Background Data provided by the social sciences as well as genetic research suggest that the 8-10 million Roma (Gypsies) who live in Europe today are best described as a conglomerate of genetically isolated founder populations. The relationship between the traditional social structure observed by the Roma, where the Group is the primary unit, and the boundaries, demographic history and biological relatedness of the diverse founder populations appears complex and has not been addressed by population genetic studies. Results Recent medical genetic research has identified a number of novel, or previously known but rare conditions, caused by private founder mutations. A summary of the findings, provided in this review, should assist diagnosis and counselling in affected families, and promote future collaborative research. The available incomplete epidemiological data suggest a non-random distribution of disease-causing mutations among Romani groups. Conclusion Although far from systematic, the published information indicates that medical genetics has an important role to play in improving the health of this underprivileged and forgotten people of Europe. Reported carrier rates for some Mendelian disorders are in the range of 5 -15%, sufficient to justify newborn screening and early treatment, or community-based education and carrier testing programs for disorders where no therapy is currently available. To be most productive, future studies of the epidemiology of single gene disorders should take social organisation and cultural anthropology into consideration, thus allowing the targeting of public health programs and contributing to the understanding of population structure and demographic history of the Roma.

Background: Interactions between genetic and environmental risk factors (GxE) contribute to an increased risk of venous thromboembolism (VTE). Understanding how these factors interact provides insight for the early identification of at-risk groups within a population and creates an opportunity to apply appropriate preventive and curative measures.Objective: To estimate and compare GxE for VTE risk in the general Hungarian and Roma populations.Methods: The study was based on data extracted from a database consisting of results previously obtained from a complex health survey with three pillars (questionnaire-based, physical, and laboratory examinations) involving 406 general Hungarian and 395 Roma subjects. DNA was genotyped for rs121909567 (SERPINC1), rs1799963 (F2), rs2036914 (F11), rs2066865 (FGG), rs6025 (F5), and rs8176719 (ABO) polymorphisms. After allele frequency comparisons, the odds ratio (OR) was calculated for individual SNPs. Furthermore, genetic risk scores (weighted GRS, unweighted GRS) were computed to estimate the joint effect of the genetic factors. Multivariable linear regression analysis was applied to test the impact of GxE on VTE risk after interaction terms were created between genetic and VTE risk factors [diabetes mellitus (DM), cancer, chronic kidney diseases (CKD), coronary artery diseases (CAD), migraine, depression, obesity, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high density lipoprotein (HDL-C), triglyceride (TG), and smoking].Results: Interestingly, the rs121909567 (SERPINC1, ATBp3 mutation) SNP was not present in the general population at all. However, the risk allele frequency was 1% among the Roma population, which might suggest a founder effect in this minority. This polymorphism multiplicatively interacted with CAD, CKD, cancer, DM, depression, migraine, and obesity. Even though interactions were not statistically significant, the trend of interaction showed the probability of an incremental VTE risk among the Roma population. The risk of VTE was 4.7 times higher (p > 0.05) for Roma subjects who had ≥3 wGRS (median value) compared with individuals having lower wGRS values but lower for the general subjects (OR = 3.1 × 10−8). Additionally, the risk of VTE was 6.6 times higher in the Roma population that had ≥3 risk alleles (median value) than in individuals with the 0–1 risk allele, and the overall risk was much higher for the Roma population (OR = 6.6; p > 0.05) than for the general Hungarian population (OR = 1.5; p > 0.05). Five positive and significant GxE interactions were identified in the Roma population. The risk of VTE was higher among depressive Roma subjects who carried the risk variant rs2036914 (β = 0.819, p = 0.02); however, this interaction was not significant for the general subjects. The joint presence of high levels of LDL-C and rs2066865 (FGG) increased the VTE risk only among Roma individuals (β = 0.389, p = 0.002). The possibility of VTE risk increment, as a result of a multiplicative interaction between rs8176719 (ABO) and cancer, was identified, which was higher for the Roma population (β = 0.370, p < 0.001) than for the general population (β = −0.042, p = 0.6). The VTE risk increased in the Roma population (β = 0.280, p = 0.001), but was higher in the general population (β = 0.423, p = 0.001) as a result of the multiplicative interaction between CAD and rs2036914 (F11). The presence of a multiplicative interaction between rs2066865 (FGG) and CAD increased the VTE risk for the Roma population (β = 0.143, p = 0.046) but not for the general population (β = −0.329, p < 0.001).Conclusions: rs121909567 (SERPINC1, ATBp3) was confirmed as a founder mutation in the Roma population. Our study revealed some evidence on the burden of the joint presence of genetic and environmental risk factors on VTE, although the finding is highly subjected to the selection and observational biases due to the very small number of VTE cases and the observational nature of the study design, respectively. As a result of higher genetic load and GxE interactions, this minority Roma population is at higher risk of VTE than the general Hungarian population. Thus, our results suggest the need for an intensive search for the rs121909567 (SERPINC1; ATBp3) founder mutation, which might be an important factor for the assessment of thrombotic disease susceptibility among the Roma population. In addition, we strongly recommend further studies among a large number of VTE cases to explore the more precise impact of genetic and environmental risk factors on VTE in the study populations.

