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International Journal of Public Health

, Volume 58, Issue 3, pp 427–434 | Cite as

Are barriers in accessing health services in the Roma population associated with worse health status among Roma?

  • Pavol JarcuskaEmail author
  • Daniela Bobakova
  • Jan Uhrin
  • Ladislav Bobak
  • Ingrid Babinska
  • Peter Kolarcik
  • Zuzana Veselska
  • Andrea Madarasova Geckova
  • HEPA-META team
Original Article

Abstract

Objectives

The health of Roma has been found to be poorer than that of the majority population. The aim of this study was to explore the differences between Roma and non-Roma regarding perceived barriers in accessing health services. Furthermore, we aimed to assess the association between self-rated health status and Roma ethnicity and explore to what degree barriers in accessing health services explain this association.

Methods

We used data from the cross-sectional HepaMeta study conducted in 2011 in Slovakia. The final sample comprised 452 Roma (mean age 34.7; 35.2 % men) and 403 (mean age 33.5; 45.9 % men) non-Roma respondents.

Results

Roma ethnicity was found to be significantly associated with poorer self-rated health status. A considerable part of this association can be explained by barriers in accessing health services as perceived by Roma.

Conclusions

Worse health in Roma is partially mediated by worse access to health services, apart from a large educational gap between Roma living in settlements and the majority population. Interventions should focus not only on health literacy among Roma but also on the health care system and health care professionals.

Keywords

Roma Ethnicity Self-rated health Access to health services Health inequalities Slovakia 

Introduction

Roma are an extremely diverse population, with multiple subgroups based on language, history, religion and occupations (Koupilova et al. 2001). They live all over the world, but they are concentrated mostly in the Central Europe and the Balkans. To the best of our knowledge, the most realistic estimate of the Roma population in Slovakia comes from the Demographic Research Centre, which indicates that about 380,000 Roma, or 7.2 % of the total population, are currently living in the Slovak Republic (Filadelfiova et al. 2007; Reynolds 2005).

The health of Roma people has been found to be poorer than that of the majority population (Zeman et al. 2003; Hajioff and McKee 2000; Van Cleemput et al. 2007). Although studies regarding the health of Roma are scarce, we can find several studies that report higher infant mortality rates (rates are between 2 and 6 and differ within countries) and a shorter life expectancy among Roma than among the majority population (Rosicova et al. 2011; Sepkowitz 2006). In general, Roma men and women live 10–15 years shorter than their non-Roma counterparts from the same region (Sepkowitz 2006), have a higher prevalence of different diseases, such as coronary artery disease, obesity, hyperlipidaemia and diabetes mellitus, compared with the majority population and more frequently experience health problems/complaints (Sepkowitz 2006). Moreover, accumulation of several biological and behavioural risk factors for cardiovascular diseases was identified in Roma (Babinska et al. 2013; Carrasco-Garrido et al. 2011). Published studies on the health of the Roma are often fragmentary and burdened with methodological problems (Voko et al. 2009). Very few studies (Filadelfiova et al. 2007; Kosa et al. 2007; Janevic et al. 2012) asked respondents to report their own perception of their health status (self-rated health). Self-rated health has been shown to have multiple independent health-related correlates, including medical diagnosis, health complaints and mortality (Gold et al. 1996).

Health inequalities in Central and Eastern Europe seem to be larger in comparison to the rest of the Europe, and these differences might be attributed in part to smoking, alcohol use and access to health care (Mackenbach et al. 2008). Worse health of Roma might be mediated by worse access to good quality health care (Erasmus MC-University Medical Centre Rotterdam Rotterdam 2007). While several studies on the health status of Roma have been carried out, an assessment of Roma access to health care is fragmentary. A number of factors, which crucially influence access to health care and quality of treatment, have not been adequately studied (European Roma Rights Centre 2006). A report of the ERRC (European Roma Rights Centre 2006 reveals systemic exclusion of Roma from key aspects of health care. In some areas, it appears that Roma may only have access to health care in the context of emergency care and/or in the immediate circumstances of childbirth. Roma throughout Europe are excluded from preventive, primary and specialised health services, and numerous Romani women have no access to pre and postnatal health care (European Roma Rights Centre 2006).

