Version Changes
Revised. Amendments from Version 1
Following the comments from our three reviews, we have significantly updated our methodology to reflect further detail that was lacking, as evidenced by the majority of the reviewers' questions. We have also modified some wording to better reflect how we obtained our final, working survey, the analyses we performed on our data, and the limitations of our study; most notably, we indicate that our work is a proof-of-concept study that draws together multiple lines of inquiry to demonstrate their relatedness.
Abstract
Background: This study explores how the Roma in Romania, the EU’s most concentrated population, are faring in terms of a number of quality of life indicators, including poverty levels, healthcare, education, water, sanitation, and hygiene.
Methods: 135 surveys were conducted across five geographically diverse Romanian communities. Household participants were selected through a comprehensive random walk method. Analyses were conducted on all data using Pandas for Python.
Results: These data indicate that the Roma in Romania face significant disparities in education, with Roma students less likely to progress beyond 8 th grade. In addition, the Roma population remains significantly disadvantaged with regard to safe and secure housing, poverty, and healthcare status, particularly in connection to diarrheal disease. In contrast, however, both Roma and non-Roma in rural areas face difficulties regarding full-time employment, sanitation, and water, sanitation, and hygiene infrastructure.
Conclusions: These data demonstrate the challenges that remain to the Roma population in Romania, and also point to the myriad of ways in which all rural Romanians, regardless of ethnicity, are encountering hardship. This study highlights the areas in which improvements can be made to ensure the Roma, and indeed all Romanian citizens, have access to and confidence in sanitation services, clean water, and adequate healthcare treatment.
Keywords: Roma, Romania, rural populations, water quality, healthcare, development, global health, decade of Roma inclusion
Introduction
In the years that followed independence and the democratic election of 1990, the southeastern European country of Romania received significant aid from the International Monetary Fund (IMF), World Bank (WB), European Bank for Reconstruction and Development (EBRD), European Investment Bank (EIB), the US Agency for International Development (USAID), and other donors 1. This influx of investment enabled Romania to make great strides in multiple areas of development and meet a number of the goals set forth in the United Nations Millennium Development Goals (UN MDGs) 2. In particular, the issues of severe poverty and hunger have significantly improved for ethnic Romanians and affluent minorities, with severe poverty (as defined by the United Nations) decreasing from 10 per cent to 4.1 per cent as of 2006 2. In addition, maternal mortality has fallen by half to 17 deaths/100,000 births, infant mortality has decreased 25 per cent, and Romania has seen a significant decrease in adolescent pregnancy, concomitant with a significant increase in the use of modern contraceptives 2. Vaccination rates, particularly for measles, hover around 98 per cent, up from less than 70 per cent at the time of independence; HIV/AIDS cases have decreased and life expectancy for those living with HIV has increased dramatically; and there has been a significant decrease in domestic violence 2.
For the Roma, the second most numerous minority in the country (after Hungarians), however, such progress was not extended. Despite enjoying a reprieve from targeted discrimination during the Soviet era, Romanian independence brought on a renewal of oppressive policies and behaviours against the Roma. The Roma are Europe’s most marginalised group 3, a minority population numbering between 10–12 million individuals across the continent and the UK 4. Emerging from slavery in the late 19 th century, they have historically faced discrimination in employment, education, and access to healthcare 5. Numerous studies indicate Roma have a significantly reduced lifespan compared to non-Roma and suffer greater rates of communicable and waterborne diseases 6– 8. In multiple countries, they are less likely to have access to basic services, including a municipal water supply, waste water treatment, or trash disposal 9, and they are routinely used as political scapegoats across the continent, from France to Moldova 10. Romania boasts the largest concentration of Roma in the European Union (EU), at approximately 1.85 million individuals, representing 9.3 per cent of the overall population of 19.8 million, though official census numbers vary 4.
