Skip to main content Accessibility help
×
Home
Hostname: page-component-768ffcd9cc-nzrtw Total loading time: 1.105 Render date: 2022-12-05T01:17:47.688Z Has data issue: true Feature Flags: { "useRatesEcommerce": false } hasContentIssue true

Prevalence of overweight and obesity among migrants in Switzerland: association with country of origin

Published online by Cambridge University Press:  22 February 2011

Pedro Marques-Vidal*
Affiliation:
Institute of Social and Preventive Medicine (IUMSP), University Hospital (CHUV), Faculty of Biology and Medicine of Lausanne, Bugnon 17, 1005 Lausanne, Switzerland Clinical Research Centre, University Hospital (CHUV), Lausanne, Switzerland
Peter Vollenweider
Affiliation:
Department of Medicine, University Hospital (CHUV), Lausanne, Switzerland
Gérard Waeber
Affiliation:
Department of Medicine, University Hospital (CHUV), Lausanne, Switzerland
Fred Paccaud
Affiliation:
Institute of Social and Preventive Medicine (IUMSP), University Hospital (CHUV), Faculty of Biology and Medicine of Lausanne, Bugnon 17, 1005 Lausanne, Switzerland
*
*Corresponding author: Email Pedro–Manuel.Marques–Vidal@chuv.ch
Rights & Permissions[Opens in a new window]

Abstract

Objective

Migrants tend to present higher overweight and obesity levels, but whether this relationship applies to all nationalities has seldom been studied. The present study aimed to assess the prevalence of overweight and obesity according to nationality in adults.

Design

Cross-sectional population-based samples.

Setting

Five-year nationwide interview surveys (Swiss Health Surveys – SHS) from 1992 to 2007 (n 63 766) and a local examination survey (CoLaus Study in Lausanne 2004–2006, n 6743).

Subjects

Participants were separated into Swiss, French, German, Italian, Portuguese, Spanish nationals, those from the former Republic of Yugoslavia and from other European and other countries.

Results

Compared with Swiss nationals, German and French nationals presented a lower prevalence of overweight and obesity, whereas nationals from Italy, Spain, Portugal and the former Republic of Yugoslavia presented higher levels. Adjusting the SHS data for age, gender, education, smoking, leisure-time physical activity and survey year, a lower risk for overweight and obesity was found for German (OR = 0·80, 95 % CI 0·70, 0·92) and French (OR = 0·74, 95 % CI 0·61, 0·89) nationals, whereas higher risks were found for participants from Italy (OR = 1·45, 95 % CI 1·33, 1·58), Spain (OR = 1·36, 95 % CI 1·15, 1·61), Portugal (OR = 1·25, 95 % CI 1·06, 1·47) and the former Republic of Yugoslavia (OR = 1·98, 95 % CI 1·69, 2·32). Similar findings were observed in the CoLaus Study for Italian (OR = 1·63, 95 % CI 1·29, 2·06), Spanish (OR = 1·54, 95 % CI 1·17, 2·04) and Portuguese (OR = 1·49, 95 % CI 1·16, 1·91) participants and for those from the former Republic of Yugoslavia (OR = 5·34, 95 % CI 3·00, 9·50).

Conclusions

Overweight and obesity are unevenly distributed among migrants in Switzerland. Migrants from Southern Europe and from the former Republic of Yugoslavia present higher prevalence rates. This suggests that preventive messages should be tailored to these specific populations.

Type
Research paper
Copyright
Copyright © The Authors 2011

Obesity has reached pandemic proportions. In Europe it is estimated that 30–80 % of adults are overweight or obese, with approximately 150 million individuals being obese(1). Several studies have shown that migrants present a higher prevalence of overweight and obesity than nationals(Reference Dijkshoorn, Nierkens and Nicolaou2Reference Wändell, Ponzer and Johansson4), although this finding has not been found in other studies(Reference Akresh5, Reference Barcenas, Wilkinson and Strom6). Switzerland has a large migrant community of over 1·6 million, representing over one-fifth of the total population(7). Nevertheless, the prevalence of overweight and obesity according to migrant status or nationality of adult migrants in Switzerland has seldom been studied(Reference Bischoff and Wanner8).

Hence, we used the data from two large, population-based samples (Swiss Health Surveys (SHS) and CoLaus Study) to assess the prevalence of overweight and obesity according to nationality among adults in Switzerland.