The aim of this study was to explore the differences between Roma and non-Roma regarding perceived barriers in accessing health services. Furthermore, we aimed to assess the association between self-rated health status and Roma ethnicity and explore to what degree barriers in accessing health services explain this association.

Methods

We used data from the cross-sectional HepaMeta study conducted in 2011 in Slovakia. This project aimed to map the prevalence of viral hepatitis B/C and metabolic syndrome in the population living in separated and segregated Roma settlements and to compare it with the occurrence of the same health indicators in the majority population in regard to the selected risk and protective factors of these health indicators.

Sample and procedure

The highest concentrations of the Roma population in Slovakia can be found in the eastern part of the country (Slusna 2010). Therefore, the target population was residents of Roma settlements in the Kosice region aged 18–55, and the control group was the majority population in the same region and of the same age composition. The majority population was divided into two subgroups: majority population with (46 %) and without (54 %) Roma population living in the vicinity.

We randomly selected 37 separated or segregated Roma settlements with at least 300 inhabitants from each district of Kosice region. We identified the general practitioners (GPs) who provided primary care for the inhabitants of these settlements, yielding 30 GPs. From these, we randomly selected 19 who were contacted and 12 agreed to participate (response rate 63 %). For the majority population, we identified areas with socially diverse population without Roma community in the vicinity where we randomly chose seven general practitioners. Five agreed to participate in our study (response rate 71 %).

A Roma sample stratified in regard to gender and age was recruited directly in the settlements by cooperating with local Roma community workers. From all the Roma who were present in the settlements and received information about our study, 452 Roma participated. Since the recruitment of Roma patients was carried out under the unpredictable conditions of Roma settlements, we were unable to record and compute the response rate. Respondents from majority population were randomly chosen from the list of patients provided by the general practitioners. These patients were contacted via phone and mail by trained research assistants, who provided information about our study and invited them to participate. Further details of recruitment of the Roma and non-Roma population can be seen in Fig. 1.
Fig. 1

Recruitment of the Roma and non-Roma population (Kosice Region, Slovakia, 2011)

Detailed information about our study and its procedures was given to all patients and informed consent was signed prior to medical check-ups. Trained medical personnel collected the blood and urine samples and performed anthropometric measures in the surgeries of cooperating general practitioners. For the majority population, trained assistants were present in the surgeries to assist with the questionnaires, if needed. Roma respondents were interviewed individually by trained community workers and assistants in community centers. We used an assisted self-administered interview adapted from other methods of collecting survey data which seem to have the smallest impact on the data reliability (Tourangeau and Smith 1996). The study was approved by the Ethics Committee of the Medical Faculty at Safarik University in Kosice. Participation in the study was fully voluntary and anonymous. Inclusion criteria for the respondents were as follows: no preventive medical check-up in the past 2 years, no acute illness, appropriate age and be able to take a time off from the work during the week of data collection in the surgery of their general practitioner. The final sample comprised 452 Roma (mean age 34.7; SD 9.14; 35.2 % men) and 403 (mean age 33.5; SD 7.4; 45.9 % men) non-Roma respondents.

Measures

Self-rated health was measured by asking respondents the question: “Would you say your health is: Excellent/Good/Fair/Poor?” (Idler and Benyamini 1997; Currie et al. 2008). The responses Excellent and Good were merged into the category “Good health status” and the responses Fair and Poor were merged into the category “Poor health status”.

Barriers in accessing health services were measured by asking respondents the question: “What are the main reasons for your difficulties in seeking and providing the necessary health services needed? Mark each alternative which concerns your difficulties.” Possible responses were: 1) I do not have enough money for medication and transportation to a doctor. 2) I do not know where to seek health services/I cannot orientate in the city/village. 3) I have a very bad traffic connection to health services. 4) I do not trust health care professionals. 5) I once had a bad experience when visiting a doctor, I fear the examination. 6) I have difficulties with providing babysitting for my children when I or one of my children needs to see a doctor. 7) I prefer to treat myself at home using my own curative methods. The items were previously tested in pilot study and were carefully selected by expert group consisted from Roma health mediators and community workers, public health experts and academics. Factor analysis was used and one factor was then extracted—all 7 items loaded into one factor with factor loadings varying from 0.44 to 0.64. Kaiser–Meyer–Olkin measure of sampling adequacy was 0.79 and Bartlett’s test of sphericity was significant (p < 0.001). Highest education as a socio-economic position indicator was measured by asking respondents the question: “What is your highest educational degree attained?” Possible responses were: Unfinished elementary/Finished elementary/Apprenticeship/Secondary/University. We merged first two categories into one category: Elementary and last two categories into one category: Higher education.