The addition of eastern European countries (including Bulgaria, Romania, and Hungary) to the EU in the mid-2000s has renewed interest in the well-being of this population, as indicated by the EU’s targeted attempt to improve the circumstances of the Roma through the recently concluded Decade of Roma Inclusion (DRI), a ten year long initiative by twelve European countries to improve the socio-economic status and social standing of the Roma minority across the continent 11. Numerous studies have explored the success of the DRI, both during its implementation and since its conclusion, and outcomes vary, depending on the sector and goal in question 8, 12– 14. This pilot study is a preliminary attempt to explore how the EU’s largest concentration of Roma are faring in terms of poverty levels, healthcare, education, and water, sanitation, and hygiene (WASH), as well as to fill the gap in available literature that focuses solely on Romania. To our knowledge, few other peer-reviewed studies have linked all of these parameters together, and even fewer have done so in the specific context of Romania. In particular, we examine the connection between physical WASH infrastructure relative to incidence of disease and overall health status and present our findings as a first attempt to specifically characterize the current situation for the Romanian Roma minority.
Methods
Regional survey
Combining questions adapted from a validated WASH survey previously used for multiple use service strategy research (MUS) in Burkina Faso (personal communication to authors) and the WHO core questions on drinking-water and sanitation 15 with questions related to demographics, socio-economic status, and healthcare access and history, we conducted 135 surveys each consisting of 56 total questions across five geographically diverse communities throughout Romania. The survey questions were modified with the assistance of our NGO partner to reflect the cultural differences in Romania as opposed to the original work in Burkina Faso. There is no comparison between the findings presented here and the work done in Burkina Faso. Communities were chosen from a list of those that had previously participated with Agentia Impreuna in education and anti-discrimination capacity-building programs for communities with prominent Roma populations. In addition, in an attempt to address geographical bias in improve the generalizability of our findings, communities were identified for their geographical diversity. Participating communities included central urban households, suburban communities, and very rural, mountainous regions. Communities were further distinct in the level of integration observed between the Roma population and the non-Roma, being fully integrated in some areas and completely separate in others. Household participants were selected through a comprehensive random walk method, with survey teams accompanied by both Roma and non-Roma community leaders. Survey teams varied the time of day they moved through any given community to ensure access to the full population, and interviews were conducted in areas throughout the community, with participants identified at their homes, as well as in shops and cafes. Identifying information for the participants was used only to ensure there was no duplication of household information. Any household with an individual over the age of 18 present and willing to participate, regardless of ethnicity, was included until the desired 30 surveys per community were achieved or there were no further willing participants. Interviews were conducted by trained volunteers who either spoke the national language (Romanian) or were accompanied by a certified translator. The team interviewed only one member of each household, who provided information about all members of the household. The specifics of participating communities are purposefully withheld to comply with the approval constraints of our ethics board.
Ethical statement
Surveys ( Supplementary material 1 and Supplementary material 2) and procedures were approved by the Virginia Tech Institutional Review Board (IRB) prior to study implementation (VT IRB #16-475), and all interviews and analysis were carried out according to IRB protocol.
IRB protocol and participant protections
Informed consent was obtained from all individual participants included in this study. A brief explanation of the survey questions and the intended use of the data was provided to each participant, and the individual’s agreement to participate in the survey interview was considered consent, as indicated by the IRB protocol. Further, interviewers ensured each participant understood that he or she could refuse to answer any question and could withdraw their consent at any time. Survey participation was anonymous, and no identifying information was retained. In addition, the IRB stipulated that location data for the participating villages remain unavailable, due to the vulnerable population and minority status of some study participants. All demographic information was self-reported, and those who were considered part of the Roma sample self-identified as either Roma or Rudar (a sub-set of Roma people who do not speak Romani), in response to a question that explicitly asked for their ethnicity ( Dataset 1).