Experimental methods

CoLaus Study

The CoLaus Study was approved by the Institutional Ethics Committee of the University of Lausanne. The CoLaus Study is cross-sectional in nature aimed at assessing the prevalence and deciphering the molecular determinants of cardiovascular risk factors in the Caucasian population of Lausanne, Switzerland, a town of 117 161 inhabitants, of whom 79 420 are of Swiss nationality.

The sampling procedure of the CoLaus Study has been described previously(Reference Firmann, Mayor and Marques-Vidal9). Briefly, the complete list of Lausanne inhabitants aged 35–75 years (n 56 694) was provided by the population registry of the city. A simple, non-stratified random sample of 35 % of the overall population was drawn. The following inclusion criteria were applied: (i) written informed consent; (ii) 35–75 years of age; (iii) willingness to participate in the study and donate a blood sample; and (iv) Caucasian origin. Recruitment began in June 2003 and ended in May 2006. Participation rate was 41 %. For the present study, data from non-Caucasian participants (n 555), initially excluded from the main study but assessed the same way, were also included.

All participants presented to the outpatient clinic of the University Hospital of Lausanne in the morning after an overnight fast. Data were collected by trained field interviewers in a single visit lasting about 60 min.

Swiss Health Survey

Data from the four SHS were obtained from the Swiss Federal Statistical Office (www.bfs.admin.ch). The SHS is a cross-sectional, nationwide, population-based telephonic survey conducted every 5 years since 1992 by the Swiss Federal Statistical Office under a mandate of the Federal Government(Reference Calmonte, Galati-Petrecca and Lieberherr10). The SHS aims to track public health trends in a representative sample of the resident population of Switzerland aged ≥15 years(11). To date, the survey has been carried out four times, in 1992–1993, 1997, 2002 and 2007.

The study population was chosen by stratified random sampling of a database of all private Swiss households with fixed line telephones. The first sampling stratum consisted of the seven main regions: West ‘Leman’, West–Central ‘Mittelland’, Northwest, Zurich, North–East, Centre and South. The second stratum consisted of the cantons, and the number of households drawn was proportional to the population of the canton. In some cantons, households were oversampled to obtain accurate cantonal estimates. The third stratum consisted of households. One member of the household was randomly selected in advance from all members aged ≥15 years. A letter inviting this selected household member to participate in the survey was sent to each sampled individual, who was then contacted thereafter by phone and interviewed using a computer-assisted telephone interview software to manage dialling and data collection. Face-to-face interviews were organized for participants older than 75 years. In the case of long-term absence of a sampled individual, a proxy interviewee was requested to provide answers on behalf of the predefined sampled person (it is estimated that this substitution occurred in approximately 3 % of households). The interviews were carried out in German, French or Italian, as appropriate. People who did not speak any of these three languages were excluded from the survey. Other criteria for exclusion were: asylum seeker status; households without a fixed line telephone; very poor health status; and living in a nursing home(12). Participation rate was 71 % in 1992–1993, 85 % in 1997, 64 % in 2002 and 66 % in 2007. It is estimated that <2 % of households were excluded because of these exclusion criteria. More details are available at http://www.bfs.admin.ch/bfs/portal/fr/index/infothek/erhebungen__quellen/blank/blank/ess/01.html.

Data collected

The following nationalities were considered: Swiss, former Yugoslavian, French, German, Italian, Portuguese and Spanish. Owing to the small number of participants, the other nationalities were grouped as follows: other European nations and the rest of the world. The choice was based on a previous study(Reference Bischoff and Wanner8), although we did not consider Turkish migrants because of small sample sizes. When a participant had dual nationality, the Swiss or the first given nationality (if not Swiss) was considered. For the CoLaus Study, the country of birth was considered as the nationality, whereas for the SHS the participants were directly asked about their nationality. The length of residence in Switzerland was assessed for all participants in the CoLaus Study, whereas only the SHS for 2007 collected such information.

