Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Cardiovascular disease risk factors in Spain: A comparison of native and immigrant populations

  • Elena Rodriguez-Alvarez ,

    Contributed equally to this work with: Elena Rodriguez-Alvarez, Luisa N. Borrell

    Roles Conceptualization, Methodology, Writing – original draft, Writing – review & editing

    elena.rodriguez@ehu.eus

    Affiliations Department of Nursing I, University of the Basque Country (UPV/EHU), Leioa, Spain, OPIK-Research Group for Social Determinants of Health and Demographic Change

  • Nerea Lanborena,

    Roles Formal analysis, Writing – review & editing

    Affiliations Department of Nursing I, University of the Basque Country (UPV/EHU), Leioa, Spain, OPIK-Research Group for Social Determinants of Health and Demographic Change

  • Luisa N. Borrell

    Contributed equally to this work with: Elena Rodriguez-Alvarez, Luisa N. Borrell

    Roles Conceptualization, Formal analysis, Supervision, Writing – original draft, Writing – review & editing

    Affiliations OPIK-Research Group for Social Determinants of Health and Demographic Change, Department of Epidemiology & Biostatistics, Graduate School of Public Health & Health Policy, City University of New York, New York, NY, United States of America, Department of Surgery, Medical and Social Science, University of Alcalá, Madrid, Spain

Cardiovascular disease risk factors in Spain: A comparison of native and immigrant populations

  • Elena Rodriguez-Alvarez, 
  • Nerea Lanborena, 
  • Luisa N. Borrell
PLOS
x

Abstract

Cardiovascular disease (CDV) risk factors are highly prevalent among adults with low social class in Spain. However, little is known on how these factors are distributed in the immigrant population, a socio-economic disadvantaged population. Thus, this study aims to examine inequalities in CVD risk factors among immigrant and native populations. We conducted a cross-sectional study using data from the Spanish National Health Survey 2017 and used log-binomial regression to quantify the association of immigrant status on CVD risk factors among adults aged 25–64 years. The probabilities of having at least three CVD risk factors were higher for immigrants from Eastern Europe (PR: 1.25; 95% CI: 1.15–1.35) and lower for immigrants from Africa (PR: 0.79; 95% CI: 0.69–0.89) when compared with natives. The association of immigrant status and CVD risk factors varies with educational attainment (p-interaction = 0.001). Immigrants from Eastern Europe with low educational attainment have a higher probability of having at least three CVD risk factors compared with their native counterparts. In contrast, immigrants from Africa and Latin America with low educational attainment had a protective effect against having at least three CVD risk relative to natives. Health prevention and promotion strategies to reduce the burden of CVD taking should account for educational attainment given its differential effect among the immigrant population in Spain.

Introduction

Cardiovascular diseases (CVD) is the leading cause of mortality worldwide, accounting for 31% of all deaths [1]. In addition, they represent an important cause of premature death (i.e., deaths before 65 years of age), disability and healthcare cost [2]. Although there has been a decrease in CVD-specific mortality in developed countries in recent decades [3], CVD continues to be the leading cause of death [4]. Moreover, the prevalence of CVD has increased, due to the aging of the population and the increase in the prevalence of risk factors [5]. In fact, in Europe, the prevalence of obesity and diabetes has doubled whereas the prevalence of hypertension and smoking have decreased in the last 30 years [3]. In addition, evidence suggests an unequal distribution of cardiovascular risk factors depending on income and educational level across countries [6]. The latter has led to higher mortality rates across European countries among lower socioeconomic groups [7, 8].

In the last two decades, the increase in migratory flows from low- to high-income countries has shaped the sociodemographic reality with implications for health and its policies [9]. In fact, place of birth constitutes a social determinant of health that generates health inequities for the immigrant population, due to their worse living and working conditions, less access to health services and their lower socioeconomic level [10]. In Europe, there is still little evidence on inequalities in cardiovascular risk factors. Studies show worse cardiovascular health in immigrants compared with natives [11, 12] and higher prevalence of hypertension, diabetes and obesity [1315]. In addition, the prevalence of these risk factors varies according to place of birth [16, 17] and country of destination [18], as a consequence of regional differences in educational opportunities, income distribution, and/or access to health care [19].