Gypsy or Irish Traveller populations by highest qualification with age, sex and accommodation type breakdowns across different geographical areas.

Abstract

The study included four separate surveys:

1. The LSMS survey of general population of Serbia in 2002

2. The survey of Family Income Support (MOP in Serbian) recipients in 2002 These two datasets are published together separately from the 2003 datasets.

3. The LSMS survey of general population of Serbia in 2003 (panel survey)

4. The survey of Roma from Roma settlements in 2003 These two datasets are published together.

Objectives

LSMS represents multi-topical study of household living standard and is based on international experience in designing and conducting this type of research. The basic survey was carried out in 2002 on a representative sample of households in Serbia (without Kosovo and Metohija). Its goal was to establish a poverty profile according to the comprehensive data on welfare of households and to identify vulnerable groups. Also its aim was to assess the targeting of safety net programs by collecting detailed information from individuals on participation in specific government social programs. This study was used as the basic document in developing Poverty Reduction Strategy (PRS) in Serbia which was adopted by the Government of the Republic of Serbia in October 2003.

The survey was repeated in 2003 on a panel sample (the households which participated in 2002 survey were re-interviewed).

Analysis of the take-up and profile of the population in 2003 was the first step towards formulating the system of monitoring in the Poverty Reduction Strategy (PRS). The survey was conducted in accordance with the same methodological principles used in 2002 survey, with necessary changes referring only to the content of certain modules and the reduction in sample size. The aim of the repeated survey was to obtain panel data to enable monitoring of the change in the living standard within a period of one year, thus indicating whether there had been a decrease or increase in poverty in Serbia in the course of 2003. [Note: Panel data are the data obtained on the sample of households which participated in the both surveys. These data made possible tracking of living standard of the same persons in the period of one year.]

Along with these two comprehensive surveys, conducted on national and regional representative samples which were to give a picture of the general population, there were also two surveys with particular emphasis on vulnerable groups. In 2002, it was the survey of living standard of Family Income Support recipients with an aim to validate this state supported program of social welfare. In 2003 the survey of Roma from Roma settlements was conducted. Since all present experiences indicated that this was one of the most vulnerable groups on the territory of Serbia and Montenegro, but with no ample research of poverty of Roma population made, the aim of the survey was to compare poverty of this group with poverty of basic population and to establish which categories of Roma population were at the greatest risk of poverty in 2003. However, it is necessary to stress that the LSMS of the Roma population comprised potentially most imperilled Roma, while the Roma integrated in the main population were not included in this study.

Geographic coverage

The surveys were conducted on the whole territory of Serbia (without Kosovo and Metohija).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample frame for both surveys of general population (LSMS) in 2002 and 2003 consisted of all permanent residents of Serbia, without the population of Kosovo and Metohija, according to definition of permanently resident population contained in UN Recommendations for Population Censuses, which were applied in 2002 Census of Population in the Republic of Serbia. Therefore, permanent residents were all persons living in the territory Serbia longer than one year, with the exception of diplomatic and consular staff.

The sample frame for the survey of Family Income Support recipients included all current recipients of this program on the territory of Serbia based on the official list of recipients given by Ministry of Social affairs.

The definition of the Roma population from Roma settlements was faced with obstacles since precise data on the total number of Roma population in Serbia are not available. According to the last population Census from 2002 there were 108,000 Roma citizens, but the data from the Census are thought to significantly underestimate the total number of the Roma population. However, since no other more precise data were available, this number was taken as the basis for estimate on Roma population from Roma settlements. According to the 2002 Census, settlements with at least 7% of the total population who declared itself as belonging to Roma nationality were selected. A total of 83% or 90,000 self-declared Roma lived in the settlements that were defined in this way and this number was taken as the sample frame for Roma from Roma settlements.

Planned sample: In 2002 the planned size of the sample of general population included 6.500 households. The sample was both nationally and regionally representative (representative on each individual stratum). In 2003 the planned panel sample size was 3.000 households. In order to preserve the representative quality of the sample, we kept every other census block unit of the large sample realized in 2002. This way we kept the identical allocation by strata. In selected census block unit, the same households were interviewed as in the basic survey in 2002. The planned sample of Family Income Support recipients in 2002 and Roma from Roma settlements in 2003 was 500 households for each group.

