoogle ScholarPubMed
54.Wardle, J, Cooke, LJ, Gibson, ELet al. (2003) Increasing children's acceptance of vegetables; a randomized trial of parent-led exposure. Appetite 40, 155162.CrossRefGoogle ScholarPubMed
55.Wardle, J, Herrera, ML, Cooke, Let al. (2003) Modifying children's food preferences: the effects of exposure and reward on acceptance of an unfamiliar vegetable. Eur J Clin Nutr 57, 341348.CrossRefGoogle ScholarPubMed
56.Bandura, A (1997) Self-Efficacy: The Excercise of Control. New York: Freeman.Google Scholar
57.Rasmussen, M, Krolner, R, Klepp, KIet al. (2006) Determinants of fruit and vegetable consumption among children and adolescents: a review of the literature. Part I: Quantitative studies. Int J Behav Nutr Phys Act 3, 22.CrossRefGoogle ScholarPubMed
58.Shaikh, AR, Yaroch, AL, Nebeling, Let al. (2008) Psychosocial predictors of fruit and vegetable consumption in adults a review of the literature. Am J Prev Med 34, 535543.CrossRefGoogle ScholarPubMed
59.Guillaumie, L, Godin, G & Vezina-Im, LA (2010) Psychosocial determinants of fruit and vegetable intake in adult population: a systematic review. Int J Behav Nutr Phys Act 7, 12.CrossRefGoogle ScholarPubMed
60.Swinburn, B, Egger, G & Raza, F (1999) Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev Med 29, 563570.CrossRefGoogle ScholarPubMed
61.Schuler, M, Dessemontet, P & Joye, D (2005) Die Raumgliederung der Schweiz. Neuchâtel: Federal Statistical Office.Google Scholar
Figure 0

Table 1 Frequency distribution and central tendency for variables in the sample of participants aged 17–64 years by nationality (2010 Swiss Migrant Health Survey 2010 and 2007 Swiss Health Survey)*

Figure 1

Table 2 Population estimates of fruit and vegetable consumption of participants aged 17–64 years by nationality (2010 Swiss Migrant Health Survey and 2007 Swiss Health Survey 2007)*

Figure 2

Table 3 Multinomial regression analysis of factors associated with daily fruit and vegetable consumption, participants aged 17–64 years (2010 Swiss Migrant Health Survey and 2007 Swiss Health Survey)*