Statistical analyses

First, we used Chi-square statistics and independent samples T test to explore the differences between Roma and non-Roma regarding independent and outcome variables. Next, we explored the distribution of particular barriers in accessing health services among Roma and non-Roma using Chi-square statistics. Finally, logistic regression analysis was used to assess differences in self-rated health by ethnicity and the degree to which barriers in accessing health services could account for these ethnic differences. Model 1 tested the crude association of self-rated health with ethnicity. Model 2 was adjusted for gender and age. Model 3 was adjusted for barriers in accessing health services in order to explore whether this would explain the associations with ethnicity. Furthermore, we tested interaction of ethnicity with highest education. We also assessed the interactions between highest education and barriers in accessing health services. All data were analysed using IBM SPSS 20 and Stata 11.

Results

There are significantly more women, those reported poor self-rated health and those with lower education among Roma in comparison to non-Roma and Roma (Table 1). Occurrence of particular barriers in access to health services was significantly higher among Roma in comparison to non-Roma (Table 2). Roma living in a settlements reported the lack of the money for medication and transport (43.6 vs. 5.2 %), bad traffic connection (12.8 vs. 3.2 %) and bad experience, fear or lack of trust (17.2 vs. 5.7 %) significantly more frequently than non-Roma. Preference of own curative methods was also highly prevalent among Roma (14.4 vs. 6.0 %).
Table 1

Distribution of covariates among Roma and non-Roma (Kosice Region, Slovakia, 2011)

 

Non-Roma

Roma

Total

Roma vs. non-Roma

N = 403

%

N = 452

%

N = 855

%

p value

Gender

<0.01a

 Men

185

45.9

159

35.2

344

40.2

 Women

218

54.1

293

64.8

511

59.8

Self-rated health

<0.001a

 Good health status

324

82.9

264

59.3

588

70.3

 Poor health status

67

17.1

181

40.7

248

29.7

Highest education

<0.001a

 Higher

300

76.3

10

2.3

310

37.1

 Apprenticeship

84

21.4

73

16.5

157

18.8

 Elementary

9

2.3

360

81.3

369

44.1

Difficulty in access HS, mean (SD)

0.24 (0.54)

1.05 (1.34)

N = 857

<0.001b

aChi-square tests

b T test

Table 2

Distribution of particular difficulties in access to health services among Roma and non-Roma (Kosice Region, Slovakia, 2011)

 

Non-Roma

Roma

Total

Roma vs. non-Roma

N = 403

%

N = 452

(%)

N = 855

%

p value

Lack of money

21

5.2

197

43.6

218

25.5

<0.001

Bad orientation

5

1.2

38

8.4

43

5.0

<0.001

Bad traffic connection

13

3.2

58

12.8

71

8.3

<0.001

Do not trust

7

1.7

29

6.4

36

4.2

<0.001

Bad experience/fear

16

4.0

49

10.8

65

7.6

<0.001

No babysitting for children

9

2.2

35

7.7

44

5.1

<0.001

Own curative methods

24

6.0

65

14.4

89

10.4

<0.001

Roma have more than 3 times higher chance to report poor self-rated health in comparison to non-Roma (Table 3, Model 1) and adjusting for gender and age decrease likelihood of reporting poor self-rated health among Roma only slightly (Table 3, Model 2). Perception of barriers in access to health care increased the likelihood of reporting poor self-rated health (Table 3, Model 3) and adding barriers in accessing health services into the model decreased the association between self-rated health and Roma ethnicity by 23.5 % (Table 3, Model 3). Significant interaction of ethnicity with highest education indicates increasing effect of ethnicity on self-rated health with decreasing level of highest education (Table 4). We omitted main effects of ethnicity and highest education in this analysis because with significant interaction, main effects lose their meaning, since the effects are crossed. Roma with lowest level of education (unfinished elementary or elementary education only) have 2.64 times higher chance to report poor self-rated health in comparison to non-Roma with higher level of education (secondary or university education). Similarly, Roma with middle level of education (apprenticeship) have 2.04 times higher chance to report poor self-rated health in comparison to non-Roma with higher level of education (secondary or university education). We also assessed whether the effect of barriers in accessing health services on likelihood of reporting poor self-rated health was modified by highest education, and this did not show any statistically significant interaction effects (not shown).
Table 3