Spain is currently the fourth country in the European Union when it comes to proportion of immigrant population (6,123,769) and has one of the highest proportions of immigrants relative to its total population (10.7% in 2019) [20]. The majority of immigrants come from Latin America (41%, mostly from Colombia, Ecuador, Venezuela, Peru and Bolivia), Maghreb (14%; mostly from Morocco), sub-Saharan Africa (4%; mostly from Senegal and Nigeria), Asia (7%; mostly from China) and Eastern Europe (16%; mostly from Romania, Bulgaria, Russia and Ukraine). However, only four studies have examined inequalities in cardiovascular health according to place of birth [2124]. Two of these studies focused on inequalities in mortality [21, 22] and the other two examined specific CVD risk factors in two regions of Spain [23, 24] without consideration of socioeconomic position. Given that in Spain, CVD is the main cause of mortality [25], cardiovascular risk factors are more common in individual from low social class [26], and the high proportion of immigrants in the population, who are often of low socioeconomic position [20], this study aims to examine inequalities in CVD risk factors among immigrant and native populations using data from the 2017 Spanish National Health Survey; and whether these inequalities vary with educational attainment. We hypothesize that immigrants will have a higher prevalence of CVD risk factors than the native Spanish population.

Materials and methods

Study design and population

We conducted a cross-sectional design study among adults aged 25 to 64 using data from Spanish National Health Survey (SNHS) for 2017. The SNHS is a representative survey of the non-institutionalized Spanish population selected through a multi-stage stratified sampling. More detailed information on the methodology of this survey has been described elsewhere [27]. The study was based on information collected through a personal interview in selected households including 23,089 people, with a response rate of 74%. We excluded records of adults under 25 years of age (n = 1,645) because of their low prevalence of risk factors, lack of complete education and/or being unemployed. The latter makes it hard to assign a social class and employment status to those under 25 years of age. In addition, we excluded records of adults older than 65 years (n = 7,032) because they are less active among the native population and because the emigration unhealthy elderly immigrants tend to return to their home countries, a phenomenon refers to as “salmon bias” [28].

Variables

Consistent with the American Heart Society (AHA) [29], the dependent variable was a CVD risk factors summary score including 3 health risk factors (diabetes, cholesterol and hypertension) and 4 health risk behaviors (overweight / obesity, smoking, poor diet and physical inactivity). These health and behaviors risk factors were self-reported. Hypertension, high cholesterol and diabetes were defined using the answer to the question (yes/no) of whether your doctor had ever told you that you had hypertension, diabetes and cholesterol? Smoking status (yes/no) was defined by aggregating those who smoked daily, occasionally, and those who had previously smoked in the same category as smokers [30] and those who reported as not smokers. Overweight/obesity, calculated using self-reported weight and height, was defined according to the World Health Organization [31] as BMI ≥ 25 kg/m2,. For diet, the Healthy Eating Index (EHI) for the Spanish population was used [32]. The EHI includes 10 indicators, with a range from 0 to 100 with a score of less than 80 considered as an unhealthy diet. Physical inactivity was determined from the International Physical Activity Questionnaire Short Form (IPAQ-SF) by measuring the time in minutes of physical activity during the last week. Physical inactivity was defined as either <75 minutes per week of vigorous intensity activity<150 minutes per week of moderate intensity activity or <150 minutes per week of moderate and vigorous intensity activity [30]. Consistent with a previous study [33, 34], a score was created by summing the number of CVD risk factors, with a range of 0 to 7. We then used the sample median distribution of the score, ≥3 CVD risk-factors, as cut point [34] to specify the outcome.

Country of birth, the independent variable, was categorized as natives for those born in Spain and immigrants for those born in a country with a Human Development Index (HDI) <0.80 [35]. We further categorized immigrants according to the region of origin in Eastern Europe (non-European Union, Romania and Bulgaria), Latin America and Africa. Please see Appendix 1 for a list the countries included in each region of origin. Hereafter, we referred to country of birth as immigrant status and to the Spanish population as natives.

Consistent with other studies [36, 37], we included as covariates age (as a continuous variable), sex, educational attainment (primary, secondary and university), living arrangement (as a couple, others), and employment status (working, in unemployment and others). In addition, we included occupational social class. Social class was based on the of the head of household (current, last or never) following the Goldthorpe-oriented classification proposed by the Spanish Society of Epidemiology [38]. Five groups were identified (I Managers with >10 workers; II Managers with <10 workers; III Intermediary and self-employed; IV Supervisors, qualified and semi-qualified; V Non-qualified workers). Occupational social class was further categorized as non-manual workers (class I, II and III) and manual workers (class IV and V).

