In 2023, it was estimated that around ** percent of people in the United States living with a disability were in poverty. In comparison, the poverty rate among people in the U.S. without a disability was **** percent. A disability is any physical or mental condition that significantly impacts a person's ability to carry out daily tasks or life activities. How many people in the United States are disabled? In 2023, around ** percent of people in the United States were thought to be living with a disability. Types of disabilities include those that affect hearing, cognition, self-care, mobility, and vision. The most common type of disability in the United States is ambulatory disabilities, which impairs a person’s ability to walk. In 2023, almost ** percent of those aged 75 years and older in the U.S. had an ambulatory disability. However, disabilities are far less common among younger people, with less than **** percent of those aged 21 to 64 suffering from an ambulatory disability. Employment among the disabled The most obvious reason why the poverty rate among those with a disability is higher than those without a disability is because disabilities affect a person’s ability to work and be employed. In 2023, the employment rate for those with a disability was **** percent, compared to an employment rate of **** percent among those without a disability. Those with hearing disabilities are the most likely to be employed, with a rate of around ** percent, compared to an employment rate of ** percent among those with an ambulatory disability. Still, those with disabilities who do work have lower annual median earnings than those without disabilities. In 2023, the annual median earnings for U.S. adults without a disability were ****** U.S. dollars, compared to ****** U.S. dollars for those with a disability.

In 2023, around **** percent of persons with a disability in the United States were living below the national poverty line. However, **** percent of persons with a disability lived at or above *** percent of the poverty level.

In 2022, it was estimated that around 26 percent of people in the United States living with a disability were in poverty. In comparison, the poverty rate among people in the U.S. without a disability was 11.5 percent. A disability is any physical or mental condition that significantly impacts a person's ability to carry out daily tasks or life activities.

How many people in the United States are disabled? In 2022, around 14 percent of people in the United States were thought to be living with a disability. Types of disabilities include those that affect hearing, cognition, self-care, mobility, and vision. The most common type of disability in the United States is ambulatory disabilities, which impair a person’s ability to walk. In 2021, almost 30 percent of those aged 75 years and older in the U.S. had an ambulatory disability. However, disabilities are far less common among younger people, with less than five percent of those aged 21 to 64 suffering from an ambulatory disability.

Employment among the disabled The most obvious reason why the poverty rate among those with a disability is higher than those without a disability is because disabilities affect a person’s ability to work and be employed. In 2022, the employment rate for those with a disability was 44.5 percent, compared to an employment rate of 79 percent among those without a disability. Those with hearing disabilities are the most likely to be employed, with a rate of around 56 percent, compared to an employment rate of 27 percent among those with an ambulatory disability. Still, those with disabilities who do work have lower annual median earnings than those without disabilities. In 2022, the annual median earnings for U.S. adults without a disability was 55,208 U.S. dollars, compared to 46,887 U.S. dollars for those with a disability.

This report was written in collaboration between the Mayor's Office of Innovation and the Rochester Monroe Anti-Poverty Initiative (RMAPI) and released in December 2019. Executive SummaryThe Rochester Monroe Anti-Poverty Initiative (RMAPI) has selected single female headed households with children as one of its key target populations in which to focus strategy and its next phase of initiatives. This report is intended to provide additional insight on this population to support the next phase of RMAPI’s strategic planning as well as broader advocacy efforts on behalf of this population.

We begin with a brief summary of historic policy and societal factors known to have contributed to the current day inequities, written in collaboration with content experts from RMAPI.

The core of this report is a fact sheet based on analysis of US Census data. Major findings include:

Finding 1: Families headed by unmarried parents are a significant segment of the city population and account for the majority of individuals living below the poverty level in the city.

Finding 2: Unmarried households with children experience lower incomes, lower rates of home ownership, and higher rent burdens compared to their married counterparts

Finding 3: Women and people of color are overrepresented among the heads of unmarried households with children.

Finding 4: Four in ten unmarried householders with children have less than a high school education. Nearly 80 percent of those without a high school education are in poverty.

Finding 5: Unmarried householders with children in poverty are more likely to be disabled or face other common barriers to employment.

Finding 6: The more adults present in unmarried households with children, the less likely that household is to be in poverty. This trend amplifies when considering the number of employed adults.

Finding 7: Unmarried parents under age 40 head the majority of all households with children in Rochester. Younger householders correlate with higher poverty rates regardless of marriage status.

Finding 8: A birth before age 20, being unmarried, and having not completed high school education are three factors that, when compounded, are associated with poor economic outcomes.

Finding 9: The highest densities of unmarried householders with children are clustered in the highest poverty neighborhoods in the city of Rochester

We end with a discussion of the gaps in available data, acknowledging that there is room for further investigation and interpretation, data collection, and insights. We recommend readers to think critically about what is presented and how it might impact their own work in poverty reduction efforts. We present a series of questions that are a jumping off point for new inquiry and reflection. Methodology can be found in the Appendix.

Data Source:2017 Census American Community Survey 5-Year Estimates, Public Microdata SampleData and documentation can be accessed here:https://www.census.gov/programs-surveys/acs/data/pums.html

Background: The unprecedented number of elderly individuals in China presents a serious public health challenge. Limited data are available on the prevalence of disability or factors resulting in disability among the elderly in China. Objective: We aimed to assess the prevalence of disability and related risk factors among the elderly of Xiamen, China. Methods: A cross-sectional study was performed on individuals who were ≥60 years of age. The subjects were recruited by multi-stage sampling; a total of 14,292 valid questionnaires were received. Study measurements included activities of daily living (ADL), demographics, and health status. The ADL was assessed by the Katz Index Scale to evaluate disability. Chi-square tests and binary logistic regression were used to identify factors associated with disabilities. Results: Among the valid participants, 4.27% had at least one disability. Bathing was the most frequently reported disability and feeding was the least frequently reported disability. Disabilities were significantly associated with female gender, older age, unmarried status, living with family, urban residence, illiteracy, poor economic status, self-rated bad health, chronic illnesses, lower life satisfaction, bad mood, and feelings of loneliness. Conclusion: Functional disability among the elderly requires more public attention. Culturally appropriate policies and programs are also needed to address the care for the disabled elderly. Assessment of disability among the elderly in Xiamen of China a representative sample survey sample of 14,292 older adults