Self-rated health in Roma, crude and with adjustment for gender, age, and difficulty in access to health services (HS): odds ratios (OR) and 95 % confidence intervals (CI) (Kosice Region, Slovakia, 2011)

Self-rated health

Model 1, OR (95 % CI)

Model 2, OR (95 % CI)

Model 3, OR (95 % CI)

Ethnicity

 Non-Roma

1 (reference)

1 (reference)

1 (reference)

 Roma

3.27 (2.36–4.52)***

3.18 (2.28–4.43)***

2.66 (1.87–3.78)***

Gender

 Men

 

1 (reference)

1 (reference)

 Women

 

1.08 (0.78–1.49)

1.11 (0.80–1.54)

Age

 

1.05 (1.03–1.07)***

1.05 (1.03–1.07)***

Difficulty in access HS

  

1.25 (1.08–1.44)**

p < 0.05, ** p < 0.01, *** p < 0.001

Table 4

The interaction between Ethnicity and Highest education, odds ratios (OR) and 95 % confidence intervals (CI) (Kosice Region, Slovakia, 2011)

Self-rated health

OR (95 % CI)

Gender

 Men

1 (reference)

 Women

1.13 (0.81–1.57)

Age

1.05 (1.03–1.07)***

Difficulty in access HS

1.30 (1.11–1.52)**

Ethnicity by highest education

 Higher

1 (reference)

 Apprenticeship

2.04 (1.15–3.62)*

 Elementary

2.64 (1.19–3.75)***

p < 0.05, ** p < 0.01, *** p < 0.001

Discussion

The aim of this study was to explore the differences between Roma and non-Roma regarding perceived barriers in accessing health services. Furthermore, we aimed to assess the association between self-rated health status and Roma ethnicity and explore to what degree barriers in accessing health services explain this association. Roma in comparison to non-Roma have three times higher chance to report worse self-rated health. Worse self-rated health among Roma seems to be partially explained by their worse access to health services. Roma reported the lack of money for medication and transport and bad experience, fear or lack of trust to be the most common barriers they perceive. These barriers can be understood as institutional and intrapersonal discrimination of Roma which affect health condition of this highly discriminated group (Bastos and Faerstein 2012). However, differences in the use of health care services might arise from differences in social norms, values and health beliefs such as the purity of the body or fatalism which are typical for Roma (Zeman et al. 2003; Vivian and Dundes 2004; Van Cleemput et al. 2007). Highest educational degree attained further explains ethnic differences in self-rated health, but does not seem to play the role in the association between barriers in accessing health services and poorer self-rated health status. No interaction was found between barriers in access to health services and highest education. It might be caused by relatively small numbers of respondents for some of the combinations of ethnicity and education, what limits the power of these analyzes. Salloway (in Puporka and Zadori 1999) reported that Roma simply have access to the worst quality services and this is why they do not like to use them, which leads to worse health. According to Mackenbach et al. (2008), there are also differences between socio-economic groups in the way of using health services. Lower socio-economic groups such as Roma more often use forgone health care and less often use preventive care compared to higher socio-economic groups who prefer specialist care (Mackenbach et al. 2008).

Roma perceive significantly more barriers in accessing health services compared with non-Roma. Barriers in accessing health services perceived by Roma might arise from the nature of separated or segregated Roma settlements, which suffer from a high degree of deprivation. It may also be a consequence of discrimination, health beliefs and behavioural differences, or resistance to assimilation leading to the non-use of various services (Kolarcik et al. 2009). Worse access to health services in Roma has previously been widely discussed by experts (Kolarcik et al. 2009; Lynch 2006; Kosa et al. 2007; Koupilova et al. 2001; Masseria et al. 2010; Peters et al. 2009), but only scarce evidence exists on barriers in accessing health services (European Roma Rights Centre 2006; Fundacion Secretariado Gitano (FSG) 2009).