Sample type: In both national surveys the implemented sample was a two-stage stratified sample. Units of the first stage were enumeration districts, and units of the second stage were the households. In the basic 2002 survey, enumeration districts were selected with probability proportional to number of households, so that the enumeration districts with bigger number of households have a higher probability of selection. In the repeated survey in 2003, first-stage units (census block units) were selected from the basic sample obtained in 2002 by including only even numbered census block units. In practice this meant that every second census block unit from the previous survey was included in the sample. In each selected enumeration district the same households interviewed in the previous round were included and interviewed. On finishing the survey in 2003 the cases were merged both on the level of households and members.

Stratification: Municipalities are stratified into the following six territorial strata: Vojvodina, Belgrade, Western Serbia, Central Serbia (Šumadija and Pomoravlje), Eastern Serbia and South-east Serbia. Primary units of selection are further stratified into enumeration districts which belong to urban type of settlements and enumeration districts which belong to rural type of settlement.

The sample of Family Income Support recipients represented the cases chosen randomly from the official list of recipients provided by Ministry of Social Affairs. The sample of Roma from Roma settlements was, as in the national survey, a two-staged stratified sample, but the units in the first stage were settlements where Roma population was represented in the percentage over 7%, and the units of the second stage were Roma households. Settlements are stratified in three territorial strata: Vojvodina, Beograd and Central Serbia.

Mode of data collection

Face-to-face [f2f]

Research instrument

In all surveys the same questionnaire with minimal changes was used. It included different modules, topically separate areas which had an aim of perceiving the living standard of households from different angles. Topic areas were the following: 1. Roster with demography. 2. Housing conditions and durables module with information on the age of durables owned by a household with a special block focused on collecting information on energy billing, payments, and usage. 3. Diary of food expenditures (weekly), including home production, gifts and transfers in kind. 4. Questionnaire of main expenditure-based recall periods sufficient to enable construction of annual consumption at the household level, including home production, gifts and transfers in kind. 5. Agricultural production for all households which cultivate 10+ acres of land or who breed cattle. 6. Participation and social transfers module with detailed breakdown by programs 7. Labour Market module in line with a simplified version of the Labour Force Survey (LFS), with special additional questions to capture various informal sector activities, and providing information on earnings 8. Health with a focus on utilization of services and expenditures (including informal payments) 9. Education module, which incorporated pre-school, compulsory primary education, secondary education and university education. 10. Special income block, focusing on sources of income not covered in other parts (with a focus on remittances).

Response rate

During field work, interviewers kept a precise diary of interviews, recording both successful and unsuccessful visits. Particular attention was paid to reasons why some households were not interviewed. Separate marks were given for households which were not interviewed due to refusal and for cases when a given household could not be found on the territory of the chosen census block.

In 2002 a total of 7,491 households were contacted. Of this number a total of 6,386 households in 621 census rounds were interviewed. Interviewers did not manage to collect the data for 1,106 or 14.8% of selected households. Out of this number 634 households

About this dataset

Context

The dataset tabulates the population of Roma by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Roma. The dataset can be utilized to understand the population distribution of Roma by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Roma. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Roma.

Key observations

Largest age group (population): Male # 10-14 years (633) | Female # 0-4 years (841). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Roma population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Roma is shown in the following column.
• Population (Female): The female population in the Roma is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Roma for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Roma Population by Gender. You can refer the same here

Background: Antithrombin (AT) is one of the most important regulator of hemostasis. AT Budapest 3 (ATBp3) is a prevalent type II heparin-binding site (IIHBS) deficiency due to founder effect. Thrombosis is a complex disease including arterial (ATE) and venous thrombotic events (VTE) and the Roma population, the largest ethnic minority in Europe has increased susceptibility to these diseases partly due to their unfavorable genetic load. We aimed to calculate the age and origin of ATBp3 and to explore whether the frequency of it is higher in the Roma population as compared with the general population from the corresponding geographical area. We investigated the association of ATBp3 with thrombotic events in well-defined patients' populations in order to refine the recommendation when testing for ATBp3 is useful.Methods and Results: Prevalence of ATBp3, investigated in large samples (n = 1,000 and 1,185 for general Hungarian and Roma populations, respectively) was considerably high, almost 3%, among Roma and the founder effect was confirmed in their samples, while it was absent in the Hungarian general population. Age of ATBp3—as calculated by analysis of 8 short tandem repeat sequences surrounding SERPINC1—was dated back to XVII Century, when Roma migration in Central and Eastern Europe occurred. In our IIHBS cohort (n = 230), VTE was registered in almost all ATBp3 homozygotes (93%) and in 44% of heterozygotes. ATE occurred with lower frequency in ATBp3 (around 6%); it was rather associated with AT Basel (44%). All patients with ATE were young at the time of diagnosis. Upon investigating consecutive young (