In the CoLaus Study, body weight and height were measured with participants standing without shoes in light indoor clothes. Body weight was measured in kilograms to the nearest 100 g using a Seca® scale (Seca Schweiz, Reinach, Switzerland), which was calibrated regularly. Height was measured to the nearest 5 mm using a Seca® height gauge (Seca Schweiz). In the SHS, the participants were asked about their current body weight and height. BMI was calculated as weight in kilograms divided by the square of height in metres (kg/m2). Participants were considered to be normal weight, overweight or obese if their BMI was <25·0, ≥25·0 and <30·0 or ≥30·0 kg/m2, respectively.

Waist was measured with a non-stretchable tape over the unclothed abdomen at the narrowest point between the lowest rib and the iliac crest(Reference Lean, Han and Morrison13). Two measurements were recorded and the mean (expressed in centimetres) was used for analyses. Abdominal obesity was defined as waist circumference ≥102 cm for men and ≥88 cm for women(Reference Lean, Han and Morrison13).

Three age categories were considered: 18–34, 35–64 and ≥65 years. Education was categorized as follows: (i) no education completed/primary school (referred to as ‘basic’); (ii) apprenticeship/secondary level (referred to as ‘secondary’); and (iii) tertiary level, which included university and other forms of education after the secondary level (referred to as ‘university’). Leisure-time physical activity was considered when the participant reported exercising at least once per week; no answer was considered as a negative answer. Smoking status was divided into current, former (irrespective of the delay) and never.

Statistical analysis

Statistical analysis was conducted using the SAS statistical software package version 9·2 (SAS Institute, Cary, NC, USA). For the SHS, a first analysis was conducted using the original data. A second analysis was conducted after weighting each participant. Weights were computed taking into account the percentage of non-responders by raking ratio estimation(Reference Mohadjer and Choudhry14). Weighting partly allows the correction for bias, i.e. participants with given characteristics who are under-represented in the original sample are attributed a higher weight.

Quantitative variables were expressed as mean and sd and qualitative variables as number of participants and percentage. Continuous and categorical data were analysed using the t test and the χ 2 test, respectively. The relationships between length of residence and BMI were assessed by Pearson's correlation and multiple regression, adjusting for age; the results of the regression analysis were expressed as standardized coefficients. Standardized regression coefficients represent the change in the dependent variable, expressed as a fraction of the sd per sd change in the independent variable, and can be considered as adjusted correlation coefficients. In the SHS, the time trends (1992–2007) in BMI were also assessed separately for each nationality by multiple regression adjusting for age and sex, and the results were expressed as standardized coefficients. As the number of participants with obesity according to nationality and survey year was relatively small, the combined prevalence of overweight and obesity was used, and its time trend was assessed separately for each nationality using the Cochran–Armitage test.

The impact of nationality on the risk of presenting with overweight and/or obesity was assessed by multivariate logistic regression analysis adjusting for age, gender, educational level, smoking status and physical activity. For the SHS, a further adjustment on survey year was applied. The results were expressed as OR and 95 % CI. Statistical significance was considered for P < 0·05.

Results

Sample characteristics

Overall, 63 766 participants from the SHS and 6743 participants from the CoLaus Study (6188 from the main study and 555 non-Caucasians) were included in the analyses. Their demographic and anthropometric characteristics according to nationality are summarized in Table 1. In both samples, participants from Southern Europe and from the former Republic of Yugoslavia were younger, had a lower educational level, practised leisure-time physical activity less frequently, smoked more and were living in Switzerland for a shorter time. The proportions of women were also lower among German, Italian and Spanish citizens.

Table 1 Characteristics of the participants according to nationality: SHS 1992–2007 and the CoLaus Study

SHS, Swiss Health Survey; PA, physical activity.

Results are expressed as number of participants and percentage, or mean and standard deviation.

Statistical analysis was carried out using the χ 2 test or ANOVA; all comparisons are significant at P < 0·001.

*For 2007 only.

Overweight and obesity levels

Differing prevalence of overweight and obesity was found according to nationality (Table 1). Compared with Swiss nationals, German and French nationals presented lower levels of overweight and obesity, whereas Southern European nationals and citizens from the former Republic of Yugoslavia presented higher levels. Similar findings were obtained for waist and abdominal obesity (Table 1). On multivariate analysis adjusting for age, gender, education, smoking, leisure-time physical activity and survey year (for the SHS only), German and French nationals tended to have a lower risk, whereas participants from Southern European countries (Italy, Spain, Portugal) and from the former Republic of Yugoslavia had a higher risk of presenting with overweight or obesity (Table 2).