Of the 14,421 people who completed the individual questionnaire, we excluded those born in countries with a very high HDI (>0.80; n = 363) because they have similar or better CVD profile and socioeconomic position than the Spanish population [39] and records without information for any of the cardiovascular risk factors: cholesterol (n = 4), smoking (n = 10), BMI (n = 355), diet (n = 479) and physical inactivity (n = 14). In addition, we exclude records of those without information on occupational social class (n = 154), employment status (n = 21) and marital status (n = 19). Immigrants from Asia were also excluded due to small sample size (n = 65). These exclusions resulted in an analytical sample of 12,937 including 1,271 immigrants. Please see Appendix 2 for a comparison of included and excluded records.

Statistical analysis

Descriptive statistics for selected characteristics were calculated for the total population and by immigrant status. In addition, the prevalence estimates for CVD risk factors were calculated by immigrant status. Chi-squared of independence statistics were used to assess associations: 1) between each covariate and immigrant status, and 2) between the prevalence of CVD risk factors and immigrant status. Log binomial regression was used to quantify the association of immigrant status and cardiovascular risk factors before and after controlling for the selected covariates. In addition of educational attainment, we tested interactions terms of immigrant status with age and sex, in the fully-adjusted model because immigrants tend to be younger and more likely to be female [40] than the native population.

Data management procedures were carried out using SPSS 24.0. (IBM, Armonk, NY, USA) whereas the statistical analyses were conducted using SUDAAN 11.0.1 (RTI, Research Triangle Park, NC, USA) to take into account the complex sampling design and yield unbiased standard error estimates. Sample sizes presented in Tables 1 and 2 are unweighted. However, proportions, standard errors (SE), prevalence ratios (PR) and 95% confidence intervals (CI) are weighted.

thumbnail
Table 1. Distribution of selected characteristics for participants by region of origin: Spanish National Health Survey, 2017.

https://doi.org/10.1371/journal.pone.0242740.t001

thumbnail
Table 2. Prevalence of cardiovascular disease risk factors according to region of origin: Spanish National Health Survey 2017.

https://doi.org/10.1371/journal.pone.0242740.t002

Results

Table 1 shows the distribution of sociodemographic characteristics as well as CVD risk factors and health behaviors by immigrant status. Compared with Spanish native adults, immigrants were younger, with a higher proportion of women among those from Eastern Europe and Latin America but lower proportion of women among those from Africa, less educated. In addition, immigrants were more likely to be in the manual occupational social class, unemployed and lived with a partner, except for those from Latin America than natives (all p values <0.001). Regarding CVD risk health factors, immigrants reported lower prevalence of hypertension and cholesterol compared with natives (p-values <0.01). However, there were no differences in the prevalence of diabetes between natives and immigrant populations, although the highest prevalence of diabetes was observed among immigrants from Africa. Compared with natives, immigrants were less likely to be smokers (except among those from Europe), more likely to have an unhealthy diet (except among those from Africa) and more likely to be physically inactive (p-value <0.05). There was no difference in the prevalence of overweight/obesity between immigrants and natives.

The prevalence of CVD risk factors according to immigrant status is shown in Table 2. The mean CVD risk factor score was higher among immigrants from Eastern Europe ( = 3.1) and lower among those from Africa ( = 2.57) relative to Spanish natives (p-value <0.001). Compared with natives, immigrants from Eastern Europe had a higher prevalence of having at least three CVD risk factors, (73.0%) whereas those from Latin America (55.0%) and Africa (49.8%) had a lower prevalence estimates (p-value <0.001).

Table 3 presents the unadjusted and adjusted PRs and 95% CIs for CVD risk factors. When compared with natives, the probability of having at least three CVD risk factors 16% (PR1.16; 95%CI: 1.07, 1.26) greater among immigrants from Eastern Europe whereas the probabilities were 12% (PR: 0.88; 95% CI: 0.81, 0.95) and 21% (PR: 0.79; 95% CI: 0.70, 0.90) lower among immigrants from Latin America and Africa, respectively. After adjustment, the associations were significant among immigrants from Eastern Europe (PR: 1.25; 95% CI: 1.15, 1.35; Table 3) and from Africa (PR: 0.79; 95% CI: 0.69, 0.89) only. Appendix 3 presents the unadjusted and adjusted PRs and their 95% confidence intervals for region of origin for each CVD risk factor.