In agreement with historical documentation, several genetic studies have revealed ancestral links between the European Romani and India. The entire mitochondrial DNA (mtDNA) of 27 Spanish Romani was sequenced in order to shed further light on the origins of this population. The data were analyzed together with a large published dataset (mainly hypervariable region I [HVS-I] haplotypes) of Romani (N = 1,353) and non-Romani worldwide populations (N>150,000). Analysis of mitogenomes allowed the characterization of various Romani-specific clades. M5a1b1a1 is the most distinctive European Romani haplogroup; it is present in all Romani groups at variable frequencies (with only sporadic findings in non-Romani) and represents 18% of their mtDNA pool. Its phylogeographic features indicate that M5a1b1a1 originated 1.5 thousand years ago (kya; 95% CI: 1.3–1.8) in a proto-Romani population living in Northwest India. U3 represents the most characteristic Romani haplogroup of European/Near Eastern origin (12.4%); it appears at dissimilar frequencies across the continent (Iberia: ∼31%; Eastern/Central Europe: ∼13%). All U3 mitogenomes of our Iberian Romani sample fall within a new sub-clade, U3b1c, which can be dated to 0.5 kya (95% CI: 0.3–0.7); therefore, signaling a lower bound for the founder event that followed admixture in Europe/Near East. Other minor European/Near Eastern haplogroups (e.g. H24, H88a) were also assimilated into the Romani by introgression with neighboring populations during their diaspora into Europe; yet some show a differentiation from the phylogenetically closest non-Romani counterpart. The phylogeny of Romani mitogenomes shows clear signatures of low effective population sizes and founder effects. Overall, these results are in good agreement with historical documentation, suggesting that cultural identity and relative isolation have allowed the Romani to preserve a distinctive mtDNA heritage, with some features linking them unequivocally to their ancestral Indian homeland.

About this dataset

Context

The dataset tabulates the data for the Roma, TX population pyramid, which represents the Roma population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Roma, TX, is 53.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Roma, TX, is 29.5.
• Total dependency ratio for Roma, TX is 83.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Roma, TX is 3.4.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Roma population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Roma for the selected age group is shown in the following column.
• Population (Female): The female population in the Roma for the selected age group is shown in the following column.
• Total Population: The total population of the Roma for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Roma Population by Age. You can refer the same here

IntroductionRoma people in Europe are still in a great risk of social exclusion because of the stereotypes, prejudices, and discrimination against them, known as Antigypsyism. They also encounter high levels of poverty, lower levels of education, housing conditions, and health care, high rates of unemployment, and so on. Based on the push-pull theory, the present study examines the phenomenon of international migration of the Roma population from Olt County, Romania, capturing the specific factors that led to their migration and return to the country, and also the effects of this phenomenon on the community at the place of origin.Methodsour study used a mixed-methods approach, applying a non-standardized questionnaire to 796 Roma people who have experienced international, temporary migration and currently live in Olt County from Romania and semistructured interviews with 15 managers and representatives of the local public and socio-cultural institutions from the same region.Resultsthe results show us that the main push-pull factors of external migration of Roma people from Romania, as well as of their return home are economic and socio-cultural ones. Our data can add to the mentioned theory new pull factors for migration to certain countries, such as the friendly climate and easier learning of the language of the host country. We have also discovered that family is the main factor for returning home to Romania, and also the disappointment of their migration experience. The effects of their return migration on them and the community can be positive (e.g., cultural exchange, awareness of the role of education), but also negative (e.g., increasing unemployment, the negative image of Romania).Conclusionthe findings highlight some assumptions of the push-pull theory, but they also bring new perspectives for understanding and approaching this phenomenon. The perspectives of Roma and representatives of institutions are different regarding the push factors that generate external migration of Roma, Roma identify only economic factors that lead to migration, while managers and representatives also talk about socio-cultural factors involved in the decision to migrate of Roma. The study also identifies the implications generated by the return home of the Roma, with economic, socio-cultural, and educational effects, but also effects at the level of public policies. We believe that the push-pull factors of external migration and the effects of Roma's return to the country are interconnected, generating an amplification of the problems for which Roma migrate. Therefore, they constitute solid arguments for building and streamlining social integration policies for Roma.

Abstract

The Republic of Macedonia Multiple Indicator Cluster Survey (MICS) 2011 was conducted as part of the fourth global round of MICS surveys (MICS4). The survey was conducted in cooperation between UNICEF and the Institute of Public Health of the Republic of Macedonia with the data collection being carried out by private research company IPSOS Strategic Puls. Financial and technical support was provided by UNICEF, with additional financial support from the United Nations Population Fund (UNFPA). The Macedonia MICS 2011 was conducted using two separate samples. One sample developed specifically for the Roma population living in Roma settlements. The sample for the Roma settlements Macedonia MICS was designed to provide estimates for a large number of indicators on the situation of Roma children and women at the national level.