This survey, conducted by the newspaper Helsingin Sanomat in 2015, charted Finnish views on poverty and social security. The survey was conducted as part of the "Two Finlands - growing inequality" project, which in turn was part of the "Is Finland Becoming Polarized?" programme funded by Kone Foundation. The survey included two open-ended questions, q8 "Describe a person who is poor in Finland; how do you recognise a poor person?" and q9 "What kind of standard of living should a poor person settle for in Finland; what kind of life should the person have a chance at?", which received a large number of responses (q8 N:5,718 and q9 N:5,726) and can be utilised in qualitative analysis. Open-ended responses are only available in Finnish. First, the respondents' perceptions of poverty and the reasons for poverty were charted with statements concerning, for example, whether they thought that people who are poor had bad luck, did not have the same chances in life as other people, or were lazy, and that the level of social security benefits was too low or that poverty was an inevitable part of contemporary development. The respondents' trust in other people and in authorities was examined next and several statements were presented on basic social assistance. The statements included, for instance, whether the respondents thought that most people who received social assistance really needed it or that many applied for social assistance on fraudulent grounds. The respondents were also asked whether they agreed or disagreed with several statements on social security in general (e.g. whether differences in living standards were too large in Finland, people should take more responsibility of themselves, and rich people were greedy). Next, the respondents were asked to place their own social standing on a scale from those who are worst off to those who are best off. Challenging situations in life were examined with questions on how closely the respondents had experienced various situations, such as long-term unemployment, over-indebtedness, serious mental health problems, or substance abuse problems, during the previous two years. Questions also focused on the respondents' opinions regarding the help provided by society to various groups of people (e.g. the long-term unemployed, disabled or homeless persons, or those who were victims of violent crimes or had been lonely for a long time). Background variables included, among others, the respondent's gender, age, income, household size, highest level of education, NUTS2 and NUTS3 regions of residence, and degree of urbanisation of municipality of residence.

This report was written in collaboration between the Mayor's Office of Innovation and the Rochester Monroe Anti-Poverty Initiative (RMAPI), and released in July 2017. Executive SummaryThe purpose of this report is to explore the demographic and earning disparities in the local workforce in Monroe County. It focuses on people who live in poverty, despite being employed, and aims to help the community better understand major contributing factors preventing residents from becoming self-sufficient. It is meant to augment and contextualize existing data on the state of poverty in Rocheser and to inform the strategy deployed by the Rochester Monroe Anti-Poverty Initiative.This report includes analysis on the correlations between the industries in which Rochester residents in poverty are employed, the wages they earn, and the hours that they work. It also examines these factors by race, gender, educational attainment, and physical ability. Through the analysis of several data sources, inlcuding the U.S. Census Public Use Microdata Sample, the Office of Innovation examines how the intersection of these factors contributes to Rochester's poverty landscape. Key findings outlined in this report include:• Many part-time and seasonal workers live in poverty or are not self sufficient.• Minorities are over-represented in several key service industries.• The industries with over-representation of minorities also tend to be the county’s lowest paying and largest sectors.• Minorities earn less than their white counterparts in nearly every industry sector.• Regardless of educational attainment, the wage gap between whites and minorities persists.The report concludes that wages play a key role in preventing minorities, women, and the disabled from achieving self-sufficiency in Rochester. The recommended next steps for RMAPI are to engage employers and lawmakers in the industry sectors where minorities are both underpaid and over-representated and work towards increasing wages to help meet the goal of increasing self-sufficiency and reducing poverty in Rochester by 50% over the next 15 years.Data Source:2015 Census American Community Survey 5-Year Estimates, Public Microdata SampleData and documentation can be accessed here:https://www.census.gov/programs-surveys/acs/data/pums.html

The Vulnerable Population Index (VPI) is intended to guide location selection and stakeholder identification for public involvement and inform Title VI and Environmental Justice (EJ) performance measurement. The Baltimore Regional Transportation Board uses data from the US Census Bureau to determine the concentrations of seven sensitive populations for the region and for each census tract. A tract with a concentration of a sensitive population greater than the concentration of the Baltimore region as a whole is considered to be “vulnerable” for the sensitive population. The Vulnerable Population Index (VPI) indicated the number of vulnerable populations for each tract, and thus provides a general indication of the extent to which each tract is vulnerable. The VPI looks at the following variables:Population in Poverty (American Community Survey 2006-2010 5-Year Estimates)Age 75 and up (Census 2010) Non-Hispanic Minority (people who are non-White and non-Hispanic) (Census 2010) Hispanic or Latino Heritage (Census 2010)Limited English Proficiency (population who speaks English “not well” or “not at all.”) (American Community Survey 2006-2010 5-Year Estimates)Households with No Car (American Community Survey 2006-2010 5-Year Estimates)Disabled Population (Census 2000) This data was used in the interactive mapping application found at http://gis.baltometro.org/Application/VPI/index.html. For more information on Transportation Equity work and studies at BMC, go to http://www.baltometro.org/about-the-brtb/transportation-equity. Note that for ACS and Census 2000 data margins of error are not provided. This data has been modified by the Baltimore Metropolitan Council and should not replace data directly loaded from the Census.Source: Variables are American Community Survey 2006-2010 5-Year Estimates, the 2000 Census (SF3), and the 2010 Census. Census tracts are the 2010 Census. Main Index is calculated by BMC.Date: Index published in May 2015. Date of raw data is either 2000, 2010, or 2006-2010 depending on the variable. See the above list for more information.Update: The VPI is updated approximately every 5 years. Data will be added as a separate layer.Data fields:PCT_NotWhite_NotHisp - Percent of the population in each tract that is a non-Hispanic minority. PCT_Hispanic - Percent of the population in each tract that is Hispanic or Latino. Pct75up - Percent of the population in each tract that is age 75 or higher. PCT_LEP - Percent of the Limited English Proficiency population in each tract.PCT_People_in_Poverty - Percent of the population in each tract that is living below the Federal poverty level.PCT_NOCAR - Percent of households in each tract that do not have a car.PCT_Disabl - Percent of the population in each tract that is disabled. Reg_NotWhite_NotHisp - Regional average for the population that is a non-Hispanic minority. This is for the same time period as the tract data. Reg_Hispanic - Regional average for the population that is Hispanic or Latino. This is for the same time period as the tract data. Reg_75up - Regional average for the population that is age 75 or higher. This is for the same time period as the tract data. Reg_LEP - Regional average for the Limited English Proficiency population. This is for the same time period as the tract data. Reg_Poverty - Regional average for the population that is living below the Federal poverty level. This is for the same time period as the tract data. Reg_NOCAR - Regional average for percent of households that do not have a car. This is for the same time period as the tract data. Reg_Disabl - Regional average for the population that is disabled. This is for the same time period as the tract data. FLAG_NotWhite_NotHisp - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_Hispanic - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_75up - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_LEP - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_Poverty - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_NOCAR - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_Disabl - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". INDEX - The sum of all the FLAG fields.