thumbnail
Table 3. Prevalence Ratios and their 95% confidence intervals for region of origin on the cardiovascular disease risk factors, Spanish National Health Survey 2017.

https://doi.org/10.1371/journal.pone.0242740.t003

Heterogeneity of the association between immigrant status and CVD risk factors was neither observed between immigrant status and age groups (p-interaction = 0.59) nor immigrant status and sex (p-interactions = 0.50). However, we observed heterogeneity in the association between immigrant status and CVD risk factors by educational attainment (p-interaction = 0.001). When compared with natives, the probability of having at least three CVD risk factors was greater in immigrants from Eastern Europe with primary and secondary educational attainment (PR: 1.15; 95% CI: 1.01, 1.31 and PR: 1.41; 95% CI: 1.29, 1.54, respectively), whereas the probability was lower among immigrants from Latin America (PR:0.86; 95% CI: 0.76, 0.98) and Africa (PR:0.74; 95% CI: 0.64, 0.85) with a primary educational attainment (Fig 1). It is worth noting that among immigrants from Latin American and African, the probability of having at least three CVD risk factors appears to increase with educational attainment.

thumbnail
Fig 1. Prevalence Ratios (PR) and 95% CI confidence intervals for region of origin on ≥3 CVD risk factors by educational attainment: Spanish National Health Survey 2017.

*Adjusted for age (continuous), sex, employment status and living arrangement.

https://doi.org/10.1371/journal.pone.0242740.g001

Discussion

This study showed inequalities in CVD risk factors between immigrants and natives in Spain. After adjustment for selected characteristics, we found a greater probability of having at least 3 CVD risk factors in immigrants from Eastern Europe and a lower probability among immigrants from Africa relative to Spanish natives. In addition, these associations varied with education attainment. Specifically, immigrants with less education from Eastern Europe were more likely to have at least three CVD risk factors compared with their Spanish native counterparts. However, in immigrants from Africa and Latin America, a primary level of education was protective against having at least three CVD risk factors relative to Spanish natives with the same educational attainment.

The differences in prevalence of CVD risk factors between the immigrant and native populations are largely dependent on place of birth [14, 15, 17, 23] type of CVD risk factor and host country of residence [16]. The latter is a consequence of regional differences and contextual factors including the degree of ethnic integration/acculturation, health beliefs and socioeconomic factors [18, 19]. Despite these differences, the evidence is consistent suggesting inequalities in CVD risk factors by region of birth. In our study, immigrants from Eastern Europe had a higher probability of having at least 3 CVD risk factors compared with natives. Related to our findings, Regidor et al. found higher CVD mortality rates among immigrants from Eastern Europe residing in Spain [21]. These high mortality rates observed among immigrants from Eastern Europe may be explained by the high prevalence of tobacco, overweight/obesity [41] and unhealthy diet [42] in their countries of origin. In fact, inequalities in CVD risk factors are related to increase risk of CVD morbidity and mortality [43]. In contrast, immigrants from Africa presented a better cardiovascular health profile, with a lower probability of having at least three CVD risk factors compared with natives. Limited evidence exists with regards to the changes in health behaviors such as diet, smoking habits and physical activity, in the host country for African immigrants. However, two studies in the Netherlands found lower prevalence of smoking [44] and a healthier diet among immigrants from Morocco, a group representing most of the African immigrant population in Spain, compared with their Dutch counterparts, regardless of socioeconomic position [45]. Thus, their lifestyle habits could explain the observed better cardiovascular profile in African immigrants in our study.

Despite the extensive evidence on the protective effect of high educational attainment on cardiovascular health [7, 8, 46, 47], this study shows that the effect of education differed among immigrants according to their regions of origin. Two previous studies, one in Norway [11] and another in the Netherlands [48] have examined the association of education with CVD risk factors, by place of birth. In both studies, educational attainment had a different effect for the immigrant and the native populations. These studies found that low educational attainment was associated with higher probability of CVD risk factors in immigrants compared to the native population with the exception of those from Morocco. Consistent with these findings, we observed that the probability of having at least three CVD risk factors was greater among immigrants from Eastern Europe with low educational attainment compared with natives. The opposite was true for immigrants from Africa and Latin America. Thus, high educational attainment may not carry health benefits for CVD risk in immigrants from Africa and Latin America. This differential effect may be related to structural discrimination in the labor market in Spain, which concentrates immigrants in the most precarious sectors regardless of their educational attainment, with little upward mobility. Specifically, immigrants from Africa have the greatest difficulties in accessing the labor market, with high unemployment rates and informal employment, and like immigrants from Latin America, high rates of job insecurity [49, 50]. Furthermore, this labor market is characterized by high levels of physical demand, low wages, and therefore, less access to resources and consumer goods. Hence, incorporation into the labor market requires immigrants to be in good health. These issues could explain the observed better cardiovascular profile associate with the lowest educational attainment among immigrants from Africa and Latin America.