Primary data analysis
All data analyses were conducted via Pandas with Python (version 2.7.11 & 0.18.0) notebook and the software package Epipy 16, 17 ( Dataset 2– Dataset 3). Descriptive statistics were broken down by community, ethnicity, gender, age, household size, education level, marital status, employment, literacy, and geographical description (urban versus rural). WASH parameters were defined using the UN descriptions as provided in the DRI progress report through 2013, as well as the addition of a ‘safe water score’, which included the option of a private, protected well water source in addition to tap water in the home 11. The overall WASH score for each participating household is an aggregate of the following UN parameters: indoor toilet (improved sanitation), indoor bathroom (improved sanitation II), piped water to tap (improved water source), and insecure housing (a 0–3 score reflecting the status of the floor, walls, and roof of a dwelling). The overall ‘WASH Safe’ score exchanged the improved water source parameter for the aforementioned safe water score. In addition, time to primary drinking water sources has been converted to a numerical scale, based on 15 minute intervals, up to one hour (0–4 scale). Distance to primary drinking water is indicated both by a percentage of those in each ethnic group who travel a kilometre or more and the average distance travelled by each group. Similar to the WASH score, the healthcare score is an aggregate of self-reported immunization, reported incidence of diarrheal event, access to primary care physician (PCP), and reported medical insurance status. Finally, the poverty score is an aggregate of available electricity in dwelling, available gas source in dwelling, and the UN indicator of severe poverty (surviving on 2USD/person/day or less). Univariate analyses compared the Roma sample to the non-Roma sample for each variable (using non-Roma as the reference population), as well as urban areas to rural ones (with urban areas as the reference population) for some parameters. Odds Ratios (ORs) with 95 per cent confidence intervals are reported, as are t-test results (95 per cent confidence interval) with accompanying p-value where appropriate.
Secondary data analysis and multivariate models
Multivariate linear regression analyses were conducted by using combinations of the four aggregate scores, as explained in primary analysis, and by including parameters that demonstrated significance in univariate modelling ( Dataset 2– Dataset 3).
Results
Population demographics
Analyses of demographic data and breakdown by percentage indicate our sample population is, overall, predominantly Roma (72.6 per cent vs. 27.4 per cent non-Roma), split evenly by sex (50.4 per cent Female, 49.6 per cent Male), and average approximately 47 years of age ( Table 1). Three of the five sample communities are rural (more than 25km from a city centre), one is suburban (between 10–25km from a city centre), and one is urban (less than 10km from a city centre). There is no significant difference between Roma and non-Roma in the sample population on the basis of marital status, age, or sex. However, our data indicate notable disparities in level of education (secondary school completion for Roma vs. high school completion for non-Roma), household size (5.3 individuals for Roma vs. 4.2 individuals for non-Roma), and literacy rate (61 per cent literate Roma vs. 97.4 per cent literate non-Roma) ( Table 1). Little difference is noted in full-time employment rates between the groups (26.6 per cent Roma vs. 32.4 per cent non-Roma), though some difference is observable between rural and urban communities ( Table 1).
Table 1. Study population demographics broken down by community.
Romania, 2016. M=male, F=female, FT=full-time, UE=unemployed, DL=day labour.