This research project tackled the complex problem of how to increase participation in social and cultural life for all as we age which has been shown to make a vital contribution to raising quality of life. The project addressed the fundamental issue that arts and cultural participation drops dramatically in older populations and that disabled, Black, Asian and minority ethnic and older people living in poverty are even less likely to participate. It tackled inequalities related to accessibility and content of digital arts and cultural provision, enabled vital R&D and established new business models to encourage digital innovation in the arts and cultural sector to support healthy ageing.

The project included exploration of the everyday lives of minoritized older adults. Throughout the project methods of doing co-design with minoritized older adults were designed. The project worked alongside older adults, creative industry players and community sector and cultural sector organisations to co-design digital arts and cultural experiences that support social connections and contribute to improved quality of life for older adults.

It supported creative industries to build a better understanding of diverse older audiences and to robustly evaluate their offer; and provided new evidence based policy making that sought to tackle inequalities in arts and cultural provision for healthy ageing outcomes.

This data set includes Interviews held towards the end of the Connecting through Culture as we Age research project. The interviews were a point of reflection on the participation of older adult co-researchers and partners reflecting on co-design in Connecting through Culture as we Age. The project recruited 20 minoritised older adults who identified as disabled, socioeconomically and/or racially minoritised and worked with them through the 3 years of the project which involved creative, participatory design based methods. The project funded 6 prototype teams that emerged during the project and included older adult co-researchers. We worked closely with community and cultural sector organisations throughout the co-design process.

Abstract Introduction Disabled people is anybody that has physical, intellectual, social or emotional alteration. They can have impediments that last for a short period of time or for the entire life. Objective Describe the clinical profile of disabled patients admitted to Instituto de Saúde da Criança do Amazonas (ICAM). Material and method Thirty-four patients were analyzed, data such as gender, age, origin, basis pathology and oral health condition were collected. The data obtained were organized and tabulated in Microsoft Excel 2013. Result There was a prevalence of males with 70% and 30% females. The age group had a predominance of 8 years. Most of the patients 60% were from Amazonas inland cities and 40% from the capital. Regarding to the pathology, Neurological Disease was prevalent in 44% of the cases, followed by the following: Down Syndrome 18%, Autistic Spectrum Disorder 12%, Myelomeningocele 12%, Deafness 3%, Diabetes 3%, Prader Willi Syndrome 3%, Moebius Syndrome 3% and Lenox Syndrome 3%. Concerning to oral condition, 44% showed a poor oral condition, 32% deficient and 24% satisfactory. Conclusion Most of the children were male, 8 years old, from Amazonas inland cities, with neurological deficiency and poor oral condition, suggesting that the presence of the dental surgeon composing the multidisciplinary hospital team helps to outline a preventive and curative treatment plan suitable for these individuals.

Abstract

The main purpose of the data collection is to address and analyze issues related to total income, expenditure and consumption levels and structures of both households and the main socio-economic groups. The Household Budget Survey (HBS) provides a source of information on qualitative and quantitative indicators of standard of livings in Latvia. The household is the basic unit of the survey. It is defined as a person or group of persons tied by relationship or other personal relations, having common subsistence expenditures and inhabiting the same living unit (house, flat, etc.), maintenance of which is covered by such persons jointly. The survey comprises information on the structure of the households, their revenue and consumer expenditures, employment of the household members, living conditions, possession of consumer durables, access to health care, culture, education, as well as subjective assessments of the households' level of welfare.

The HBS data will allow us to address the following issues: - Information on income and consumption, characteristics of consumption in relation to different social layers, number of household members, children etc.; - Information for calculation of consumer price index; - Linkages between different components of material welfare, e.g., revenue and living area conditions, revenue and access to consumer durable in households, etc.;information for various statistical purposes, e.g., for calculation of gross domestic product for the national account statistics; - Level of consumption of food products, components of nutritive and calorie consumption in different groups of households; - Indicators of poverty, to investigate the spread of poverty into different layers of society.

In the context of the envisaged reform of the social security system, the survey shall enable monitoring and evaluation of social policies with respect to: - Improvement of social aid to different socially vulnerable groups; - Reform of social security system; - Poverty problems in the state.

The survey is multi-functional. This means, that even during the preparatory phase of the survey the scope of issues included can be changed or amplified if necessary by adding or substituting relevant sets of the survey. The HBS is organized with the expectation that the results will be used by a wide spectrum of users. The CSB will publish the data of the survey in the form of tables, and prepare analytical reports and statistical bulletins. It is foreseen to make the basic data files available on magnetic information carriers to a range of users. These microfiles will contain the basic data of the survey on a quarterly basis, having discarded any identification signs that would allow the identification of individual households.

Geographic coverage

The data are collected over three main domains, Riga and large cities, small towns and villages in rural areas.

Analysis unit

Households

Universe

The target population of the HBS consists of all households in Latvia. Persons living in institutional households (elderly people boarding house, disabled children boarding house, student hostels, hotels, barracks, hospitals, sanatoriums, penal institutions, etc.) and homeless people are excluded from the current survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

During the preparation stage of the survey it was decided to use the population register formed in the early 90s as the sampling frame. At the beginning of 1995, it included more than 99% of the Latvian population. In the pre-pilot survey in 1995 we found out that due to the different mistakes in the population register, several households were not found in the given addresses. Almost 10% of the entries of the register were outdated. Some respondents were dead. Other deficiencies were found with the addresses, physically non-existing addresses were also ascertained as well as other mistakes with the register. One should admit that the usage of the population register to form the sample of HBS makes the data processing procedures more difficult. However, in towns the population register was the only available register which allowed to create the HBS sample. It could mean that the principal survey should consider non-response, the amount of which could seriously impair the representativeness of the survey. Alternatives for the sampling frame were, therefore, sought out. One of the alternatives turned out to be the complete list of households of the local governments - the civil parish. Of 32 parishes included in the first phase of HBS, 11 parishes already had a full list of households due to a previous agricultural survey. Therefore, it was necessary to prepare the identical lists only for the remaining 21 parishes.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of principal survey forms were developed in order to perform the survey: the Household Diary and the Household Questionnaire. Each of them has a task of its own and information contained in one is not repeated in the other. The Household Diary is completed by the household itself and it contains data on all money expenditure, goods and services received free of charge or from own production representing all expenditures in relation to the household (in cash and kind). Each household receives two diaries in succession: the first - for the first 15 days of the month, and the second for the period until the end of the month (from 16 to 30 or 31, depending on the month)

The Household Questionnaire is filled in by the interviewer. It consists of two interviews: an introductory (preliminary) interview and a final interview. Whilst the first part contains more general questions in relation to the members of the household, conditions of the living area, employment of the household members, the second part, which is filled in during the final interview, contains questions that might be raised only if a certain degree of trust has been established between the household and the interviewer. These are questions on income of the household members, existence of consumer durables, etc.

Actually the interviewer must visit the household in-between the above-mentioned visits in order to ascertain the manner in which the household fills in the diary, whether it needs any assistance and/or additional explanations. Quite often, the diaries are not filled in on a sufficiently regular basis, and an additional inquiry on purchases made in between the visits proves to be necessary. Such assistance is often necessary for older people, as well as to those with poor eye-sight or other handicaps .

In all cases whereby the household sampling list contains a household not found at the given address (false address, change of address, nobody lives at the given address, long-term absence of the addressee, etc.) or a household refuses to participate in the survey, a Report on reasons of non-response is completed.

Data appraisal

Quality of data, interpretation of content of application forms in quarter IV, 1995 was influenced by the fact that interviewers, despite their education, were not sufficiently qualified yet.

Abstract

For the Belarus Household Sample Survey 2015, researchers collect information on demographic characteristics of household members, housing conditions, personal subsidiary plots, property, household expenditure and income.

The information obtained from the survey is used to analyze the influence of new social processes on living standards and to develop policies aimed at social protection of various population groups. Data is also used to compile household accounts in the system of National Accounts, to calculate consumer price index for goods and services, and to estimate the poverty level in the country.

Geographic coverage

National coverage

Analysis unit

A household is understood as the unit of the survey. For survey purposes the category "households" includes: - families consisting of a husband and a wife with or without children or single parent families; - relatives living together and having a common budget (brother and sister, grandmother and grandson and etc.); - persons living together and having a common budget but who are not relatives, for example two friends; - persons living alone; - families consisting of two and more married couples with or without children.

Universe

The survey covers all household members excluding persons fully supported by the state, for example people staying in homes for the elderly and the disabled, children in public care institutions, prisoners, etc. The survey also excludes foreigners living and working in Belarus on contract basis and families of military men living in military residential settlements or other restricted areas.

Kind of data

Sample survey data [ssd]

Sampling procedure

In accordance with international standards, survey data collection and processing system were altered as well as sample designing method. Instead of branch principle that had been employed earlier, probability (random) sampling method was introduced where sampling units are determined based on the probability proportionate to population size. This method ensures sample representativeness at national and regional levels, sample results independence and intentional error avoidance. Household participation in the survey is on a voluntary basis. Sampled households are surveyed for a year and then are subject to replacement (rotation).

To conduct a sample survey, households' residential addresses are sampled. An overall number of the households living in the Republic of Belarus (according to the results of the latest population Census of the Republic of Belarus) forms universe general population during sampling with an exception of collective households and students residing in dormitories. Sampled population forming 0,2% of universe general population is annually arranged by the Belstat.

Mode of data collection

Face-to-face [f2f]

Research instrument

The main components of the survey are:

1) The main interview which is intended to establish the first contact with the household, to make the list of all household members, to collect the basic information about the household in general and its individual members and to fix the date for subsequent interviews. Before an interview a household receives the initial letter signed by the Minister of Statistics and Analysis stating the date and time of the interviewer's visit. The main interview is conducted in December of the previous year;

2) Four quarterly interviews, conducted in April, July, October of the current year and January of the next year. Quarterly interview covers three previous months and summarizes the information about incomes and major expenditures of the households. At the beginning of every quarter a household is given a diary for recording expenditures during the quarter. The diary is used during quarterly interviews;

3) Four two-week diaries which are handed to a household every quarter. The diary is intended for daily recording of expenditures on foodstuffs and non-food products within 14 days as well as for recording of the consumed foodstuffs which were produced at the individual subsidiary land plot or received as a present.

Cleaning operations

The following coding systems were developed and introduced for Belarus household sample survey: 1) coding of households covered by the survey; 2) coding of household expenditures; 3) coding of additional incomes and employment of household members by sectors and types of activity.

In 2023/24, 26.4 percent of children in the United Kingdom were defined as living in absolute poverty, compared with 16.9 percent of working-age adults, 13.2 percent of pensioners, and 20 percent of families where someone is disabled.

In recent years, the Personal Welfare Services sector has experienced favourable operating conditions. The COVID-19 pandemic heightened the focus on health and social services, benefitting the industry through increased government funding and overall demand. Revenue for the Personal Welfare Services industry is expected to grow at an annualised 5.8% over the five years through 2023-24, to total $2.38 billion. New Zealand's economy took a major hit from the COVID-19 pandemic, leading to a significant rise in unemployment and aggravating existing societal problems. Even though the country saw considerable economic growth and lower unemployment rates before the pandemic, multiple negative factors continue to influence demand for personal welfare services. These factors include child poverty, single-parent households and individuals living alone and consequences from substance abuse like family breakdown and domestic violence. This situation has led to a growing need for counselling and child and family welfare services in recent years. The scarcity of affordable housing has also escalated homelessness, resulting in increased utilisation of food banks, soup kitchens and homeless welfare support. In 2023-24, industry revenue is anticipated to rise by 0.6% due to the increasing cost of living and persistent socio-economic inequalities. Despite many businesses being not-for-profit, profit margins are also expected to rise as government spending grows in line with the Wellbeing Budget. Revenue is projected to rise at an annualised 0.2% over the five years through 2028-29 to $2.40 billion. Revenue is set to climb slower than in recent years due to stabilising conditions following the COVID-19 pandemic. Many government investments and initiatives hope to alleviate housing stress and lower rates of homelessness. However, an aging population and the pervasive problem of child poverty will persistently lead to heightened demand for personal welfare services in the approaching years.

Economic crisis. Globalisation. National and European employment and social policies. Discrimination. Development aid. Public transport services.

Topics: 1. General life satisfaction; assessment of the present situation and expectations for the next twelve months regarding life in general, the place of residence, the healthcare system and the pension system in the own country, unemployment benefits, cost of living, relations between people of different national and religious backgrounds in the own country, social inequality and poverty, energy costs, housing costs, public administration, economic situation of the own country, the national labour market situation, the personal job situation, and the financial situation of the own household; comparison of these issues with five years ago.

1. Economic crisis: own unemployment or in the social environment due to the economic crisis; feared personal unemployment or in the social environment (partner, colleague, child); expected impact of the crisis on the labour market situation.

2. Globalisation: knowledge of the European Globalisation adjustment Fund to assist victims of globalisation.

3. National and European employment and social policies: knowledge of the European Social Fund (ESF), the European Regional Development Fund (ERDF), the Erasmus Programme, and the ´Lisbon Strategy´; assessment of the proportion of the EU budget used for financing the European Social Fund; frequency of occupational and job change over the life course of the respondent; duration of the current or the last employment; most important skills to find a job; assessment of the safety of the own job in the next few months, and in two years; participation in training courses within the last twelve months; funding of the training; own education to date is sufficient, or further training is needed to keep the job; reasons that prevent from participating in training courses; likelihood to find a new job within six months (scale); kind of job to which the respondent would apply after a layoff; estimation of the amount of compensation by the national unemployment insurance and the welfare system during the first six months after a presumed job loss on the basis of the current income (percentage); easiest way to find a job; assessment of the statements: life-time jobs with the same employer are a thing of the past, more jobs through more flexible work contracts, making job change easier is a helpful asset to find new work, too many people in the country go into retirement too early, improved chances on the labour market through regular training; assessment of the effectiveness of selected measures to support employment promotion (increasing child care facilities, increasing care facilities for persons in need, discouraging early retirement, increasing the difference of income between working and non-working people, promoting mobility, supporting self-employment, conversion of undeclared work into regular jobs, regular training for employees); assessment of the EU´s influence on the employment and social policies as positive or negative: setting minimum standards for working conditions throughout the EU, creation of new jobs and combating unemployment, reducing regional disparities in unemployment, exchanging best practices in employment policies between EU member states, improving access to education and training, promotion of dialogue between employers and trade unions, fight against social exclusion and poverty, promotion of gender equality, combating discrimination, coordination of reforms of national social protection systems; interest in information on the EU´s employment and social policies; image of the actions regarding employment and social affairs taken by the EU.

4. Discrimination: perceived general extent of discrimination at present and five years ago with regard to: ethnic origin, gender, sexual orientation, age, religion, disability; own experience of discrimination as well as recently observed discrimination against other persons according to the above characteristics; adversely affecting characteristics of an applicant in a concurrent application situation: name, address, way of speaking, ethnic origin, gender, sexual orientation, age, disability, religious belief, smoking, physical appearance; acceptance of a person in a high political position with the following characteristics: woman, homosexual, different ethnic origin, aged under 30, different religious belief, disabled, aged over 75 years (scale); attitude towards specific measures to ensure equal opportunity in the field of employment; approval to monitor the workforce composition with respect to the representation of ethnic minorities and the recruitment procedures; sufficient efforts of the own country to fight discrimination; knowledge of the own rights in the case of discrimination; adequate reflection of social diversity in the media regarding the above characteristics; negative impact of the economic...

Abstract

The Sierra Leone Core Welfare Indicators Questionnaire (CWIQ) survey provides information for management of the Sierra Leone economy and society. It embodies the results of a household survey designed to produce indicators for social welfare in a cheaper and more regular way to provide instruments for continuous monitoring of the poverty alleviation programme. The CWIQ survey produces information for measuring key changes in social indicators for different population groups in particular Indicators of access, use and satisfaction with social services. The overall objective of the Sierra Leone CWIQ survey, 2007 was to provide timely information for monitoring the implementation of the Sierra Leone Poverty Reduction Strategy and to begin a process of capacity building for the design, implementation, processing and analysis of household surveys within Statistics Sierra Leone (SSL) to strengthen the Poverty Reduction Strategy Monitoring and Evaluation System. This report presents the major findings of the CWIQ survey carried out from 5 April-10 May 2007 by SSL. A sample size of 7,800 households, covering rural and urban areas, in all nineteen Local Councils of the four administrative regions of the country was selected from a total of 520 Enumeration Areas. Detailed information was collected on most aspects of poverty such as demographic characteristics, education, health, employment, household assets, household amenities, poverty predictors, children under five, maternal child health and agriculture. The major findings of the survey are summarized in the order of the relevant chapters of the report.

Geographic coverage

The CWIQ Survey covered all four Sierra Leone administrative regions and nineteen Local Councils. Five hundred and twenty (520) Enumeration Areas (E.A.s) covering rural and urban areas in each of the Local Councils were sampled. Fifteen households were sampled in each EA and resulted in an overall sample of 7,800 households.

Analysis unit

The survey design was based on a stratified two-stage sample design using existing SSL sampling frame (2004 Population and Housing Census). E.A.'s served as primary sampling units while households served as secondary sampling units. The survey design enabled reporting of results at Local Council, Regional and National levels.

Universe

The survey covered sampled households and all household members country-wide.

Kind of data

Sample survey data [ssd]

Sampling procedure

A total of 7,797 households were enumerated from a sample of 7,800 households, in 520 Enumeration Areas, giving the survey coverage rate of 98.4 percent (Table 1.2 of Appendix 1).For each enumeration area a reserve list of three household was selected for replacement due to refusals, respondents not at home, households not located, moved away among others. Only three Local Councils Kenema District, Kenema Town and Kambia District had 100% completed of the original households in the sample. The rest of the Local Council areas had some household replaced due to refusals or not found. The Southern Region had the highest level of replacement households of 3.3% and the Eastern Region had the lowest level of replacement of 0.1%. Nationally, 4,905 households were covered in the rural areas while 2,892 households were covered in the urban areas.

Sampling deviation

For each enumeration area a reserve list of three household was selected for replacement due to refusals, respondents not at home, households not located, moved away among others.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey instruments included the modified generic scannable CWIQ questionnaire; the interviewer's manual and supervisor's manual. CWIQ2007(24464): Sierra Leone 2007 Main Survey 19-03-2007 IMPORTANT Create a reference number by combining the household and questionnaire numbers. Write this number NOW on the top of all pages. Page 1 of 14 Q.1 INTERVIEWER'S NAME A.1 CLUSTER A.2 HOUSEHOLD A.3 SEQ. A.4 INTERVIEWER A.5 DATE A.6 TIME A.7 RESPONDENT Q.2 NAME OF HEAD OF HOUSEHOLD Q.3 PROVINCE/REGION Q.4 DISTRICT Statistics Sierra Leone A.J. Momoh Street Freetown, Sierra Leone Comments A - INTERVIEW INFORMATION C W I Q Core Welfare Indicators Questionnaire I Q.5 LOCAL COUNCIL Q.6 CHIEFDOM/WARD Quest. N o. Hour Min. AM PM Member N o. A.8 RESULT Complete with selected household Complete with replacement - refusal Complete with replacement - not found Incomplete 1 2 3 4 A.9 INTERVIEW END Hour Min. AM PM PRINTING AND SHADING INSTRUCTIONS For optimum accuracy, please print carefully and avoid contact with the edges of the box. The following will serve as an example: Tel: 022-223287 Q.7 SECTION Q.8 VILLAGE/LOCALITY Day Mon th Y ear Reference Number 8862244644 CWIQ2007(24464): Sierra Leone 2007 Main Survey 19-03-2007 IF RESPONSE IS NO OR DON'T KNOW GO TO NEXT PERSON MEMBER NUMBER 1 2 3 4 5 6 7 8 9 10 Head B Page 2 of 14 - LIST OF HOUSEHOLD MEMBERS WRITE DOWN THE NAMES OF ALL PERSONS WHO NORMALLY LIVE AND EAT TOGETHER IN THIS HOUSEHOLD, STARTING WITH THE HEAD. B.1 Is [NAME] male or female? Male Female B.2 How long has [NAME] been away in the last 12 months? Never Less than 6 months 6 months or more B.3 What is [NAME]'s relationship to the head of household? Head Spouse Child Parent Other relative Not related B.4 How old was [NAME] at last birthday? (RECORD AGE IN COMPLETED YEARS.) B.9 Is [NAME]'s mother living in the household? Yes No What is [NAME]'s marital status? Never married Married(monogamous) Married(polygamous) Divorced Separated Widowed Is [NAME]'s father alive? Yes No Don't know B.7 Is [NAME]'s father living in the household? Yes No B.8 Is [NAME]'s mother alive? Yes No Don't know M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N IF RESPONSE IS NO OR DON'T KNOW GO TO B.8 M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N M F 1 2 3 1 2 3 4 5 6 1 2 3 4 5 6 Y N X Y N Y N X Y N B.5 IF PERSON IS UNDER AGE 10 GO TO B.6 B.6 IF PERSON IS AGED 18 OR ABOVE GO TO NEXT PERSON Reference Number 7226244647 CWIQ2007(24464): Sierra Leone 2007 Main Survey 19-03-2007 GO TO NEXT PERSON GO TO NEXT PERSON MEMBER NUMBER 1 2 3 4 5 6 7 8 9 10 Page 3 of 14 C - EDUCATION Can [NAME] read and write in any language? Yes No C.2 Has [NAME] ever attended school? Yes No Why has [NAME] not started school? (YOU MUST MARK AT LEAST ONE ANSWER) a Too young b Too far away c Too expensive d Is working (home or job) e Useless/uninteresting f Illness g Other C.3 What is the highest grade [NAME] completed? C.4 Did [NAME] attend school last year? Yes No C.5 Is [NAME] currently in school? Yes No C.6 What is the current grade [NAME] is attending? C.7 Who runs the school [NAME] is attending? Government Religious organization Private Community Other C.8 Did [NAME] have any problems with school? (YOU MUST MARK AT LEAST ONE ANSWER) a No problem (satisfied) b Lack of books/supplies c Poor teaching d Not enough teachers e Teachers often absent f Lack of space g Facilities in bad condition h High fees i Other problem C.9 Why is [NAME] not currently in school? (YOU MUST MARK AT LEAST ONE ANSWER) a Completed school b Too far away c Too expensive d Is working (home or job) e Illness f Drug related problem g Pregnancy h Got married i Useless/uninteresting j Failed exam k Awaiting admission l Dismissed m Other C3 - Highest grade completed 00 None 01 Pre-school 11 P1 21 JSS1 31 University 12 P2 22 JSS2 41 Vocational 13 P3 23 JSS3 42 Teacher training 14 P4 24 SSS1 43 Technical 15 P5 25 SSS2 16 P6 26 SSS3 C6 - Current grade attending 01 Pre-school 11 P1 21 JSS1 31 University 12 P2 22 JSS2 41 Vocational 13 P3 23 JSS3 42 Teacher training 14 P4 24 SSS1 43 Technical 15 P5 25 SSS2 16 P6 26 SSS3 Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N Y N Y N Y N 1 2 3 4 5 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y IF C5 RESPONSE IS NO GO TO C.9 IF C2 IS NO AND [NAME]IS BELOW 19 YEARS GO TO C.10; ELSE GO TO NEXT PERSON C.10 ASK C10 IF PERSON IS BELOW 19 YEARS C.1 ASK C.1 IF PERSON IS AGE 15 OR ABOVE OTHERWISE GO TO C.2 Reference Number 2017244640 CWIQ2007(24464): Sierra Leone 2007 Main Survey 19-03-2007 MEMBER NUMBER 1 2 3 4 5 6 7 8 9 10 Page 4 of 14 D - HEALTH D.1 Is [NAME] physically or mentally handicapped or disabled? Include person only if handicap prevents him or her from maintaining a significant activity or schooling. What sort of sickness/injury did [NAME] suffer? (YOU MUST MARK AT LEAST ONE ANSWER) D.5 What kind of health provider did [NAME] see? D.6 How did [NAME] pay for the consultation? a No need b Too expensive c Too far d Lack of confidence e Other D.8 Why did [NAME]

China’s Long-Term Care Insurance (LTCI) system is designed to address the caregiving needs of elderly individuals with disabilities and dementia, focusing on long-term care to ensure adequate survival and quality of life for disabled individuals. This study employs the PMC index model to evaluate LTCI policies in 16 pilot cities, including Changchun and Qingdao, using keyword extraction and social network analysis on the latest policy documents from these cities. The study revealed the following findings: (1) Among the 16 cities, only Qingdao’s policy achieved a “perfect” rating, with two policies rated as “excellent,” 11 as “acceptable,” and two as “poor.” (2) While most cities allow the involvement of commercial insurance in LTCI administration, there is a lack of clear policy direction for the assessment and service provision by commercial insurers. (3) Dementia care receives significantly less attention compared to physical disabilities. (4) Most cities have underdeveloped financing mechanisms, and family caregiving services are undervalued. Moreover, an analysis of representative policies based on the PMC surface indicates substantial differences between the pilot cities, with Qingdao’s “perfect” policy serving as a model for future LTCI development. The study offers several recommendations: (1) Improve caregiver support policies to enhance family caregiving services. (2) Expand funding sources to increase the equity of LTCI financing. (3) Allocate insurance policy resources more effectively to gradually eliminate policy barriers. (4) Increase the focus on dementia care and clarify the criteria for assessing disability. (5) Strengthen the preventive function of LTCI and progressively expand its coverage. This research provides critical insights into the ongoing development of China’s LTCI system and proposes viable strategies for promoting equity and sustainable growth.

China’s Long-Term Care Insurance (LTCI) system is designed to address the caregiving needs of elderly individuals with disabilities and dementia, focusing on long-term care to ensure adequate survival and quality of life for disabled individuals. This study employs the PMC index model to evaluate LTCI policies in 16 pilot cities, including Changchun and Qingdao, using keyword extraction and social network analysis on the latest policy documents from these cities. The study revealed the following findings: (1) Among the 16 cities, only Qingdao’s policy achieved a “perfect” rating, with two policies rated as “excellent,” 11 as “acceptable,” and two as “poor.” (2) While most cities allow the involvement of commercial insurance in LTCI administration, there is a lack of clear policy direction for the assessment and service provision by commercial insurers. (3) Dementia care receives significantly less attention compared to physical disabilities. (4) Most cities have underdeveloped financing mechanisms, and family caregiving services are undervalued. Moreover, an analysis of representative policies based on the PMC surface indicates substantial differences between the pilot cities, with Qingdao’s “perfect” policy serving as a model for future LTCI development. The study offers several recommendations: (1) Improve caregiver support policies to enhance family caregiving services. (2) Expand funding sources to increase the equity of LTCI financing. (3) Allocate insurance policy resources more effectively to gradually eliminate policy barriers. (4) Increase the focus on dementia care and clarify the criteria for assessing disability. (5) Strengthen the preventive function of LTCI and progressively expand its coverage. This research provides critical insights into the ongoing development of China’s LTCI system and proposes viable strategies for promoting equity and sustainable growth.