Roma from our study reported the lack of money (43.6 %) for medication and transportation to be the most common difficulty they perceive. According to the Slovak constitution, everybody has the right to access basic health care free of charge (Constitution-40). Puporka and Zadori (1999) extended the idea about access to health services among Roma. They stated that even though health care should be accessible and free of charge for everybody, certain health care services require payment (dental care). The poor financial status of Roma often makes them unable to pay even small charges, which makes their access to the health care worse. They also brought up the idea of costs for travelling from a patient’s residence to a health care institution as a potential difficulty (Puporka and Zadori 1999). This supports our findings, although we have doubts about whether Roma have the proper information about their rights regarding health services (Marcincin and Marcincinova 2009).

Additional common barriers reported by Roma were that they prefer to treat themselves at home using their own curative methods, have a bad traffic connection and have previously had a bad experience when visiting a doctor. These barriers have been previously discussed by some authors, which support our findings. Self-treatment in particular seems to be typical for Roma unless the pain is unbearable. Health complaints other than pain or fever are not considered to be serious enough by Roma to visit the doctor (Puporka and Zadori 1999). Moreover, preferring traditional curative methods is still possible in separated and segregated Roma settlements (Puporka and Zadori 1999) of the kind we examined. A bad traffic connection as one of barriers seems to be rather logical, arising from the essential nature of separated and segregated settlements, which often have the nearest traffic connection several kilometres away. A bad experience from visiting a doctor might be caused by the unfriendly or even rude attitudes of doctors or nurses (Lynch 2006), which might lead to reluctance to visit the doctor again. We witnessed such attitudes during the data collection.

Differences found in self-rated health between Roma and non-Roma are in line with previous studies (Van Cleemput et al. 2007; Hajioff and McKee 2000; Zeman et al. 2003). Findings from studies comparing self-rated health of Roma and non-Roma population support our findings regarding worse health and extremely low educational level of Roma (Kosa et al. 2007; Janevic et al. 2012). We found 80 % of Roma attained at most an elementary education, which represents a hugely significant gap between Roma living in separated or segregated settlements and the majority population. Results of interactions revealed an important role of education in regard to health of Roma population. Roma compared to non-Roma seem to be more sensitive on the effect of highest education on self rated health, or in other words, the undesirable effect of living in Roma settlements and having low education cumulate and significantly contribute to gap in health between Roma and non Roma population. Living in a Roma settlements indicates an accumulation of socio-economic disadvantages like segregation, poor housing, overcrowding, limited access to drinking water and a lack of sewage systems, and these communities experience generational poverty, a high prevalence of long-term unemployment, a low educational level and high risk of discrimination, violence and usury (Derevjanikova 2010; Filadelfiova et al. 2007; Marcincin and Marcincinova 2009; Vasecka and Dzambazovic 2000; European Union Agency for Fundamental Rights 2009; Schaaf 2011). Our findings support the part of puzzle in the explanation of poor health status of Roma which can be explained by (1) different socio-economic characteristics (living conditions, access to sources and services, extended poverty, territorial segregation), (2) cultural differences (health literacy, health-related behaviour, e.g. nutritional habits, use of psychoactive substances, physical activity and disease prevention), (3) psychosocial factors (stress from discrimination and social exclusion, depression, hopelessness and life satisfaction), (4) biological and genetic differences and (5) disadvantages accumulation (Rosicova et al. 2009; Gourgoulianis et al. 2000; Krajcovicova-Kudlackova et al. 2004; Petek et al. 2006; Panzarella et al. 2006; Proctor et al. 2009; Stansfeld et al. 1998).

Strengths and limitations

The strengths of our study are that it comprises a considerable representative sample of a hard-to-reach population living in separated or segregated Roma settlements. We were able to compare them with the majority population living in the same geographical area, although our results should be generalised with caution, as Roma are a very heterogeneous group in terms of living conditions and levels of integration, thus our results can be generalized only to the Roma population living in Roma settlements.