The 2011 Macedonia Multiple Indicator Cluster Survey primary objectives are: - To provide up-to-date information for assessing the situation of children and women in Macedonia; - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Macedonia and to strengthen technical expertise in the design, implementation, and analysis of such systems; - To generate data on the situation of children and women, including the identification of vulnerable groups and of disparities, to inform policies and interventions.

Geographic coverage

National

Analysis unit

• Individuals
• Households

Universe

The survey covered all de jure household members, all women aged between 15-49 years, all children under 5 living in the household, and all children aged 2-9 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the Roma settlements in the Macedonia Multiple Indicator Cluster Survey was to produce statistically reliable estimates of most indicators, for the Roma population living in Roma settlements at the national level.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.

The target national sample size for the Roma settlements in the Macedonia MICS was 1079 households.

For the calculation of the sample size, the key indicator used was the incidence of stunting among children aged 0-4 years. The resulting number of households from this exercise was 4,972 households which is the sample size needed to provide a sufficient number of children under 5 for drawing reliable conclusions. This sample size was reduced to 1,079 based on the original plan to stratify the listing in Roma sample PSUs by households with and without children under 5 for the second stage of selection. In this case a higher sampling rate would have been used for the households with children, similar to the sampling strategy for the national MICS. However, later it was decided that given the higher average number of children under 5 for the Roma households, the sampling procedure was simplified to select all households with equal probability in each Roma sample PSU at the second stage. The average number of households selected per cluster for the Macedonia Roma MICS was determined as 15 households, based on a number of considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster.

In total, 70 clusters were allocated to the regions with the number of clusters proportional to the population of the individual regions.

The 2002 census frame was used for the selection of clusters. Census enumeration areas were defined as primary sampling units (PSUs), and were selected from each of the sampling strata by using systematic pps (probability proportional to size) sampling procedures, based on the estimated sizes of the enumeration areas from the 2002 Population Census. The first stage of sampling was thus completed by selecting the required number of enumeration areas at the regional level.

Since the sampling frame (the 2002 Population Census) was not up-to-date, a new listing of households was conducted in all the sample numeration areas prior to the selection of households. For this purpose, listing teams were formed, who visited each enumeration area, and listed the occupied households. Listing activities were conducted by the same company that was responsible for the data collection. The same teams that were selected for the data collection process were used for listing. The listing took place in February 2012. All teams were given the descriptions and maps of the selected clusters. The teams visited all households in the sample clusters asking for the number of members, number of women aged 15-49 and for number of children under age 5.

Lists of households with household members were prepared by the listing teams for each enumeration area. The number of selected households per enumeration area was different, depending on the total number inhabitants in the enumeration area.

The sampling procedures are more fully described in "Macedonia Multiple Indicator Cluster Survey (MICS) 2011 - Final Report" pp.151-152.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Generic MICS were structured questionnaires based on the MICS4 model questionnaire with some modifications and additions. Household questionnaires were administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes household listing form, education, water and sanitation, household characteristics, child labour and child discipline.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49, children under age five and children aged 2-9 years. For children, the questionnaire was administered to the mother or primary caretaker of the child.

The women's questionnaire includes woman's background, child mortality, desire for last birth, maternal and newborn health, illness symptoms, contraception, unmet need, attitudes toward domestic violence, marriage/union, tobacco and alcohol use and life satisfaction.

The children's questionnaire includes child's age, birth registration, early childhood development, breastfeeding, care of illness, immunization and anthropometry.

The questionnaire form for child disability contained the ten question module for identifying children with an increased risk of disability.

The questionnaire form for vaccinations at health facility was used to check the consistency in recording the immunizations between the documents kept in the health facilities and the immunization cards in the households.

The questionnaires were based on the MICS4 model questionnaire. From the MICS4 model English version, the questionnaires were customized, translated into Macedonian and Albanian, back translated into English, and pre-tested in Skopje in March 2011. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

In addition to the administration of the questionnaires, fieldwork teams measured the weights and heights of children under 5 years of age. Details and findings of these measurements are provided in the respective sections of the report.

Cleaning operations

Data were entered using the CSPro software. The data were entered on 12 microcomputers and carried out by 20 data entry operators and 10 data entry supervisors. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS4 programme and adapted to the Macedonia questionnaire were used throughout. Data processing began almost simultaneously with data collection in May 2011 and was completed in August 2011. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program, Version 18, and the model syntax and tabulation plans developed by UNICEF were used for this purpose.

Response rate

Of the 1079 households selected for the sample, 997 were found to be occupied. Of these, 953 were successfully interviewed for a household response rate of 96 percent. In the interviewed households, 1134 women (aged 15-49 years) were identified. Of these, 1091 were successfully interviewed, yielding a response rate of 96 percent within interviewed households. There were 483 children under age 5 listed in the household questionnaire. Questionnaires were completed for 476 of these children, which correspond to a response rate of 99 percent within interviewed households. Overall, response rates of 92 and 94 percentages are calculated for the interviews with women and children under age 5.