Table 2 Multivariate analysis of the factors associated with overweight and obesity: SHS 1992–2007 and the CoLaus Study

SHS, Swiss Health Survey; PA, physical activity; Ref., reference category.

Statistical analysis was carried out using multivariate logistic regression.

The length of residence of non-Swiss nationals was positively related with BMI (Pearson r = 0·203, n 1853 and r = 0·089, n 2640, for the SHS and the CoLaus Study, respectively, both with P < 0·001). Findings were similar for waist circumference (Pearson r = 0·126, P < 0·001) in the CoLaus Study. These significant positive relationships remained after adjusting for age in SHS 2007 (standardized regression coefficient = 0·11, P < 0·001), but not in the CoLaus Study (standardized regression coefficient = −0·03, P = 0·31 and −0·02, P = 0·38, respectively). Splitting the length of residence into 10-year categories (<10, 10–19, 20–29 and ≥30 years) showed no significant relationship with obesity and overweight/obesity after adjusting for age, gender, smoking, leisure-time physical activity and nationality in the CoLaus Study, and no clear trend was identified in the SHS 2007 (Table 3). As for BMI-derived obesity, no relationship between length of residence and abdominal obesity was found, and no differences were found regarding nationality; for French and Portuguese nationals, OR = 0·74 (95 % CI 0·44, 1·25) and 0·80 (95 % CI 0·45, 1·43), respectively (P = NS).

Table 3 Multivariate analysis of the effect of duration on overweight and obesity (migrants only): SHS 2007 and the CoLaus Study

SHS, Swiss Health Survey; PA, physical activity; Ref., reference category.

Statistical analysis was carried out using multivariate logistic regression.

After adjusting for age and sex, positive increases in BMI with time were found for German (standardized regression coefficient = 0·065, P < 0·02), Italian (standardized regression coefficient = 0·057, P < 0·004), French (standardized regression coefficient = 0·095, P < 0·01), Portuguese (standardized regression coefficient = 0·113, P < 0·002), other European (standardized regression coefficient = 0·090, P < 0·001) and other world (standardized regression coefficient = 0·100, P < 0·004) nationals, whereas no significant trends were found for Spanish (standardized regression coefficient = 0·058, P = 0·14) nationals and for those from the former Republic of Yugoslavia (standardized regression coefficient = 0·065, P = 0·06). The corresponding value for Swiss nationals was 0·048 (P < 0·001). Similarly, the combined prevalence of overweight and obesity increased with time in most migrant groups, with the exception of Spain and the former Republic of Yugoslavia (Table 4).

Table 4 Trends in the prevalence of overweight and obesity according to survey year (migrants): SHS 1992–2007

SHS, Swiss Health Survey.

Test for trend was performed separately for each nationality using the Cochran–Armitage test.

Discussion

To our knowledge, the present study is the most comprehensive one assessing the prevalence of overweight and obesity according to nationality among migrants living in Switzerland. Our data indicate that overweight and obesity are unevenly distributed among migrants in Switzerland, some groups showing higher overweight and obesity levels independently of education, smoking, physical activity or length of residence. Our findings are partly in agreement with those of a previous study(Reference Bischoff and Wanner8), which failed to find any relationship between nationality and obesity status, probably because of the smaller sample size.

The highest prevalence of overweight and obesity was found for migrants from the former Republic of Yugoslavia, a finding already reported for adolescents(Reference Kirchengast and Schober15). The reasons for such an increase cannot be attributed solely to differences in age, socio-economic status or physical activity, as this increased prevalence remained after multivariate adjustment. It is possible that some migrants associate a fat body to increased wealth(Reference Renzaho16), but this statement has been challenged(Reference Nicolaou, Doak and Dam17, Reference Råberg, Kumar and Holmboe-Ottesen18). Hence, other factors such as diet and eventually a differing genetic background await further investigation.

Some discrepancies were found regarding the factors associated with BMI and waist-derived obesity. No associations were found between most nationalities and abdominal obesity, whereas significant associations were found using BMI. Further, Portuguese migrants had a higher OR for overweight and obesity (BMI-derived) and a lower OR for abdominal obesity, although no significant association was found after adjusting for length of residence. Overall, our findings suggest that the relationship between migrant status or nationality and abdominal obesity might be different from that regarding BMI-derived obesity, but the reasons for such a discrepancy await further investigation.