|
Population
N (%) |
Sex
% M(F) |
Age of
Respondents (Mean in years) |
House-hold
Size N (Mean no. persons) |
Education Level
of Respondents (Mean Grade Completed) |
Marital Status
% Partnership (Single) |
Employment
Status % FT (UE or DL) |
Literacy of
Families Overall (%) |
Geographical
Location |
|
|---|---|---|---|---|---|---|---|---|---|
| Community 1 | |||||||||
| Roma | 28 (96.6) | 28.5 (71.4) | 49.3 | 4.7 |
Secondary
School (8th grade) |
71.4 (28.6) | 10.7 (89.3) | 56 | -- |
| Non-Roma | 1 (3.4) | 100 (0) | 52 | 5 |
Some University
/ College |
100 (0) | 0 (100) | 80 | -- |
| Overall | 29 | 31 (69) | 49.4 | 4.7 | Secondary
School (8th grade) |
72.4 (27.6) | 7.7 (89.7) | 57.5 | Rural |
| Community 2 | |||||||||
| Roma | 24 (80) | 75 (25) | 48.1 | 5.9 |
Secondary
School (8th grade) |
87.5 (12.5) | 16.7 (83.3) | 58.9 | -- |
| Non-Roma | 6 (20) | 50 (50) | 50.1 | 4.8 |
Some University
/ College |
83.3 (16.7) | 66.7 (33.3) | 100 | -- |
| Overall | 30 | 70 (30) | 45.8 | 5.7 | Required School
(10th grade) |
86.7 (13.3) | 26.7 (73.3) | 66.7 | Rural |
| Community 3 | |||||||||
| Roma | 18 (60) | 44.4 (55.6) | 42.6 | 5.3 |
Secondary
School (8th grade) |
94.4 (5.6) | 27.8 (72.2) | 58.3 | -- |
| Non-Roma | 12 (40) | 58.3 (41.7) | 50.1 | 4.2 |
High School
+ Vocational School |
91.7 (8.3) | 25 (75) | 100 | -- |
| Overall | 30 | 50 (50) | 45.6 | 4.9 | Required School
(10th grade) |
93.3 (6.7 | 26.7(73.3) | 74.4 | Suburban |
| Community 4 | |||||||||
| Roma | 13 (43.3) | 46.2 (53.8) | 42.7 | 6.1 |
Secondary
School (8th grade) |
84.6 (15.4) | 23.1 (76.9) | 48 | -- |
| Non-Roma | 17 (56.7) | 29.4 (70.6) | 60.4 | 2.9 |
Required School
(10th grade) |
58.8 (41.2) | 23.5 (76.5) | 95.1 | -- |
| Overall | 30 | 36.7 (63.3) | 52.7 | 4.3 | Secondary
School (8th grade) |
70 (30 | 23.3 (76.7) | 69.2 | Rural |
| Community 5 | |||||||||
| Roma | 15 (93.7) | 66.7 (33.3) | 35.4 | 4.7 |
High School
(12th grade) |
73.3 (26.7) | 73.3 (26.7) | 93.2 | -- |
| Non-Roma | 1 (6.3) | 100 (0) | 40 | 4 |
Required School
(10th grade) |
100 (0) | 100 (0) | 100 | -- |
| Overall | 16 | 68.8 (31.2) | 35.7 | 4.7 | High School
(12th grade) |
75 (25) | 75 (25) | 93.6 | Urban |
| Overall | |||||||||
| Roma | 98 (72.6) | 51 (49) | 44.8 | 5.3 |
Secondary
School (8th grade) |
75.5 (24.5) | 26.6 (73.4) | 61 | -- |
| Non-Roma | 37 (27.4) | 46 (54) | 52.4 | 4.2 |
High School
(12th grade) |
75.6 (24.3) | 32.4 (67.6) | 97.4 | -- |
| Total | 135 | 49.6 (50.4) | 46.9 | 4.8 | Required School
(10th grade) |
80 (20) | 28.1 (71.9) | 72.3 | -- |
WASH, healthcare, poverty parameters
Using parameters utilized by the DRI in the 2011 progress report, univariate analysis indicates little difference between Roma and non-Roma with regard to specific WASH variables. The non-Roma are slightly more likely to have an indoor toilet (21.6 per cent non-Roma vs 17.3 per cent Roma) and bathroom (21.6 per cent non-Roma vs 20.4 per cent Roma), but the Roma are more likely than non-Roma to have tap (indoor or outdoor) water (20.4 per cent Roma vs 8.1 per cent non-Roma), whether piped in from a personal well or a municipal water source ( Table 2). However, when considering all safe water options (including a protected well without a tap to the home or garden), non-Roma report greater accessibility (59.5 per cent non-Roma vs 50 per cent Roma). In addition, Roma are significantly more at risk to inhabit insecure housing, regardless of geographical region, than non-Roma (27.6 per cent Roma vs 5.4 per cent non-Roma) ( Table 2). Interestingly, while the Roma population have greater access to tap water (indoor or outdoor), they are less likely to use it as their primary drinking water source, demonstrated by the increased time and distance Roma are likely to travel to secure safe drinking water (12.2km Roma vs. 10.8km non-Roma; Table 2). Of interest, however, is the increased time all individuals in suburban and urban areas must travel to secure drinking water compared to their rural counterparts (16–30 minutes (1.2 on 0–3 scale) urban vs. 0–15 minutes (1.0 on 0–3 scale) rural) ( Table 3).