Sampling error estimates

The sample of respondents selected in the Macedonia Multiple Indicator Cluster Survey is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data.

The following sampling error measures are presented for each of the selected indicators:

• Standard error (se): Sampling errors are usually measured in terms of standard

1. Reproductive asynchrony, a temporal mismatch in reproductive maturation between an individual and potential mates, may contribute to mate-finding failure and Allee effects that influence the establishment and spread of invasive species. Variation in elevation is likely to promote variability in maturation times for species with temperature-dependent development, but it is not known how strongly this influences reproductive asynchrony or the population growth of invasive species. 2. We examined whether spatial variation in reproductive asynchrony, due to differences in elevation and local heterogeneity in elevation (hilliness), can explain spatial heterogeneity in the population growth rate of the gypsy moth, Lymantria dispar (L.), along its invasion front in Virginia and West Virginia, USA. 3. We used a spatially explicit model of the effects of reproductive asynchrony on mating success to develop predictions of the influences of elevation and elevational heterogeneity on local population growth rates. Population growth rates declined with increased elevation and more modestly with increased elevational heterogeneity. As in earlier work, we found a positive relationship between the population growth rate and the number of introduced egg masses, indicating a demographic Allee effect. At high elevations and high heterogeneity in elevation, the population growth rate was lowest and the density at which the population tended to replace itself (i.e., the Allee threshold) was highest. 4. An analysis of 22 years of field data also showed decreases in population growth rates with elevation and heterogeneity in elevation that were largely consistent with the model predictions. 5. These results highlight how topographic characteristics can affect reproductive asynchrony and influence mate-finding Allee effects in an invading non-native insect population. Given the dependence of developmental rates on temperature in poikilotherms, topographic effects on reproductive success could potentially be important to the population dynamics of many organisms.

Roma populations by highest level qualification, with age, sex, main language and English language proficiency breakdowns across different geographical areas.

Thermal regimes can diverge considerably across the geographic range of a species, and accordingly, populations can vary in their response to changing environmental conditions. Both local adaptation and acclimatization are important mechanisms for ectotherms to maintain homeostasis as environments become thermally stressful, which organisms often experience at their geographic range limits. The spatial spread of the gypsy moth (Lymantria dispar L.) after introduction to North America provides an exemplary system for studying population variation in physiological traits given the gradient of climates encompassed by its current invasive range. This study quantifies differences in resting metabolic rate (RMR) across temperature for four populations of gypsy moth, two from the northern and two from southern regions of their introduced range in North America. Gypsy moth larvae were reared at high and low thermal regimes, then metabolic activity was monitored at four temperatures using stop-f...

For most of the 20th century, the invasive gypsy moth (Lymantria dispar) was the most serious insect threat to forests and shade trees in the northeastern United States, but outbreaks have been sporadic and light since 1989, after the successful establishment of a fungal pathogen, Entomophaga maimaiga. However, in 2016 a surprising new outbreak of gypsy moth began in southern New England, resulting in dramatic oak (Quercus spp.) mortality across thousands of forested hectares by 2018. In 2017, during the height of the outbreak, a rapid assessment of defoliation across 486 plots in six clusters (aka ‘hotspots’) across the Quabbin Watershed Forest in central Massachusetts was conducted. These sample points can be related to satellite-based defoliation estimates, and the tree and site data analyzed for predictors of defoliation severity.

Characterizing the current population structure of potentially invasive species provides a critical context for identifying source populations and for understanding why invasions are successful. Non-native populations inevitably lose genetic diversity during initial colonization events, but subsequent admixture among independently introduced lineages may increase both genetic variation and adaptive potential. Here we characterize the population structure of the gypsy moth (Lymantria dispar Linnaeus), one of the world's most destructive forest pests. Native to Eurasia and recently introduced to North America, the current distribution of gypsy moth includes forests throughout the temperate region of the northern hemisphere. Analyses of microsatellite loci and mitochondrial DNA sequences for 1738 individuals identified four genetic clusters within L. dispar. Three of these clusters correspond to the three named subspecies; North American populations represent a distinct fourth cluster, presumably a consequence of the population bottleneck and allele frequency change that accompanied introduction. We find no evidence that admixture has been an important catalyst of the successful invasion and range expansion in North America. However, we do find evidence of ongoing hybridization between subspecies and increased genetic variation in gypsy moth populations from Eastern Asia, populations that now pose a threat of further human-mediated introductions. Finally, we show that current patterns of variation can be explained in terms of climate and habitat changes during the Pleistocene, a time when temperate forests expanded and contracted. Deeply diverged matrilines in Europe imply that gypsy moths have been there for a long time and are not recent arrivals from Asia.