Compared with data from their country of origin(1), differing patterns were found: migrants from France, Germany and Spain presented lower levels of overweight and obesity, whereas migrants from Portugal presented higher levels (Fig. 1). A possible explanation might be the socio-economic status of migrants. Indeed, and as reported in Table 1, the Portuguese had a much lower educational level than the Swiss, whereas the French and Germans had a higher level. Nevertheless, the Spanish also had a lower educational level than the Swiss, but their obesity levels were actually lower than those reported for Spain. Although socio-economic status might partly explain the differences in overweight and obesity prevalence between migrants, other factors such as diet should also be considered(Reference Kouris-Blazos, Wahlqvist and Trichopoulou19). For instance, and as reported for Greek migrants in Australia(Reference Landman and Cruickshank20), Portuguese migrants might adopt a less healthy diet than in their original countries, whereas maintaining a more traditional lifestyle would protect them against obesity(Reference Renzaho, Swinburn and Burns21). Overall, our data indicate that the prevalence of overweight and obesity among migrants in Switzerland depends on their nationality, and does not obligatorily replicate the obesity pattern of the original country. Further, these differences in the prevalence of overweight and obesity cannot only be ascribed to differences in age, socio-economic status or leisure-time physical activity, and other factors such as diet and eventually a differing genetic background should be assessed.

Fig. 1 Comparison of the prevalence of overweight and obesity between migrants and their country of origin: (a) self-reported data and (b) measured data (, normal; , overweight; , obese)

It has been shown that increased length of residence can be associated with the risk of overweight and obesity(Reference Akresh5, Reference Goel, McCarthy and Phillips22, Reference Gentilucci, Picardi and Manfrini23), although this statement has been challenged(Reference Bjerregaard, Jørgensen and Andersen24). The present analysis shows ambiguous results. The small but significant relationships between length of residence and BMI were no longer significant after multivariate adjustment. Indeed, with increasing length of residence, the obesity rates in migrants tend to increase until they equal or even surpass the host country's rates(Reference Greenberg, Cwikel and Mirsky25, Reference Kaplan, Huguet and Newsom26). Hence, the risk of becoming obese is likely to depend on the actual prevalence of obesity in the host country; migrants in a country with a high obesity prevalence such as the USA might have a higher risk(Reference Akresh5, Reference Goel, McCarthy and Phillips22) than migrants in a country with a low obesity prevalence such as Sweden(Reference Bjerregaard, Jørgensen and Andersen24). Compared with other European countries(1), the prevalence of overweight and obesity in Switzerland is rather low; hence, it is possible that migrants coming to Switzerland may have a lower risk of developing overweight or obesity than migrants going to other countries. Overall, our data indicate that the length of residence does not seem to exert a significant effect on overweight or obesity levels among migrants in Switzerland, possibly because of a less ‘obesogenic’ environment.

An increase in BMI with time was found for most migrant groups, and this increase tended to be higher than the increase observed for Swiss nationals. However, some increases did not reach statistical significance (i.e. for Spanish and formerly Yugoslavian nationals); the most likely explanation is the relatively small sample sizes, and thus limited statistical power. Interestingly, most increases were stronger than those observed for Swiss nationals. A possible explanation is the fact that in some countries the prevalence of overweight and obesity has increased steeper than in Switzerland and that, therefore, migrants who arrived more recently might be more overweight or obese than those who came several years ago.

The present study has several limitations worth pointing out. The participation rate in the CoLaus Study was low (41 %), which might limit the generalization of the findings; however, this participation rate is similar to that of other epidemiological studies(Reference Grøtvedt, Kuulasmaa and Tolonen27). In addition, in the SHS, height and weight were self-reported, leading to a probable underestimation of the prevalence of overweight and obesity. Nevertheless, if we assume a non-differential bias, i.e. that the magnitude of height and weight underestimation does not change according to nationality, the relationship between overweight/obesity and nationality should not change. Finally, specific BMI and waist thresholds were used to define obesity, and it has been suggested that other thresholds should be used for non-Caucasians(Reference Deurenberg28). Nevertheless, as it was not possible to precisely assess the ethnicity of all CoLaus and SHS participants, the use of specific thresholds was justified. The major strength of our study is that we used two population-based samples representative of the Swiss population and that the results obtained were quite similar.