Table 2. Univariate analyses.
Romania, 2016. Reference population for all variables is non-Roma. * indicates significance at 95% CI level. ** indicates significance at 90% CI level.
| Roma | Non-Roma | t-statistic | p-value |
Odds
Ratio |
95% CI | ||
|---|---|---|---|---|---|---|---|
| WASH | Improved Sanitation
(Indoor Toilet, % yes) |
17.3 | 21.6 | 0.567 | 0.57 | 1.31 | 0.51, 3.37 |
| Improved Sanitation II
(Indoor Bathroom, % yes) |
20.4 | 21.6 | 0.154 | 0.878 | 1.08 | 0.43, 2.71 | |
| Improved Water Source
(Piped water to tap, % yes) |
20.4 | 8.1 | -1.701 | 0.091 ** | 0.34 | 0.1, 1.24 | |
| Insecure Housing (% yes) | 27.6 | 5.4 | 2.858 | 0.005 * | 6.65 | 1.5, 29.6 | |
| Time to Primary Drinking Water Source
(Mean, 0–4 scale, 15min intervals) |
1.12 | 1.0 | 0.769 | 0.443 | 1.12 | 0.37, 3.43 | |
| Distance to Primary Drinking Water Source
(%, 1km or more) |
12.2 | 10.8 | 0.124 | 0.901 | 1.15 | 0.35, 3.82 | |
| Safe Water Source (tap or well, % yes) | 50 | 59.5 | 0.978 | 0.329 | 1.47 | 0.8, 1.91 | |
| Healthcare | Moderate/Severe Diarrhea in Last Year
(% yes) |
58.1 | 40.5 | -1.84 | 0.07 ** | 2.04 | 0.94, 4.4 |
| Reports Immunization of any kind (% yes) | 87.8 | 97.1 | 0.678 | 0.499 | 1.58 | 0.42, 5.96 | |
| Medically Insured (% yes) | 81.6 | 89.1 | 1.057 | 0.292 | 1.86 | 0.58, 5.9 | |
| Access to PCP (% yes) | 98 | 97 | -0.231 | 0.818 | 0.75 | 0.07, 8.53 | |
| Poverty | Electricity in Home or Dwelling (% no) | 13.2 | 2.7 | 1.804 | 0.07 ** | 5.51 | 0.69, 43.68 |
| Piped or Tank Gas in Home or Dwelling
(% no) |
32.7 | 18.9 | 1.57 | 0.12 | 2.47 | 0.82, 5.24 | |
| Spends more than $2/person/day (% no) | 55.1 | 43.2 | 1.23 | 0.22 | 1.61 | 0.75, 3.45 |
Table 3. Geographical univariate analysis.
Romania, 2016. Reference population for all variables is urban. * indicates significance at 95% CI level.
| Rural | Urban | t-statistic | p-value |
Odds
Ratio |
95% CI | |
|---|---|---|---|---|---|---|
|
Time to Primary Drinking Water Source
(Mean, 0–4 scale, 15min intervals) |
1.0 | 1.2 | 1.306 | 0.194 | 0.53 | 0.19, 1.49 |
| Spends more than $2/person/day (% no) | 61.8 | 32.6 | 3.323 | 0.001 * | 3.3 | 1.58, 7.08 |
In addition to physical infrastructure, we analysed the differences between Roma and non-Roma with regard to key factors contributing to overall health status. Roma are more than twice as likely to report at least one household member suffering from moderate to severe diarrhoea (lasting more than 3 days) than non-Roma (58.1 per cent Roma vs 40.5 per cent non-Roma; OR 2.04) ( Table 2). In addition, while there is little difference in access to a primary care physician between the groups, Roma are approximately 1.5 times less likely to report having received an immunization of any kind (87.8 per cent Roma vs 97.1 per cent non-Roma; OR 1.58) and fewer Roma possess medical insurance (81.6 per cent Roma vs 89.1 per cent non-Roma; OR 1.86) than non-Roma ( Table 2).
Finally, we used the UN definition of extreme poverty (2USD/person/day or less) in addition to two other variables as an overall indicator of impoverished conditions ( Table 2). Roma report a slightly greater, though not significant, incidence of lacking working electricity in their homes or dwellings (13.2 per cent Roma vs 2.7 per cent non-Roma), as well as lacking piped gas and/or the ability to purchase gas tanks (32.7 per cent Roma vs. 18.9 per cent non-Roma, p=0.12) ( Table 2). Moreover, Roma report greater incidences of severe poverty (2USD/day/person or less) than non-Roma (55.1% per cent vs. 43.2 per cent) ( Table 2), although overall, those in rural areas are significantly more susceptible to extreme poverty than those in suburban or urban communities (61.8 per cent rural vs. 32.6 per cent urban) ( Table 3).
Multivariate analyses
Following univariate analysis, we used general multivariate linear regression analysis for four distinct models, combining categories that indicated a specific score (WASH, WASH Safe, poverty, healthcare) or approached a level of significance in the univariate analysis ( Table 4). These analyses further demonstrate the significant (α = 0.05) disparity between Roma and non-Roma.
Table 4. Multivariate analysis modelling.
Romania, 2016. All models use non-Roma as reference. * indicates significance at 95% CI level. ** indicates significance at 90% CI level.
| MOD1 | Regression
coefficient |
p-value | 95% Confidence
Interval |
|---|---|---|---|
| Property Documents | 0.0854 | 0.279 | 0.069, 0.240 |
| Education Level | 0.2613 * | 0.001 | 0.100, 0.422 |
| Household Size | 0.2362 * | 0.002 | 0.083, 0.389 |
| Employment Status | 0.0505 | 0.559 | -0.119, 0.220 |
| MOD2 | Regression
coefficient |
p-value | 95% Confidence
Interval |
| Improved Water
Source |
-0.1914 * | 0.05 | -0.383, -0.0000465 |
| Moderate/Severe
Diarrhea |
0.1302 ** | 0.08 | -0.016, 0.276 |
| Electricity in Dwelling | 0.1802 | 0.139 | -0.058, 0.419 |
| Insecure Housing | 0.2860 * | 0.001 | 0.111, 0.461 |
| MOD3 | Regression
coefficient |
p-value | 95% Confidence
Interval |
| WASH Score | -0.4104 * | 0.017 | -0.747, -0.074 |
| Healthcare Score | 0.3407 ** | 0.066 | -0.022, 0.704 |
| Poverty Score | 0.3391 * | 0.013 | 0.070, 0.608 |
| MOD4 | Regression
coefficient |
p-value | 95% Confidence
Interval |
| WASH Safe Score | -0.250 | 0.203 | -0.521, 0.111 |
| Healthcare Score | 0.3277 ** | 0.083 | -0.042, 0.698 |
| Poverty Score | 0.3305 * | 0.02 | 0.052, 0.609 |
A multivariate combination of demographic variables further highlights the difference in education level and household size between Roma and non-Roma. Roma households are significantly larger than non-Roma households, but whether this is a correlation with birth rate or the presence of multiple generations in a single dwelling is beyond the scope of this study. Furthermore, Roma individuals are far less likely to complete required education (10 th grade) than non-Roma individuals (MOD1; Table 4). In our univariate analysis, we broke down the score categories to their individual components and identified significant factors to further explore. Multivariate analysis of these parameters points to insecure housing as having the strongest correlation with being Roma, followed by access to tap water (improved water source), and less significantly, the occurrence of moderate or severe diarrhoea (MOD2; Table 4).