This study is not without limitations. First, it is a cross-sectional study and does not allow us to make causal inferences or examine changes over time for CVD risk factors. Second, CVD risk factors were self-reported, which raises possible recall biases and social desirability. The biases if they were to occur, they may have been non-differential and could either over- or under-estimate our results toward the null. However, if we assume that immigrants face more barriers to access the health system, their probability of being diagnosed with hypertension, diabetes or high cholesterol levels may be lower than natives. The latter may lead to differential misclassification and a potential underestimation of the PRs we observed. Third, immigrants with lower levels of education and undocumented are less likely to participate in national and international survey [51]. However, while the overall response rate was 74% for the SNHS, country of origin was not a variable considered for stratification in the sampling design. Fourth, while there was not missing values observed for education in our population, we have missing values for several variables including CVD risk factors, employment and occupational social class. When compared with immigrants, natives were more likely to have missing values for all variables with the exception of cholesterol (Appendix 2). However, given the low percentage of missing values (<10%) relative to the analytical sample and the results presented in Tables 13, it is unlikely these exclusions have affected our results. Finally, given the limited sample size for the immigrant groups, it was not possible to examine length of stay in Spain by region of origin. Despite the small sample sizes and as a sensitivity analysis, we repeated the analyses presented in Table 3 accounting for length of stay among immigrants (Appendix 4). While we observed lower probabilities of at least three CVD risk factors among immigrants with at least 10 years of residence in Spain, the results were similar to the ones we presented in Table 3. Therefore, it is worth noting that acculturation, or the process by which foreign-born individuals adopt the culture and behaviors of the host country, may play a role [52]. Among the strengths of this study is the use of a large and representative sample of the Spanish adult population. The latter allows for the disaggregation by region of birth, as well as the examination of CVD clustering of risk factors and interactions of age, sex, and education with immigrant status.

Conclusions

Our findings contribute to the study of inequalities in CVD risk factors, according to region of birth. The latter is crucial to identify populations at risk for CVD morbidity and mortality. In addition, the study examines the joint effects of immigrant status and educational, attainment which are important determinants of health inequalities. The findings show that the burden of CVD risk factors among immigrants is affected by education. Thus, our findings underscore the need to consider immigrant status and educational attainment in the design of prevention and health promotion strategies. These strategies should account for both the highest and the lowest educational attainment of immigrants, given their differential effect according to region of birth. Using such approach could reduce both the burden of CVD outcomes and their inequalities among immigrants.