AbstractThe spongy moth, Lymantria dispar, is an irruptive forest pest native to Eurasia where its range extends from coast to coast and overspills into northern Africa. Accidentally introduced from Europe in Massachusetts in 1868–69, it is now established in North America where it is considered a highly destructive invasive pest. A fine-scale characterization of its population genetic structure would facilitate identification of source populations for specimens intercepted during ship inspections in North America and would enable mapping of introduction pathways to help prevent future incursions into novel environments. In addition, detailed knowledge of L. dispar’s global population structure would provide new insight into the adequacy of its current subspecies classification system and its phylogeographic history. To address these issues, we generated >2,000 genotyping-by-sequencing-derived SNPs from 1,445 contemporary specimens sampled at 65 locations in 25 countries/3 continents. Using multiple analytical approaches, we identified eight subpopulations that could be further partitioned into 28 groups, achieving unprecedented resolution for this species’ population structure. Although reconciliation between these groupings and the three currently recognized subspecies proved to be challenging, our genetic data confirmed circumscription of the japonica subspecies to Japan. However, the genetic cline observed across continental Eurasia, from L. dispar asiatica in East Asia to L. d. dispar in Western Europe, points to the absence of a sharp geographical boundary (e.g., the Ural Mountains) between these two subspecies, as suggested earlier. Importantly, moths from North America and the Caucasus/Middle East displayed high enough genetic distances from other populations to warrant their consideration as separate subspecies of L. dispar. Finally, in contrast with earlier mtDNA-based investigations that identified the Caucasus as L. dispar’s place of origin, our analyses suggest continental East Asia as its evolutionary cradle, from where it spread to Central Asia and Europe, and to Japan through Korea., MethodsMoth sampling The bulk of spongy moth specimens were collected during the summers of 2017 and 2018, using milk-carton type pheromone-baited traps. Additional samples (whole moths or parts thereof) from regions not fully covered by our network of traps were provided by colleagues who had collected them in the context of independent studies; with the exception of a few samples, collection dates for these were recent (overall, 93% of the moths used were collected between 2013 and 2018, and most specimens were males [only 0.8% of females]) DNA extraction and sequencing For DNA extraction, we sampled one antenna and three legs from each moth. These were frozen in liquid nitrogen and ground using a Retsch MM 200 mixer mill (Retsch technology, Haan, Germany). Then, DNA was extracted with the DNeasy 96 Blood & Tissue Kit (Qiagen, Carlsbad, CA, USA) following the manufacturer's instructions, with the exception of an additional RNase A treatment before the addition of buffer AL/ethanol (4 µL of 100 mg/mL Rnase A; 5 min digestion at room temperature). DNA concentration and purity of the extracts were assessed using a NanoDrop 8000 spectrophotometer (Thermo scientific, Waltham, MA, USA). Samples were diluted to 10 ng/μL prior to library construction. Libraries were prepared based on a genotyping-by-sequencing (GBS) protocol using the restriction enzymes PstI and MspI (Poland et al., 2012). Individuals were barcoded with unique sequences and pooled in multiplexes of 96 individuals per library. Moths from the same sampling site were randomized in the different libraries to reduce the chances of artifactual library effects being interpreted as a biological pattern. Library preparation and sequencing on Ion Torrent Proton P1v2 chips were carried out at the Genomic Analysis Platform of Université Laval, Quebec City, Canada (for a detailed description of the method, see Abed et al. 2019). GBS data The data consists of 1445 sequence individuals from 65 populations and sampled in 25 different counrties, The files Picq_EvolApp_SpongyMothBiosafe_Table_1_20221107.xlsx and Picq_EvolApp_SpongyMothBiosafe_Figure_population_localisation_20221018.docx give the details for each studied populations (localisation, effective etc.). Raw data 12 plates of 96 individuals; sequencing in 2018; sequencer ouput filename Cusson_p*_c01.fastq.txt.gz 4 plates of 96 individuals; sequencing in 2019; sequencer ouput filename Cusson_AGM_p*_c01.fastq.gz 1 plate de 96 individuals but only 10 individusals considered in the present project (popultion from Georgia); sequencing in 2020; sequencer ouput filename I.Giguere_BioSAFE_AGM_c01.fastq.gz The file providing the barcodes is named Picq_EvolApp_Spong... Visit https://dataone.org/datasets/sha256%3A3f2ad9c9ff4c8bd7187fc1d90acfdd0c5b4dd2a123fb491567d2d4bd12b515bc for complete metadata about this dataset.

Gypsy moth populations may exist for many years at low densities such that it may be difficult to find any life stages. Then, for reasons that are not completely understood, populations may rise to very high densities and substantial defoliation of the canopy may occur. These data shows the historical frequency (1972-2002) pattern of gypsy moth defoliation as it spreads south and west from the New England states. forested areas with repeated annual defoliation become more stressed and are at increased risk of permanent damage. More information about these resources, including the variables used in this study, may be found here: https://edg.epa.gov/data/Public/ORD/NERL/ReVA/ReVA_Data.zip.