In summary, our results indicate that overweight and obesity are unevenly distributed among migrants in Switzerland. Migrants from Southern Europe and from the former Republic of Yugoslavia present higher prevalence rates. These differences suggest that preventive interventions should be tailored to the needs of specific populations(29).

Acknowledgements

The CoLaus Study was supported by research grants from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, Switzerland, and the Swiss National Science Foundation (Grant no.: 33CSCO-122661). P.V. and G.W. received an unrestricted grant for GSK to conduct the CoLaus Study. The authors report no conflict of interest. P.M.-V. analysed the data and drafted the manuscript; F.P., G.W. and P.V. conceived and designed the study and revised the manuscript critically for important intellectual content. All authors gave their final approval of the version published. The authors express their gratitude to the participants in the Lausanne CoLaus Study and to the investigators who have contributed to the recruitment, in particular Yolande Barreau, Anne-Lise Bastian, Binasa Ramic, Martine Moranville, Martine Baumer, Marcy Sagette, Jeanne Ecoffey and Sylvie Mermoud for data collection.

References

1.World Health Organization (2007) The Challenge of Obesity in the WHO European Region and the Strategies for Response. Copenhagen: WHO Regional Office for Europe.Google Scholar
2.Dijkshoorn, H, Nierkens, V & Nicolaou, M (2008) Risk groups for overweight and obesity among Turkish and Moroccan migrants in The Netherlands. Public Health 122, 625630.CrossRefGoogle ScholarPubMed
3.Renzaho, AM, Gibbons, C, Swinburn, B et al. (2006) Obesity and undernutrition in sub-Saharan African immigrant and refugee children in Victoria, Australia. Asia Pac J Clin Nutr 15, 482490.Google ScholarPubMed
4.Wändell, PE, Ponzer, S, Johansson, SE et al. (2004) Country of birth and body mass index: a national study of 2000 immigrants in Sweden. Eur J Epidemiol 19, 10051010.CrossRefGoogle ScholarPubMed
5.Akresh, IR (2008) Overweight and obesity among foreign-born and U.S.-born Hispanics. Biodemography Soc Biol 54, 183199.CrossRefGoogle ScholarPubMed
6.Barcenas, CH, Wilkinson, AV, Strom, SS et al. (2007) Birthplace, years of residence in the United States, and obesity among Mexican-American adults. Obesity (Silver Spring) 15, 10431052.CrossRefGoogle ScholarPubMed
7.Office Fédéral des Migrations (2010) Rapport sur la Migration 2009. Berne Wabern, Switzerland: ODM.Google Scholar
8.Bischoff, A & Wanner, P (2008) The self-reported health of immigrant groups in Switzerland. J Immigr Minor Health 10, 325335.CrossRefGoogle ScholarPubMed
9.Firmann, M, Mayor, V, Marques-Vidal, P et al. (2008) The CoLaus Study: a population-based study to investigate the epidemiology and genetic determinants of cardiovascular risk factors and metabolic syndrome. BMC Cardiovasc Disord 8, 6.CrossRefGoogle ScholarPubMed
10.Calmonte, R, Galati-Petrecca, M, Lieberherr, R et al. (2005) Gesundheit und Gesundheitsverhalten in der Schweiz 1992–2002. Schweizerische Gesundheitsbefragung. Neuchâtel, Switzerland: BFS.Google Scholar
11.Bundesamt für Statistik (2000) Schweizerische Gesundheitsbefragung: Gesundheit und Gesundheitsverhalten in der Schweiz 1997. Neuchâtel, Swtzerland: BFS.Google Scholar
12.IHA-GfK (2003) Schweizerische Gesundheitsbefragung SGB 2002 – Schlussbericht zur Datenerhebung. Neuchâtel, Switzerland: BFS.Google Scholar
13.Lean, ME, Han, TS & Morrison, CE (1995) Waist circumference as a measure for indicating need for weight management. BMJ 311, 158161.CrossRefGoogle ScholarPubMed
14.Mohadjer, L & Choudhry, GH (2001) Adjusting for missing data in low-income surveys. In Studies of Welfare Populations: Data Collection and Research Issues, pp. 129156 [Panel on Data and Methods for Measuring the Effects of Changes in Social Welfare Programs, M Ver Ploeg, RA Moffitt and CF Citro, editors]. Washington, DC: National Academy Press.Google Scholar