Finally, we analysed our four score categories, using two different approaches. We first analysed the WASH score, as defined by the DRI, together with the healthcare and poverty scores (MOD3; Table 4). Healthcare and poverty equally significantly correlate with being Roma. The WASH score, however, is negatively correlated to the Roma, indicating that Roma individuals actually have an advantage over non-Roma individuals. To further investigate this question, we ran an additional analysis with healthcare and poverty, but substituting our WASH Safe score (MOD4; Table 4). The significant difference observed in healthcare and poverty remains, but when protected well water is included alongside tap water in the definition of improved or safe water sources, the disparity associated with WASH is eliminated.
Romania, 2016. Excel file of compiled responses to survey questions. Coded and de-identified. Numerical code corresponds to responses as indicated on the study surveys ( Supplementary material 1 and Supplementary material 2).
Copyright: © 2018 Powell Doherty R et al.
Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
Romania, 2016. Python Notebook analysis of survey data.
Copyright: © 2018 Powell Doherty R et al.
Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
Romania, 2016. Python Notebook analysis of survey data, exported as a PDF file.
Copyright: © 2018 Powell Doherty R et al.
Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
Discussion
A number of studies have examined the various factors the Decade of Roma Inclusion (DRI) sought to address in Roma communities across the EU, both during the implementation of the project and since its conclusion in 2015 5, 11, 13, 18, 19. Unfortunately, while some improvements did occur, a number of studies indicate the DRI did not achieve its stated goals in the areas of education, housing, employment, and health status of Roma in participating countries 20, 21. Our study supports these conclusions, particularly with regard to education, healthcare, and poverty. However, disparities that other studies have highlighted in multiple countries with regard to employment and sanitation do not necessarily occur in Romania 19, 22– 24. Rather, both the Roma and non-Roma in rural Romania face similar challenges regarding access to full-time employment and water, which are exacerbated by a lack of municipal sanitation services in over 800 Romanian communities 25. The lack of significant difference between Roma and non-Roma in our sample in relation to indoor toilets and bathrooms does not indicate that either ethnic group has an advantage, but rather all those who reside in rural communities face a disadvantage, regardless of ethnicity. Notably, our findings indicate that, in some instances, the Roma appear to have a slight advantage over non-Roma ( Table 4). Using the DRI definition of piped water to an indoor or outdoor tap, our analyses indicate Romanian and other non-Roma individuals lag behind the Roma in ‘improved water sources’. However, when one accounts for the prevalence of private, protected wells (WASH Safe score), the disparity is minimized and no longer significant ( Table 4). We postulate this distinction is indicative of how our survey collected this type of data, and future iterations will refine how we classify ‘safe’ and ‘improved’ water sources.
Of additional interest is the key indicator that those in suburban and urban areas, Roma and non-Roma alike, take longer to reach their chosen primary drinking water sources than do their rural counterparts. However, this statistic is potentially ambiguous. The urban community included in this study reported overwhelmingly that it had recently been subject to a contamination of the municipal water supply with coliform bacteria and, thus, the majority of residents therein reported the need to purchase water rather than use the taps available in their homes. It was not possible to collect data regarding the behaviour of these residents prior to the contamination event. Furthermore, the suburban community included here recently experienced the loss of a bridge, connecting the far side of the river to the village centre on the other side. Those individuals stranded on the far side of the bridge (predominantly Roma) reported numerous problems with their wells, requiring them to travel 5km or more to the nearest crossing to reach a shop or market until the bridge is restored. Therefore, this statistic is potentially a reflection of the walking or driving time that would otherwise be unnecessary.