Abstract

Since its inception in the mid-1990s, the Multiple Indicator Cluster Surveys programme, known as MICS, has become the largest source of statistically sound and internationally comparable data on children and women worldwide. In countries as diverse as Bangladesh, Thailand, Fiji, Qatar, Cote d’Ivoire, Turkmenistan and Argentina, trained fieldwork teams conduct face-to-face interviews with household members on a variety of topics – focusing mainly on those issues that directly affect the lives of children and women. MICS is an integral part of plans and policies of many governments around the world, and a major data source for more than 30 Sustainable Development Goals (SDGs) indicators. The MICS programme continues to evolve with new methodologies and initiatives, including MICS Plus, MICS Link, MICS GIS and the MICS Tabulator.

Geographic coverage

North Macedonia, Republic of (Roma Settlements) The majority of MICS surveys are designed to be representative at the national level. Sample sizes are sufficient to generate robust data at the regional or provincial levels, and for urban and rural areas. Subnational surveys, covering specific population groups (such as Palestinians in Lebanon) or specific geographical areas (such as selected regions of East in Afghanistan) within countries are also conducted.

Analysis unit

Household, Individual

Sampling procedure

Sample sizes vary greatly from one survey to the other, currently averaging around 12,000 households (for national surveys).

The sample for the Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for areas of residence, and for geographical locations, such as regions, governorates, or districts. A multi-stage, stratified cluster sampling approach was typickly used for the selection of the survey sample. MICS6 surveys are not self-weighting. For reporting national level results, sample weights were used. A more detailed description of the sample design can be found in Appendix A of Final Report.

Mode of data collection

Face-to-face [f2f]

Research instrument

MICS questionnaires were designed by implementing agencies, typically the National Statistical Offices. In each country, MICS questionnaires were based on an assessment of the country’s data needs. The starting point were the standard MICS questionnaires designed by UNICEF’s Global MICS Team, in close coordination with experts, development partners and other international survey programmes. Countries chose from the MICS modules in the standard MICS questionnaires. UNICEF’s MICS experts supported implementing agencies to customize the questionnaires, as required, to the national setting. All survey activities, from sample and survey design, to fieldwork and report writing are carried out by the implementing agencies – with continuous technical support from UNICEF.

The sixth round of MICS included six model questionnaires: • Household Questionnaire • Water Quality Testing Questionnaire • The Questionnaire for Individual Women • The Questionnaire for Individual Men • The Questionnaire for Children Age 5-17 and • The Questionnaire for Children Under Five

The flexible, modular nature of MICS questionnaires makes it easy to remove modules which may not be relevant, and modules for which there is already good quality data from other sources.

Refer to tools page on mics.unicef.org for more detailed information on the flow of questionnaires and contents of the modules.

Variation in thermal performance within and between populations provides the potential for adaptive responses to increasing temperatures associated with climate change. Organisms experiencing temperatures above their optimum on a thermal performance curve exhibit rapid declines in function and these supraoptimal temperatures can be a critical physiological component of range limits. The gypsy moth, Lymantria dispar (L.) (Lepidoptera: Erebidae), is one of the best-documented biological invasions and factors driving its spatial spread are of significant ecological and economic interest. The present study examines gypsy moth sourced from different latitudes across its North American range for sensitivity to high temperature in constant temperature growth chamber experiments. Supraoptimal temperatures result in higher mortality in northern populations compared with populations from the southern range extent (West Virginia and coastal plain of Virginia, U.S.A.). Sublethal effects of high te...

This dataset represents ethnic group (19 tick-box level) by highest level qualification, for England and Wales combined. The data are also broken down by age and by sex.

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021. This dataset shows population counts for usual residents aged 16+ Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.

These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.

For quality information in general, please read more from here.

Ethnic Group (19 tick-box level)

These are the 19 ethnic group used in this dataset:

• Asian, Asian British or Asian Welsh
  • Bangladeshi
  • Chinese
  • Indian
  • Pakistani
  • Other Asian
• Black, Black British, Black Welsh, Caribbean or African
  • African
  • Caribbean
  • Other Black
• Mixed or Multiple ethnic groups
  • White and Asian
  • White and Black African
  • White and Black Caribbean
  • Other Mixed or Multiple ethnic groups
• White
  • English, Welsh, Scottish, Northern Irish or British
  • Gypsy or Irish Traveller
  • Irish
  • Roma
  • Other White
• Other ethnic group
  • Arab
  • Any other ethnic group

No qualifications

No qualifications

Level 1

Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills

Level 2

5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma

Apprenticeship

Apprenticeship

Level 3

2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma

Level 4 +

Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)

Other

Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)