15.Kirchengast, S & Schober, E (2006) To be an immigrant: a risk factor for developing overweight and obesity during childhood and adolescence? J Biosoc Sci 38, 695705.CrossRefGoogle ScholarPubMed
16.Renzaho, AM (2004) Fat, rich and beautiful: changing socio-cultural paradigms associated with obesity risk, nutritional status and refugee children from sub-Saharan Africa. Health Place 10, 105113.CrossRefGoogle ScholarPubMed
17.Nicolaou, M, Doak, C, Dam, R et al. (2008) Body size preference and body weight perception among two migrant groups of non-Western origin. Public Health Nutr 11, 13321341.CrossRefGoogle ScholarPubMed
18.Råberg, M, Kumar, B, Holmboe-Ottesen, G et al. (2010) Overweight and weight dissatisfaction related to socio-economic position, integration and dietary indicators among south Asian immigrants in Oslo. Public Health Nutr 13, 695703.CrossRefGoogle ScholarPubMed
19.Kouris-Blazos, A, Wahlqvist, ML, Trichopoulou, A et al. (1996) Health and nutritional status of elderly Greek migrants to Melbourne, Australia. Age Ageing 25, 177189.CrossRefGoogle ScholarPubMed
20.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
21.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
22.Goel, MS, McCarthy, EP, Phillips, RS et al. (2004) Obesity among US immigrant subgroups by duration of residence. JAMA 292, 28602867.CrossRefGoogle ScholarPubMed
23.Gentilucci, UV, Picardi, A, Manfrini, S et al. (2008) Westernization of the Filipino population resident in Rome: obesity, diabetes and hypertension. Diabetes Metab Res Rev 24, 364370.CrossRefGoogle Scholar
24.Bjerregaard, P, Jørgensen, ME, Andersen, S et al. (2002) Decreasing overweight and central fat patterning with Westernization among the Inuit in Greenland and Inuit migrants. Int J Obes Relat Metab Disord 26, 15031510.CrossRefGoogle ScholarPubMed
25.Greenberg, L, Cwikel, J & Mirsky, J (2007) Cultural correlates of eating attitudes: a comparison between native-born and immigrant university students in Israel. Int J Eat Disord 40, 5158.CrossRefGoogle ScholarPubMed
26.Kaplan, MS, Huguet, N, Newsom, JT et al. (2004) The association between length of residence and obesity among Hispanic immigrants. Am J Prev Med 27, 323326.CrossRefGoogle ScholarPubMed
27.Grøtvedt, L, Kuulasmaa, K, Tolonen, H et al. (2008) Sampling and recruitment. In Review of Health Examination Surveys in Europe, pp. 82126 [H Tolonen, P Koponen, A Aromaa et al., editors]. Helsinki, Finland: KTL – National Public Health Institute.Google Scholar
28.Deurenberg, P (2001) Universal cut-off BMI points for obesity are not appropriate. Br J Nutr 85, 135136.CrossRefGoogle Scholar
29.Office Fédéral de la Santé Publique (2007) Stratégie Migration et Santé (Phase II: 2008–2013). Bern, Switzerland: OFSP.Google Scholar
Figure 0

Table 1 Characteristics of the participants according to nationality: SHS 1992–2007 and the CoLaus Study

Figure 1

Table 2 Multivariate analysis of the factors associated with overweight and obesity: SHS 1992–2007 and the CoLaus Study

Figure 2

Table 3 Multivariate analysis of the effect of duration on overweight and obesity (migrants only): SHS 2007 and the CoLaus Study

Figure 3

Table 4 Trends in the prevalence of overweight and obesity according to survey year (migrants): SHS 1992–2007

Figure 4

Fig. 1 Comparison of the prevalence of overweight and obesity between migrants and their country of origin: (a) self-reported data and (b) measured data (, normal; , overweight; , obese)

You have Access
13
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Prevalence of overweight and obesity among migrants in Switzerland: association with country of origin
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

Prevalence of overweight and obesity among migrants in Switzerland: association with country of origin
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

Prevalence of overweight and obesity among migrants in Switzerland: association with country of origin
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *