Among all federal subjects of Russia, the Ingushetia Republic had the lowest gross regional product (GRP) per capita in 2022, which was measured at 159.6 thousand Russian rubles. In the Chechen Republic, the figure was measured at around 207 thousand Russian rubles per person.

In 2024, **** million people in Russia lived below the poverty line, marking a considerable decrease compared to the previous year. The number of Russian residents that earned an income below the subsistence minimum was nearly ** million higher in 2000. What percentage of Russians live in poverty? Looking at annual figures, Russia’s poverty rate has declined since 2015, when it exceeded ** percent. Over ***** percent of the population of Russia lived below the national poverty line in 2024. Several other Central and Eastern European (CEE) countries, such as Bulgaria, Romania, and Latvia, reported higher poverty rates. Subsistence minimum in Russia Starting from January 1, 2025, the monthly per capita subsistence minimum in Russia stood at ****** Russian rubles for the working-age population and at ****** Russian rubles on average. That figure includes the cost of essential goods, such as food products, clothing, and medicines, and services, such as utilities and transportation expenses. The subsistence minimum was lower than the average wage in Russia, which was set at ****** Russian rubles from January 1, 2025.

This data collection consists of transcripts from 12 focus group discussions on themes related to social equality in Russia. The focus group discussions were conducted by the Institute of Applied Politics in Moscow, directed by Dr Kryshtanovskaya; using a discussion guide written by the Investigators. They were held in 12 cities chosen to represent different regions of the country, with an emphasis on provincial cities: Ufa, Kaliningrad, Ekaterinburg, Tiumen, Saratov, Ulyanovsk, Volgograd, Ivanovo, Irkutsk, Obolensk, Vladivostok and Protvino. The respondents included a mix of ages, genders, blue and white collar workers. The focus groups in Protvino and Ulyanovsk were held only for respondents age 18-29. The focus group discussions dealt with household and national economic change, perceptions of social fairness, and welfare values. Specifically, respondents were asked about the state of the national and local economies, their household economy, how they define rich and poor people and how they position themselves in relation to these categories. They were asked about whether they perceived differences in wealth between individuals, regions and between urban and rural areas as fair, and whether such differences are increasing or decreasing. Finally they were asked about whether the rich should take more responsibility for the welfare of the poor, about their own personal responsibility and that of the state and businesses, as well as about progressive income taxes and the degree to which the state should control the economy. The discussion guide is provided in Russian and English. Basic information about the respondents, including gender, age, and occupation are provided at the top of each focus group transcript. Each participant is identified by their given name only. The transcripts are provided in Russian. The Russian text was transcribed by the Institute of Applied Politics from audio files. A parallel set of focus groups was conducted in China and are available as the collection Social equality forum China: Focus group transcripts (see Related Resources). Taken together, Russia and China account for 41 per cent of the total territory of the BRICs and 63 per cent of their GDP/PPP. On Goldman Sachs projections China will be the world’s largest economy by 2050, and Russia its sixth largest. The project will seek to examine the following propositions: (1) that these two BRIC countries are becoming increasingly unequal; (2) that within them, political power and economic advantage are increasingly closely associated; (3) that their political systems have increasingly been employed to ensure that no effective challenge can be mounted to that combination of government position and economic advantage; (4) that set against a broader comparative perspective, an increasingly unequal society in which government is effectively immune from conventional challenge is likely to become increasingly regressive, or unstable, or both. Evidence will be drawn from official statistics, interviews with policy specialists and government officials, two dozen focus groups, and an analysis of the composition of the management boards of the largest companies in both countries. A final part of the analysis will employ crossnational evidence to test a series of hypotheses relating to the association between inequality and political instability on a more broadly comparative basis. Focus group discussions held in 12 Russian cities with 6 participants each drawn from a range of ages, both genders and different professions. Two focus groups were held for respondents age 18-29 only.

1.7 (%) in 2014. The amount of money required to bring the income of the poor to the subsistence minimum.

Over nine percent of children in Russia were estimated to fall into poverty additionally due to the economic crisis caused by the Russian invasion of Ukraine, based on the analysis from 2022. Russia had the most children among Eastern European and Central Asian countries. Furthermore, five percent of the Ukrainian child population was expected to experience poverty as a result of the economic shock. The economic decline caused by the war was also projected to increase adult poverty across the region, though to a lesser extent.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

National excluding: а) persons, doing their military service at the conscription or by contract; b) persons under imprisonment before trial and convicted; c) persons living in old people’s home, psycho-neurological hospitals and other closed institutions; d) persons living in remote or difficult for access regions of Far North and Far East; e) persons living in Chechnya and Ingushetia; f) persons residing in rural settlements with less than 50 inhabitants; g) homeless peoples

Analysis unit

Household Individual

Universe

National Population, Both sexes,18 and more years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 2500

At the first stage of selection of primary sampling units (PSU’s) urban and rural settlements will be selected. All the PSU’s are distributed among eight Federal districts (Northwestern, Central, Volga, Southern, North Caucasus, Ural, Siberian and Far Eastern), and in every Federal district, independently of each other - by strata according to the number of their population: cities with 1 million and more population; cities with from 500 thousands up to 1 million population; cities with from 100 thousands up to 500 thousands population, urban settlements with up to 100 thousands population, rural settlements.

Mode of data collection

Face-to-face [f2f]

Research instrument

For each wave, suggestions for questions are solicited by social scientists from all over the world and a final master questionnaire is developed in English. Since the start in 1981 each successive wave has covered a broader range of societies than the previous one. Analysis of the data from each wave has indicated that certain questions tapped interesting and important concepts while others were of little value. This has led to the more useful questions or themes being replicated in future waves while the less useful ones have been dropped making room for new questions.

The questionnaire is translated into the various national languages and in many cases independently translated back to English to check the accuracy of the translation. In most countries, the translated questionnaire is pre-tested to help identify questions for which the translation is problematic. In some cases certain problematic questions are omitted from the national questionnaire.

WVS requires implementation of the common questionnaire fully and faithfully, in all countries included into one wave. Any alteration to the original questionnaire has to be approved by the EC. Omission of no more than a maximum of 12 questions in any given country can be allowed.

Response rate

76%

Sampling error estimates

Estimated error: 2.0

Abstract

The World Bank Group is interested in gauging the views of clients and partners who are either involved in development in Russia or who observe activities related to social and economic development. The World Bank Group Country Opinion Survey will give the World Bank Group's team that works in Russia, greater insight into how the Bank's work is perceived. This is one tool the World Bank Group uses to assess the views of its stakeholders, and to develop more effective strategies that support development in Russia.

The survey was designed to achieve the following objectives: - Assist the World Bank Group in gaining a better understanding of how stakeholders in Russia perceive the World Bank Group; - Obtain systematic feedback from stakeholders in Russia regarding: · Their views regarding the general environment in Russia; · Their overall attitudes toward the World Bank Group in Russia; · Overall impressions of the World Bank Group’s effectiveness and results, knowledge work and activities, and communication and information sharing in Russia; · Perceptions of the World Bank Group’s future role in Russia. - Use data to help inform Russia country team’s strategy.

Geographic coverage

National coverage

Analysis unit

Stakeholder

Kind of data

Sample survey data [ssd]

Sampling procedure

In February-June 2014, 393 stakeholders of the World Bank Group in Russia were invited to provide their opinions on the World Bank Group's assistance to the country by participating in a country survey. Participants in the survey were drawn from the office of the President; the office of the Prime Minister; office of a minister; office of a parliamentarian; ministries, ministerial departments, or implementation agencies; consultants/contractors working on World Bank Group-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials; bilateral and multilateral agencies; private sector companies; private foundations; the financial sector/private banks; NGOs; community based organizations; the media; independent government institutions; trade unions; academia/research institutes/think tanks; the judiciary branch; and other organizations.

Mode of data collection

Other [oth]

Research instrument

The questionnaire consists of 9 Sections:

A. General Issues Facing Russia: Respondents were asked to indicate whether Russia is headed in the right direction, what they thought were the top three most important development priorities in the country, which areas would contribute most to reducing poverty and generating economic growth in Russia, and how “shared prosperity” would be best achieved in Russia.

B. Overall Attitudes toward the World Bank Group (WBG): Respondents were asked to rate their familiarity with the WBG, the WBG’s effectiveness in Russia, WBG staff preparedness to help Russia solve its development challenges, their agreement with various statements regarding the WBG’s work, and the extent to which the WBG is an effective development partner. Respondents were asked to indicate the WBG’s greatest values and weaknesses, the most effective instruments in helping reduce poverty in Russia, with which stakeholder groups the WBG should collaborate more, in which sectoral areas the WBG should focus most of its resources (financial and knowledge services), and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Group’s Effectiveness and Results: Respondents were asked to rate the extent to which the WBG’s work helps achieve development results in Russia, the extent to which the WBG meets Russia’s needs for knowledge services and financial instruments, and the WBG’s level of effectiveness across thirty-three development areas, such as economic growth, governance, private sector development, education, and job creation.

D. The World Bank Group’s Knowledge Work and Activities: Respondents were asked to indicate how frequently they consult WBG’s knowledge work and activities and to rate the effectiveness and quality of the WBG’s knowledge, including how significant of a contribution it makes to development results and its technical quality.

E. Working with the World Bank Group: Respondents were asked to rate their level of agreement with a series of statements regarding working with the WBG, such as the WBG taking decisions quickly in Russia, imposing reasonable conditions on its lending/ investments, disbursing funds promptly, increasing Russia’s institutional capacity, and providing effective implementation support.

F. The Future Role of the World Bank Group in Russia: Respondents were asked to indicate what the WBG should do to make itself of greater value in Russia, and which services the WBG should offer more of in the country.

G. Russia’s Role as a Global Donor for Development: Respondents were asked about their views on Russia’s role as a donor providing assistance to developing/poor countries.

H. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the WBG, and their usage and evaluation of the WBG’s websites and social media channels. Respondents were also asked about their awareness of the WBG’s Access to Information policy, past information requests from the WBG, and their level of agreement that they use more data from the WBG as a result of the WBG’s Open Data policy.

I. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the WBG, their exposure to the WBG in Russia, which WBG agencies they work with, and their geographic location.

The questionnaire was prepared in English and Russia.

Response rate

A total of 139 stakeholders participated in the survey (35% response rate).

0.6 (%) in 2014. The amount of money required to bring the income of the poor to the subsistence minimum.

The overall state of financial inclusion in Russia is relatively advanced along certain basic metrics. The number of adults with accounts at a financial institution stands at 67.4 percent, which compares well to the Europe and Central Asia (ECA) regional average of 51.4 percent. Account penetration has increased by nearly 20 percentage points since 201l, with increases experienced across all segments of the population, including for the poorest 40 percent and for women.1 Russia also has a large number of regulated financial institutions and enjoys 36.98 branches per 100,000 adults, higher than for the United States (32.39) and China (24.03). In addition, usage of accounts and other financial services remains low among the underserved, as does the available range and quality of financial products and services. The main mode for retail payments is still via cash; while underserved individuals may own accounts, many consumers withdraw the full amount they receive from regular government payments or salaries. Most credit and deposit-taking activity still occurs among the middle-high income segments of the population, and there appear to be gaps in terms of both the availability and usage of appropriate savings products for the underserved. The microcredit products that are available to the underserved are of poor quality. There are low levels of trust in the formal financial sector among the Russian population, in particular for microfinance institutions (MFIs).

The monthly minimum wage in Russia as of January 1, 2025, amounted to ****** Russian rubles, or approximately *** U.S. dollars using the exchange rate as of February 28, 2025. In the capital Moscow, it was set at ****** Russian rubles, or around *** U.S. dollars. In the country's second-largest city, Saint Petersburg, it was lower, at ****** Russian rubles. Since 2021, the minimum wage in Russia has been calculated as 42 percent of the median wage. Between 2018 and 2020, it equaled to the minimum cost of living that was set in the country. The poor and the rich in Russia Around ** million residents lived under the poverty line in Russia. Those earning the highest 20 percent of income accounted for approximately ** percent of the total composite monetary income in 2023, while the group with the lowest income had a ***-percent share. Regional disparities The economic disparity was also observed across Russian federal subjects. The median monthly wage ranged from ****** Russian rubles in the Kabardino-Balkaria Republic to ****** Russian rubles in the Chukotka Autonomous Okrug between September 2018 and August 2019. Minimum wage thresholds can be regulated by regional authorities, as long as they are not lower than the federal minimum wage.

Mukhrino Field Station is owned and run by the UNESCO Chair on Environmental Dynamics and Climate Change at the Yugra State University, Khanty-Mansiysk, Russia. The Mukhrino Field Station is located at the east bank of the Irtysh River near the confluence with the Ob River in the central taiga area of Western Siberia (60°54’ N, 68°42’ E), 30 km south-west of the town of Khanty-Mansiysk (60 000 inhabitants). Due to the severe continental climate, the environmental conditions in the region are comparable with the sub-arctic zone of Northern Europe. The research site is representative for the Western Siberian pristine carbon accumulating peatland ecosystem (“plain mires”). The mires cover c. 60 % of the land surface and can be regarded as important sources/sinks of greenhouse gases and aerosols. The main mire type of the site is raised bogs of the type Pine-dwarf shrubs-bogs (Ryam) characterized by pine trees, Ledum palustre and dwarf shrubs, with areas of Sphagnum fuscum. Interspersed are mires of the type Poor fens (partly drained in the summer) dominated by Carex lasiocarpa and other graminoids, and Sphagnum balticum. Also ridge-hollow complexes, consisting of bog ridges and poor fen hollows are present.

Household Income per Capita: Avg per Month: SF: Volgograd Region data was reported at 41,393.000 RUB in 2024. This records an increase from the previous number of 34,903.000 RUB for 2023. Household Income per Capita: Avg per Month: SF: Volgograd Region data is updated yearly, averaging 12,530.700 RUB from Dec 1994 (Median) to 2024, with 31 observations. The data reached an all-time high of 41,393.000 RUB in 2024 and a record low of 135.700 RUB in 1994. Household Income per Capita: Avg per Month: SF: Volgograd Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA012: Household Income per Capita: by Region: Annual.

Household Income per Capita: Avg per Month: NW: Republic of Karelia data was reported at 62,254.000 RUB in 2024. This records an increase from the previous number of 49,783.000 RUB for 2023. Household Income per Capita: Avg per Month: NW: Republic of Karelia data is updated yearly, averaging 14,293.000 RUB from Dec 1994 (Median) to 2024, with 31 observations. The data reached an all-time high of 62,254.000 RUB in 2024 and a record low of 266.400 RUB in 1994. Household Income per Capita: Avg per Month: NW: Republic of Karelia data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA012: Household Income per Capita: by Region: Annual.

10.8 (%) in 2015. Population with money income lower than the minimum subsistence level is based on the data on distribution of population by per capita money income and is calculated by comparison with minimum subsistence level (percent of total population, January-December).

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

Sample excludes remote or difficult-to-access areas in the Far North, North Caucasus, and Far East (Nenets autonomous region, Yamalo-Nenetsautonomous region, Chukotsk region) as well as other remote or difficult-to-access districts. The excluded areas represent about 20% of the population.

Analysis unit

Individuals

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Observation data/ratings [obs]

Sampling procedure

The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world's population (see Table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size was 2000.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

This project aimed to explore how the isolation that women in Russia's penal institutions suffer shapes their experiences of custody and re-entry into society. 65 prisoners, 21 ex-prisoners, 30 prison personnel, and 71 local inhabitants of penal regions were interviewed, forming 186 semi-structured, face-to-face interview transcripts. Another 300 prisoners completed self-completion questions between 2007 and 2009. At the end of 2004, there were approximately 36,000 women imprisoned in 40 of Russia's penal colonies.The majority were held at considerable distances from home, often in remote places difficult for their relatives to access. The negative influence of distance on prisoners - its contribution to high rates of recidivism and poor prisoner mental and physical health - is recognised by the post-Soviet authorities. In reforms to the 'correctional code', Russia has pledged itself to holding prisoners near to home, but women are excluded from this provision. The research will examine how the isolation suffered by women in Russia's penal system shapes their experiences of custody and the decisions they make at the end of their sentences. The project is the first systematic study of the geography of imprisonment in Russia. It will involve first-hand research in penal colonies in three regions and will employ both quantitative and qualitative methods. In addition to women prisoners, the researchers will conduct interviews with prison officers, other members of the penal service and voluntary organisations. The results will be analysed in the context of the continuities and changes in Russia's broader penal geography in the past two decades. A total of 187 face-to-face semi-structured interviews were carried out with current prisoners, former prisoners, prison personnel and local inhabitants of penal regions. Self-completion questionnaires were also carried out by 300 prisoners. Volunteer sampling was used for this repeated cross-sectional project.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Objective: To evaluate the prevalence and geographic distribution of overweight and obesity in Russian adults aged 25–64 years as well as the association between chronic risk factors and obesity. Methods: Data were obtained from the survey “Epidemiology of Cardiovascular Diseases and Its Risk Factors in Some Regions of the Russian Federation” (ESSE-RF). This is a large cross-sectional multicenter population-based study that included interviews and medical examination (anthropometry, blood pressure [BP] measurement, and laboratory analysis) applied in 2012–2014. Results: The sample included 20,190 adults (response rate 79.4%) aged 25–64 years. Approximately one third of participants (30.3%) had obesity and another third (34.3%) were classified as overweight. BMI increased with age in both sexes. The prevalence of obesity between regions ranged from 24.4 to 35.5%. Overweight and obesity levels decreased with higher education (men only). Overall obesity rates were higher in rural than urban populations, but rates of overweight were similar in rural and urban populations. Participants with obesity were more likely to have BP > 160/100 mm Hg (odds ratio > 2.0) and also > 140/90 mm Hg, raised blood glucose, and high triglycerides. Conclusion: The prevalence of overweight and obesity in Russian adults aged 25–64 years is not evenly distributed geographically, but it is comparable to that of other European countries. Individuals with obesity were also more likely to have indicators of poor cardiovascular and metabolic health.

8,905 (Rubles) in 2015. Represents cost estimate of consumer goods basket as well as statutory payments and fees. Consumer goods basket includes minimum set of food and non-food products and services needed for maintenance of human health and life support. It is established both on national level by Federal law and on regional level by regional authorities. Minimum subsistence level is determined in average per capita on the quarterly base for three socio-economic groups of population (working-age population, retirees and children) by the Government of the Russian Federation.

Shifting sands with sparse pine forests are rare landscapes in the biome of temperate broadleaf and mixed forests. Pine forests on the shifting sands are the state natural movement of regional level in Kaluga Region. This site is place of growing of many rare plant species, especially associated with poor soils. Our dataset summarizes findings of beetles in this natural monument and surroundings during 1998-2020.