A limitation of our study may be that data from the Roma were collected via an interview, and data from the non-Roma came via self-reported questionnaires. The reason for this was to cope with illiteracy among the Roma, which we considered to be a more serious source of non-response and bias than using two different types of administration. In Roma, we used the technique of assisted self-administration, which has shown good reliability of data (Tourangeau and Smith 1996). Moreover, using this technique was found to be a good decision, as most of Roma were not able to fill in questionnaires without assistance.

Another limitation may be the low response rate (56 %) of the majority population. The main reasons for non-response were that respondents had already undergone a preventive check-up in the past 2 years or were not able to take a time off from work during the week of data collection in the surgery of their general practitioner. Since recruitment of the Roma sample took place directly in settlements under specific circumstances, it was not possible to follow the number of Roma asked to participate and the number of refusals and later calculate the response rate. The main reasons for non-response were fear of giving a blood sample and reluctance or fear of visiting a general practitioner.

Implications

Our results suggest that worse health among Roma compared with non-Roma is mediated by worse access to health services, apart from a large educational gap between Roma and non-Roma. A part of the barriers in accessing health services apparently arises from the nature of separated and segregated Roma settlements (e.g. transport). Another important factor is cultural divergence regarding health belief and the attitudes of Roma and their distrust of the health care system arising from previous experiences. These findings offer scientific background for social and community workers and their potential interventions. Not only interventions regarding health literacy among Roma are important but also interventions regarding prejudices among health-care professionals. Health care professionals should be aware of the limitations and specifics of working with Roma and their special needs and should be able to effectively communicate and work with them in regard to the overall positive effect on the global health of the population, including Roma. This might be transferable also to other countries and other ethnic minorities as problems and associations explored in our study apply to these as well (Mackenbach et al. 2008). Future research should then focus on the validation of interventions put into practice and bring deeper insight into Roma needs regarding the health care system.

Conclusion

Worse health in Roma compared with non-Roma is partially mediated by worse access to health services, apart from the large educational gap between Roma living in separated or segregated Roma settlements and the majority population. Interventions should focus not only on health literacy among Roma but also on “Roma literacy” among health care professionals and policy makers, and should address prejudices, cultural divergence, effective communication and the specifics of working with Roma patients.

Notes

Acknowledgments

This project was partially supported by Roche Slovensko, s.r.o., and the Agency of the Slovak Ministry of Education for the Structural Funds of the EU, under project ITMS: 26220120058 (40 %).