Despite the evidence presented that Roma and non-Roma alike are subjected to ineffective sanitation and hygiene services throughout the country, one should note that the Roma population still reports a greater incidence of diarrheal disease and a reduced rate of immunization than the non-Roma population. There are potentially a number of reasons for this. Unlike in other countries 5, 24, the Romanian Roma report fairly equivalent rates of medical insurance and access to primary care, but the type of treatment received when care is sought was beyond the scope of this study and may be a contributing factor. Indeed, Roma individuals have elsewhere reported poor health related to both their unhygienic circumstances and the care they receive 19, 26, 27. In addition, as has already been noted, both literacy rates and overall levels of education are significantly decreased in the Romanian Roma population. This is in contrast to education rates in Roma populations of other countries, as the educational component of the DRI has been lauded as the most successful portion of the initiative, albeit only for primary school attendance 20, 21. Rates of disease and healthcare status overall are inversely associated with education 28, which may offer another possible explanation for the disparity in diarrheal disease rates. It is important to consider, however anecdotally, the Roma do report some knowledge of personal water treatment and safety (data not shown), through the use of salt or lime in personal wells and a commitment to boiling water before drinking or cooking if possible. However, the lack of infrastructure and services works against these individual and imperfect efforts. Furthermore, for those Roma who do have access to tap water (municipal or otherwise), many of them report using an alternative primary water source. While these same individuals indicate that they believe their tap water to be safe (data not shown), their daily activities are in direct contrast to this assertion.
Overall, while these data demonstrate the ongoing challenges following the Decade of Roma Inclusion as applied to the Roma population in Romania, this study also points to the myriad of ways in which all Romanians, regardless of ethnicity, are encountering challenges. It highlights the areas in which improvements can be made to ensure all Romanian citizens have access to and confidence in basic sanitation services, clean water, and adequate healthcare treatment.
Limitations and future directions
The primary limitation to this study is the sample size of 135 individuals. Time and funding constraints, as well as limited personnel, inhibited our ability to interact with more than 30 households per community and restricted the study to five communities. Future efforts will expand the population included in similar studies by increasing the number of communities engaged, and will seek to enroll equal numbers of Roma and non-Roma. Additionally, subsequent studies can use these and other data to generate detailed models that explore specific initiatives that could be implemented to address discrepancies in equality and access, and progress the literature around Roma health disparities beyond analysis and into intervention testing.
Data availability
The data referenced by this article are under copyright with the following copyright statement: Copyright: © 2018 Powell Doherty R et al.
Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication). http://creativecommons.org/publicdomain/zero/1.0/
Dataset 1: Coded survey data. Romania, 2016. Excel file of compiled responses to survey questions. Coded and de-identified. Numerical code corresponds to responses as indicated on the study surveys ( Supplementary material 1 and Supplementary material 2).
DOI, 10.5256/f1000research.12546.d177233 29
Dataset 2: Python Notebook data analysis and statistics. Romania, 2016. Python Notebook analysis of survey data.
DOI, 10.5256/f1000research.12546.d177234 30
Dataset 3: Python Notebook data analysis and statistics. Romania, 2016. Python Notebook analysis of survey data, exported as a PDF file.
Acknowledgments
We would like to thank Dr. Ralph P. Hall for his assistance developing the surveying instrument, and all the staff members at Agentia Impreuna for helping to make this project possible. We thank our external collaborators and members of the Network Dynamics and Simulation Science Laboratory (NDSSL) for their suggestions and comments. In addition, we are grateful to the numerous friends and family who contributed financially to support our time in the field, with particular thanks to George K. Agardi, Sr. and Dr. Susan Evans.
Funding Statement
This work has been partially supported by the National Institutes of Health and National Institute of General Medical Sciences - Models of Infectious Disease Agent Study Grant 5U01GM070694-13, the Defense Threat Reduction Agency - Comprehensive National Incident Management System Contract HDTRA1-11-D-0016-0001, and the Virginia-Maryland College of Veterinary Medicine.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
[version 2; referees: 2 approved with reservations
Supplementary material
Supplementary material 1: Quality of Life Survey, English. Romania 2016. Survey questions provided in English.
Supplementary material 2: Quality of Life Survey, Romanian. Romania, 2016. Survey questions provided in Romanian.
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