References

  1. 1. Collaborators GBDCoD. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1736–88. pmid:30496103; PubMed Central PMCID: PMC6227606.
  2. 2. Lennon RP, Claussen KA, Kuersteiner KA. State of the Heart: An Overview of the Disease Burden of Cardiovascular Disease from an Epidemiologic Perspective. Prim Care. 2018;45(1):1–15. pmid:29406937.
  3. 3. Timmis A, Townsend N, Gale CP, Torbica A, Lettino M, Petersen SE, et al. European Society of Cardiology: Cardiovascular Disease Statistics 2019. Eur Heart J. 2020;41(1):12–85. pmid:31820000.
  4. 4. Jagannathan R, Patel SA, Ali MK, Narayan KMV. Global Updates on Cardiovascular Disease Mortality Trends and Attribution of Traditional Risk Factors. Curr Diab Rep. 2019;19(7):44. pmid:31222515.
  5. 5. Bansilal S, Castellano JM, Fuster V. Global burden of CVD: focus on secondary prevention of cardiovascular disease. Int J Cardiol. 2015; 201 Suppl 1:S1–7. pmid:26747389.
  6. 6. Rosengren A, Smyth A, Rangarajan S, Ramasundarahettige C, Bangdiwala SI, AlHabib KF, et al. Socioeconomic status and risk of cardiovascular disease in 20 low-income, middle-income, and high-income countries: the Prospective Urban Rural Epidemiologic (PURE) study. The Lancet Global Health. 2019;7 (6):e748–e60. pmid:31028013
  7. 7. Veronesi G, Tunstall-Pedoe H, Ferrario MM, Kee F, Kuulasmaa K, Chambless LE, et al. Combined effect of educational status and cardiovascular risk factors on the incidence of coronary heart disease and stroke in European cohorts: Implications for prevention. Eur J Prev Cardiol. 2017;24(4):437–45. pmid:27837152.
  8. 8. Di Girolamo C, Nusselder WJ, Bopp M, Bronnum-Hansen H, Costa G, Kovacs K, et al. Progress in reducing inequalities in cardiovascular disease mortality in Europe. Heart. 2020;106(1):40–9. pmid:31439656; PubMed Central PMCID: PMC6952836.
  9. 9. Hossin MZ. International migration and health: it is time to go beyond conventional theoretical frameworks. BMJ Global Health. 2020;5 (2):e001938. pmid:32180999
  10. 10. Marmot M, Wilkinson RG. Social determinants of health: the solid facts. 2nd edition. Oxford: Oxford University Press; 2006.
  11. 11. Perini W, Agyemang C, Snijder MB, Peters RJG, Kunst AE. Ethnic disparities in educational and occupational gradients of estimated cardiovascular disease risk: The Healthy Life in an Urban Setting study. Scand J Public Health. 2018;46(2):204–13. pmid:28699411; PubMed Central PMCID: PMC5871022.
  12. 12. Sohail QZ, Chu A, Rezai MR, Donovan LR, Ko DT, Tu JV. The Risk of Ischemic Heart Disease and Stroke Among Immigrant Populations: A Systematic Review. Can J Cardiol. 2015;31(9):1160–8. pmid:26195229.
  13. 13. Bonilla-Escobar BA, Borrell LN, Del Cura-Gonzalez I, Sanchez-Perruca L, Escortell-Mayor E, Franco M. Type 2 diabetes prevalence among Andean immigrants and natives in a Southern European City. Acta Diabetol. 2020. pmid:32253608.
  14. 14. Fedeli U, Avossa F, Ferroni E, Schievano E, Bilato C, Modesti PA, et al. Diverging patterns of cardiovascular diseases across immigrant groups in Northern Italy. Int J Cardiol. 2018; 254:362–7. pmid:29246427.
  15. 15. Snijder MB, Galenkamp H, Prins M, Derks EM, Peters RJG, Zwinderman AH, et al. Cohort profile: the Healthy Life in an Urban Setting (HELIUS) study in Amsterdam, The Netherlands. BMJ Open. 2017;7 (12):e017873. pmid:29247091; PubMed Central PMCID: PMC5736025.
  16. 16. Liu R, So L, Mohan S, Khan N, King K, Quan H. Cardiovascular risk factors in ethnic populations within Canada: results from national cross-sectional surveys. Open Medicine. 2010;4(4):e143. pmid:21687334
  17. 17. Skogberg N, Laatikainen T, Koskinen S, Vartiainen E, Jula A, Leiviska J, et al. Cardiovascular risk factors among Russian, Somali and Kurdish migrants in comparison with the general Finnish population. Eur J Public Health. 2016;26(4):667–73. pmid:27060592.
  18. 18. Agyemang C, Kunst A, Bhopal R, Zaninotto P, Unwin N, Nazroo J, et al. A cross-national comparative study of blood pressure and hypertension between English and Dutch South-Asian- and African-origin populations: the role of national context. Am J Hypertens. 2010;23(6):639–48. pmid:20300070.