References

  1. Babinska I, Veselska Z, Bobakova D et al (2013) Is the cardiovascular risk profile of people living in Roma settlements worse in comparison with the majority population in Slovakia? Int J Pub Health (accepted)Google Scholar
  2. Bastos JL, Faerstein E (2012) Conceptual and methodological aspects of relations between discrimination and health in epidemiological studies. Cad Saude Publica 28(1):177–183PubMedCrossRefGoogle Scholar
  3. Carrasco-Garrido P, Lopez de Andres A, Hernandez Barrera V, Jimenez-Trujillo I, Jimenez-Garcia R (2011) Health status of Roma women in Spain. Eur J Public Health 21:793–798PubMedCrossRefGoogle Scholar
  4. Currie C, Gabhainn SN, Godeau E et al (2008) Inequalities in young people’s health: health behaviour in school-aged children (HBSC) international report from the 2005/2006 survey. Health policy for children and adolescentsGoogle Scholar
  5. Derevjanikova S (2010) Socialnopravna ochrana deti z marginalizovanych romskych komunit (Social and legal protection of children from marginalized Roma communities). In: Socialni, ekonomicke, pravni a bezpecnostni otazky soucasnosti (Social, economical, legal, and safety issues of the present). Private University College of Economic Studies, Ltd., PragueGoogle Scholar
  6. Erasmus MC, University Medical Centre Rotterdam (2007) Tackling health inequalities in Europe: an integrated approach. Department of Public health, University Medical Centre Rotterdam, The NetherlandsGoogle Scholar
  7. European Roma Rights Centre (2006) Ambulance not on the way: the disgrace of health care for Roma in Europe. Westimprim bt, BudapestGoogle Scholar
  8. European Union Agency for Fundamental Rights (2009) EU-MIDIS European Union Minorities and Discrimination Survey. http://fra.europa.eu/fraWebsite/eumidis/index_en.htm
  9. Filadelfiova J, Gerbery D, Skobla D (2007) Report on the living conditions of Roma in Slovakia. United Nations Development Programme, Regional Bureau for Europe, BratislavaGoogle Scholar
  10. Fundacion Secretariado Gitano (FSG) (2009) Health and the Roma community: analysis of the situation in Europe. FSG, MadridGoogle Scholar
  11. Gold M, Franks P, Erickson P (1996) Assessing the health of the nation. The predictive validity of a preference-based measure and self-rated health. Med Care 34:163–177PubMedCrossRefGoogle Scholar
  12. Gourgoulianis KI, Tsoutsou P, Fotiadou N et al (2000) Lung function in gypsies in Greece. Arch Environ Health 55:453–454PubMedCrossRefGoogle Scholar
  13. Hajioff S, McKee M (2000) The health of the Roma people: a review of the published literature. J Epidemiol Commun H 54:864–869CrossRefGoogle Scholar
  14. Idler EL, Benyamini Y (1997) Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav 38:21–37PubMedCrossRefGoogle Scholar
  15. Janevic T, Jankovic J, Bradley E (2012) Socioeconomic position, gender, and inequalities in self-rated health between Roma and non-Roma in Serbia. Int J Public Health 57:49–55Google Scholar
  16. Kolarcik P, Madarasova Geckova A, Orosova O, van Dijk JP, Reijneveld SA (2009) To what extent does socioeconomic status explain differences in health between Roma and non-Roma adolescents in Slovakia? Soc Sci Med 68:1279–1284PubMedCrossRefGoogle Scholar
  17. Kosa Z, Voko Z, Szeles G et al (2007) A comparative health survey of the inhabitants of Roma settlements in Hungary. Am J Public Health 97:853–859PubMedCrossRefGoogle Scholar
  18. Koupilova I, Epstein H, Holcik J, Hajioff S, McKee M (2001) Health needs of the Roma population in the Czech and Slovak Republics. Soc Sci Med 53:1191–1204PubMedCrossRefGoogle Scholar
  19. Krajcovicova-Kudlackova M, Blazicek P, Spustova V et al (2004) Cardiovascular risk factors in young Gypsy population. Bratisl Lek Listy 105:256–259PubMedGoogle Scholar
  20. Lynch E (2006) Travellers’ tales. Nurs Stand 20:20–21CrossRefGoogle Scholar
  21. Mackenbach JP, Stirbu I, Roskam AR et al (2008) Socioeconomic inequalities in health in 22 European countries. New Engl J Med 358:2468–2481PubMedCrossRefGoogle Scholar
  22. Marcincin A, Marcincinova L (2009) The cost of non-inclusion: the key to integration is respect for diversity. Open Society Foundation, BratislavaGoogle Scholar
  23. Masseria C, Mladovsky P, Hernandez-Quevedo C (2010) The socio-economic determinants of the health status of Roma in comparison with non-Roma in Bulgaria, Hungary and Romania. Eur J Public Health 20:549–554PubMedCrossRefGoogle Scholar
  24. Panzarella C, Alloy LB, Whitehouse WG (2006) Expanded hopelessness theory of depression: on the mechanisms by which social support protects against depression. Cognitive Ther Res 30:307–333CrossRefGoogle Scholar
  25. Petek D, Pavlic DR, Svab I et al (2006) Attitudes of Roma toward smoking: qualitative study in Slovenia. Croat Med J 47:344–347PubMedGoogle Scholar
  26. Peters J, Parry GD, Van Cleemput P et al (2009) Health and use of health services: a comparison between gypsies and travellers and other ethnic groups. Ethnic Health 14:359–377CrossRefGoogle Scholar
  27. Proctor C, Linley P, Maltby J (2009) Youth life satisfaction: a review of the literature. J Happiness Stud 10:583–630CrossRefGoogle Scholar
  28. Puporka L, Zadori Z (1999) The health status of Romas in Hungary. Roma Press Center, BudapestGoogle Scholar
  29. Reynolds M (2005) Transitions online: Myths debunked. Transitions Online. http://www.ceeol.com/aspx/issuedetails.aspx?issueid=8631ee01-dc65-4b4b-8504-ddc3bc4cdcbd. Accessed 21 November 2008
  30. Rosicova K, Madarasova Geckova A, van Dijk JP, Kollarova J, Rosic M, Groothoff JW (2011) Regional socioeconomic indicators and ethnicity as predictors of regional infant mortality rate in Slovakia. Int J Public Health 56:523–531PubMedCrossRefGoogle Scholar
  31. Rosicova K, Madarasova Geckova A, van Dijk JP, Rosic M, Zezula I, Groothoff JW (2009) Socioeconomic indicators and ethnicity as determinants of regional mortality rates in Slovakia. Int J Pub Health 54(4):274–282Google Scholar
  32. Schaaf M (2011) Roma Health Mediators: Successes and Challenges. Roma Health Project Open Society Public Health Program. Open Society Foundations, New York. ISBN: 978-1-936133-58-1Google Scholar
  33. Sepkowitz KA (2006) Health of the world’s Roma population. Lancet 367:1707–1708PubMedCrossRefGoogle Scholar
  34. Slusna L (2010) Slovakia. In: Healthy Communities. Poverty and social exclusion in the WHO European Region: health systems respond. WHO Regional Office for Europe, CopenhagenGoogle Scholar
  35. Stansfeld SA, Head J, Marmot MG (1998) Explaining social class differences in depression and well-being. Soc Psychiatr Psychiatr Epidemiol 33:1–9CrossRefGoogle Scholar
  36. Tourangeau R, Smith TW (1996) Asking sensitive questions: the impact of data collection mode, question format, and question context. Public Opin Quart 60:275–304CrossRefGoogle Scholar
  37. Van Cleemput P, Parry G, Thomas K, Peters J, Cooper C (2007) Health-related beliefs and experiences of gypsies and travelers: a qualitative study. J Epidemiol Commun H 61:205–210CrossRefGoogle Scholar
  38. Vasecka M, Dzambazovic R (2000) Socialno-ekonomicka situacia Romov na Slovensku ako potencionalnych migrantov a ziadatelov o azyl v krajinach EU. (“Socio-economic Situation of Romanies in Slovakia as Potential Migrants and Asylum Seekers in EU Member States”). International Organization for Migration, BratislavaGoogle Scholar
  39. Vivian C, Dundes L (2004) The crossroads of culture and health among the Roma (Gypsies). J Nurs Scholarship 36:86–91PubMedCrossRefGoogle Scholar
  40. Voko Z, Csepe P, Nemeth R et al (2009) Does socioeconomic status fully mediate the effect of ethnicity on the health of Roma people in Hungary? J Epidemiol Commun H 63:455–460CrossRefGoogle Scholar
  41. Zeman CL, Depken DE, Senchina DS (2003) Roma health issues: a review of the literature and discussion. Ethnic Health 8:223–250PubMedCrossRefGoogle Scholar