  19. 19. Agyemang C, Kunst A, Bhopal R, Zaninotto P, Nazroo J, Nicolaou M, et al. Dutch versus English advantage in the epidemic of central and generalised obesity is not shared by ethnic minority groups: comparative secondary analysis of cross-sectional data. Int J Obes (Lond). 2011;35(10):1334–46. pmid:21326206.
  20. 20. National Institute of Statistics of Spain NIE. Population Figures at 1 January 2019. Available online: https://www.ine.es/prensa/cp_j2019_p.pdf (accessed on 15 October 2019).
  21. 21. Regidor E, Astasio P, Calle ME, Martinez D, Ortega P, Dominguez V. The association between birthplace in different regions of the world and cardiovascular mortality among residents of Spain. Eur J Epidemiol. 2009;24(9):503–12. pmid:19557526.
  22. 22. Ruiz-Ramos M, Juarez S. [All-cause and cause-specific mortality in the immigrant and native-born populations in Andalusia (Spain)]. Gac Sanit. 2013;27 (2):116–22. pmid:22633801.
  23. 23. Cainzos-Achirica M, Vela E, Cleries M, Bilal U, Mauri J, Pueyo MJ, et al. Cardiovascular risk factors and disease among non-European immigrants living in Catalonia. Heart. 2019. pmid:30819763.
  24. 24. Lozano Sanchez ML, Leal Hernandez M, Abellan Huerta J, Gomez Jara P, Ortin Ortin EJ, Abellan Aleman J. [Cardiovascular risk of immigrants living in Spain according to origin and years of stay]. Aten Primaria. 2013;45(2):92–100. pmid:23164796.
  25. 25. Soriano JB, Rojas-Rueda D, Alonso J, Anto JM, Cardona PJ, Fernandez E, et al. The burden of disease in Spain: Results from the Global Burden of Disease 2016. Med Clin (Barc). 2018;151(5):171–90. pmid:30037695.
  26. 26. Gullon P, Diez J, Cainzos-Achirica M, Franco M, Bilal U. Social inequities in cardiovascular risk factors in women and men by autonomous regions in Spain. Gac Sanit. 2020. pmid:32674863.
  27. 27. García-Mayor J, Moreno-Llamas A, De la Cruz-Sánchez E. Smoking prevalence and health-related lifestyle behaviours according to tobacco use after the smoke-free law in Spain: analysis of Spanish National Health Surveys 2009–2017. Rev Esp Salud Pública. 2019;93.
  28. 28. Abraido-Lanza AF, Dohrenwend BP, Ng-Mak DS, Turner JB. The Latino mortality paradox: a test of the "salmon bias" and healthy migrant hypotheses. Am J Public Health. 1999;89(10):1543–8. pmid:10511837; PubMed Central PMCID: PMC1508801.
  29. 29. Lloyd-Jones DM, Hong Y, Labarthe D, Mozaffarian D, Appel LJ, Van Horn L, et al. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association's strategic Impact Goal through 2020 and beyond. Circulation. 2010;121(4):586–613. pmid:20089546.
  30. 30. Peng Y, Wang Z. Association of Life's Simple 7 and presence of cardiovascular disease in general Australians. Open Heart. 2017;4 (2):e000622. pmid:28878949; PubMed Central PMCID: PMC5574438.
  31. 31. World Health Organization (WHO). Global Database on Body Mass Index. 2013. Available online:http://www.who.int/bmi (accessed on 1 September 2020).
  32. 32. Norte Navarro AI, Ortiz Moncada R. Calidad de la dieta española según el índice de alimentación saludable. Nutr Hosp. 2011; 26:330–6. pmid:21666971
  33. 33. Jin K, Gullick J, Neubeck L, Koo F, Ding D. Acculturation is associated with higher prevalence of cardiovascular disease risk-factors among Chinese immigrants in Australia: Evidence from a large population-based cohort. Eur J Prev Cardiol. 2017;24(18):2000–8. pmid:29064273.
  34. 34. Commodore-Mensah Y, Ukonu N, Cooper LA, Agyemang C, Himmelfarb CD. The Association Between Acculturation and Cardiovascular Disease Risk in Ghanaian and Nigerian-born African Immigrants in the United States: The Afro-Cardiac Study. J Immigr Minor Health. 2018;20(5):1137–46. pmid:28852948.
  35. 35. Human Development Report 2014 (UNDP). Sustaining Human Progress: Reducing Vulnerabilities and Building Resilience. Available at http://hdr.undp.org/sites/default/files/hdr14-report-en-1.pdf.
  36. 36. Grossmann FF, Leventhal ME, Auer-Boer B, Wanner P, Bischoff A. Self-reported cardiovascular risk factors in immigrants and Swiss nationals. Public Health Nurs. 2011;28(2):129–39. pmid:21732967.
  37. 37. Raza Q, Nicolaou M, Dijkshoorn H, Seidell JC. Comparison of general health status, myocardial infarction, obesity, diabetes, and fruit and vegetable intake between immigrant Pakistani population in the Netherlands and the local Amsterdam population. Ethn Health. 2017;22(6):551–64. pmid:27748128.
  38. 38. Domingo-Salvany A, Bacigalupe A, Carrasco JM, Espelt A, Ferrando J, Borrell C, et al. [Proposals for social class classification based on the Spanish National Classification of Occupations 2011 using neo-Weberian and neo-Marxist approaches]. Gac Sanit. 2013;27(3):263–72. pmid:23394892.
  39. 39. Malmusi D, Borrell C, Benach J. Migration-related health inequalities: showing the complex interactions between gender, social class and place of origin. Soc Sci Med. 2010;71(9):1610–9. pmid:20869798.
  40. 40. Economic and Social Committee ESC. [Immigration in Spain: effects and opportunities]. 2019. Available online http://www.ces.es/documents/10180/5209150/Inf0219.pdf (accessed on 30 October 2020).
  41. 41. Pikhart H, Bobak M, Malyutina S, Pajak A, Kubinova R, Marmot M. Obesity and education in three countries of the Central and Eastern Europe: the HAPIEE study. Cent Eur J Public Health. 2007;15(4):140–2. pmid:18251227.
  42. 42. Boylan S, Welch A, Pikhart H, Malyutina S, Pajak A, Kubinova R, et al. Dietary habits in three Central and Eastern European countries: the HAPIEE study. BMC Public Health. 2009; 9:439. pmid:19951409; PubMed Central PMCID: PMC2791768.
  43. 43. Palazon-Bru A, Ferri-Rufete D, Mares-García E, Durazo-Arvizu RA, Divison-Garrote JA, Carbayo-Herencia JA, et al. Clusters of Cardiovascular Risk Factors and Their Impact on the 20-Year Cardiovascular Risk in a General Population. J Cardiovasc Nurs. 2020;35(2):210–6. pmid:31904694
  44. 44. Visser MJ, Ikram UZ, Derks EM, Snijder MB, Kunst AE. Perceived ethnic discrimination in relation to smoking and alcohol consumption in ethnic minority groups in The Netherlands: the HELIUS study. Int J Public Health. 2017;62(8):879–87. pmid:28508943; PubMed Central PMCID: PMC5641269.
  45. 45. Mackenbach JP, Kulhanova I, Menvielle G, Bopp M, Borrell C, Costa G, et al. Trends in inequalities in premature mortality: a study of 3.2 million deaths in 13 European countries. J Epidemiol Community Health. 2015;69(3):207–17; discussion 5–6. pmid:24964740.
  46. 46. Jankovic J, Davidovic M, Bjegovic-Mikanovic V, Jankovic S. Status of cardiovascular health in the Republic of Serbia: Results from the National Health Survey. PLoS One. 2019; 14(3):e0214505. pmid:30917180; PubMed Central PMCID: PMC6436747.
  47. 47. Graciani A, Leon-Munoz LM, Guallar-Castillon P, Rodriguez-Artalejo F, Banegas JR. Cardiovascular health in a southern Mediterranean European country: a nationwide population-based study. Circ Cardiovasc Qual Outcomes. 2013;6(1):90–8. pmid:23300271.
  48. 48. Agyemang C, van Valkengoed I, Hosper K, Nicolaou M, van den Born BJ, Stronks K. Educational inequalities in metabolic syndrome vary by ethnic group: evidence from the SUNSET study. Int J Cardiol. 2010;141(3):266–74. pmid:19144421.
  49. 49. Ballester R, Velazco J, Rigall-I-Torrent R. Effects of the Great Recession on Immigrants’ Household Consumption in Spain. Social Indicators Research. 2014;123(3):771–97.
  50. 50. Domingo A, Gil-Alonso F. Immigration et évolution de la structure de la main-d'œuvre au Sud de l'Union européenne. Population. 2007;62(4):825.
  51. 51. Monge S, Ronda E, Pons-Vigues M, Vives Cases C, Malmusi D, Gil-Gonzalez D. [Methodological limitations and recommendations in publications on migrant population health in Spain]. Gac Sanit. 2015;29(6):461–3. pmid:26387460.
  52. 52. Andreeva VA, Unger JB. Host society acculturation and health practices and outcomes in the United States: public health policy and research implications worldwide. J Public Health Policy. 2014; 35(3):278–91. pmid:24694944.