Copyright information

© Swiss School of Public Health 2013

Authors and Affiliations

  • Pavol Jarcuska
    • 1
    Email author
  • Daniela Bobakova
    • 2
    • 3
  • Jan Uhrin
    • 4
  • Ladislav Bobak
    • 5
  • Ingrid Babinska
    • 2
    • 3
  • Peter Kolarcik
    • 2
    • 3
  • Zuzana Veselska
    • 2
    • 3
  • Andrea Madarasova Geckova
    • 2
    • 3
    • 6
  • HEPA-META team
    • 7
  1. 1.Department of Infectology and Travel Medicine, Medical FacultyPJ Safarik UniversityKosiceSlovak Republic
  2. 2.Graduate School Kosice Institute for Society and HealthPJ Safarik UniversityKosiceSlovak Republic
  3. 3.Department of Health Psychology, Medical Faculty, Institute of Public HealthPJ Safarik UniversityKosiceSlovak Republic
  4. 4.1st Department of PsychiatryLouis Pasteur University HospitalKosiceSlovak Republic
  5. 5.Associated Tissue Bank, Medical FacultyLouis Pasteur University Hospital, PJ Safarik UniversityKosiceSlovak Republic
  6. 6.Department of Christian Education, Sts. Cyril and Methodius Faculty of TheologyOlomouc University Social Health Institute, Palacky University OlomoucOlomoucCzech Republic
  7. 7.PJ Safarik UniversityKosiceSlovak Republic

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