Abstract

Starting from 1995, the National Statistical Committee of the Republic of Belarus (formerly the Ministry of Statistics and Analysis) has been conducting a sample survey of 6,000 households on a yearly basis, according to the methodology complying with international standards. The survey is carried out in all regions of the country and Minsk City, covering 49 cities, towns and urban-type settlements, and 53 rural councils. Data from the latest population census is used to construct the sample.

For the survey, researchers collect information on demographic characteristics of household members, housing conditions, personal subsidiary plots, property, household expenditure and income.

The information obtained from the survey is used to analyze the influence of new social processes on living standards and to develop policies aimed at social protection of various population groups. Data is also used to compile household accounts in the system of National Accounts, to calculate consumer price index for goods and services, and to estimate the poverty level in the country.

Geographic coverage

National coverage

Analysis unit

A household is understood as the unit of the survey. For survey purposes the category "households" includes: 1) families consisting of a husband and a wife with or without children or single parent families; 2) relatives living together and having a common budget (brother and sister, grandmother and grandson and etc.); 3) persons living together and having a common budget but who are not relatives, for example two friends; 4) persons living alone; 5) families consisting of two and more married couples with or without children.

Universe

The survey covers all household members excluding persons fully supported by the state, for example people staying in homes for the elderly and the disabled, children in public care institutions, prisoners, etc. The survey also excludes foreigners living and working in Belarus on contract basis and families of military men living in military residential settlements or other restricted areas.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampled households are surveyed for a year and then are subject to replacement (rotation). To conduct the survey, households' residential addresses are sampled. Sampled population forming 0.2% of universe general population is annually arranged by the statistical office.

A household is understood as the unit of the survey. This is a person or a group of persons (mainly relatives) living together and having a common budget. Close relationship is not an obligatory condition.

Sampling was based on the territorial principle of forming a selection. In accordance with this principle, sampling involved three stages. Different territorial units of selection were used at every stage: the larger units were used at the initial stage while at the third stage the surveyed unit was equal to the selection unit. To ensure equal distribution of sample over the territory of the country, the selection was made separately for urban and rural population.

At the first stage, administrative and territorial units such as cities (including urban settlements) and rural councils were taken as the units of selection. Nineteen cities with the population above 72,000 people and 58 village councils were selected.

At the second stage, constituencies were taken as the selection units in urban areas and residential settlements were taken as the selection units in rural areas. The list of constituencies is drafted at the regional level based on the district (city) executive committees' data on the number of eligible voters. The list of voters excluded persons living in students' and workers' hostels. At the second stage maps of all selected cities and village councils were widely used when building a sample.

At the third stage, a household was taken as the unit of selection. Within the area of the selected constituencies in urban areas and residential settlements in rural areas, the lists of residential apartments and individual houses were drafted based on the data of apartment register in towns and village councils' registers in rural areas. The lists were drafted in line with the numbering of buildings within the area of the selected constituencies in urban areas and in residential settlements in rural areas.

Detailed information about the sampling is available in "Belarus Household Sample Survey Methodology" in Technical Documents (p.9-17).

Mode of data collection

Face-to-face [f2f]

Research instrument

The main components of the survey are:

1) The main interview which is intended to establish the first contact with the household, to make the list of all household members, to collect the basic information about the household in general and its individual members and to fix the date for subsequent interviews. Before an interview a household receives the initial letter signed by the Minister of Statistics and Analysis stating the date and time of the interviewer's visit. The main interview is conducted in December of the previous year;

2) Four quarterly interviews, conducted in April, July, October of the current year and January of the next year. Quarterly interview covers three previous months and summarizes the information about incomes and major expenditures of the households. At the beginning of every quarter a household is given a diary for recording expenditures during the quarter. The diary is used during quarterly interviews;

3) Four two-week diaries which are handed to a household every quarter. The diary is intended for daily recording of expenditures on foodstuffs and non-food products within 14 days as well as for recording of the consumed foodstuffs which were produced at the individual subsidiary land plot or received as a present.

Cleaning operations

The following coding systems were developed and introduced for Belarus household sample survey: 1) coding of households covered by the survey; 2) coding of household expenditures; 3) coding of additional incomes and employment of household members by sectors and types of activity.

Detailed information about coding procedures is available in "Belarus Household Sample Survey Methodology" (p.22-25) in Technical Documents.

Abstract

The first Household Budget Survey in Latvia took place in 1926-1927, the second in 1936-1937. In the post-war period Family Budget Survey was started in 1952 within the system of the former Central Statistical Board of the USSR. This survey continued also during first independence years of Latvia, after the Soviet Union collapsed. The new Household Budget Survey was introduced in September 1995.

Since 1995, Latvia Household Budget Survey has been conducted annually. The annual household sample is evenly distributed over time (the same number of households participates in the survey within each of the 52 weeks of the year).

The Household Budget Survey provides information on qualitative and quantitative indicators of standards of livings in Latvia. The survey gathers data on the structure of households, their revenue and consumer expenditures, employment of the household members, living conditions, possession of consumer durables, access to health care, culture, education, as well as subjective assessments of the households' level of welfare. Data is collected through face-to-face interviews and household expenditure diaries.

Latvia Household Budget Survey was redesigned in 2001 to improve sampling methodology and survey instruments. Latvia Population Census carried out in spring 2000 has been used to construct the sampling frame. The design of the household diary was changed to facilitate better response.

Geographic coverage

National

Analysis unit

• Households,
• Individuals.

Household is defined as a person or group of persons tied by relationship or other personal relations, having common subsistence expenditures and inhabiting the same living unit (house, flat, etc.), maintenance of which is covered by such persons jointly.

Universe

The target population of HBS consists of all non-institutional households in Latvia. Persons living in institutional households (elderly people boarding house, disabled children boarding house, student hostels, hotels, barracks, hospitals, sanatoriums, penal institutions, etc.) and homeless people are excluded from the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two-stage stratified random sampling method was used to select households. The annual household sample is evenly distributed over time (the same number of households participates in the survey within each of the 52 weeks of the year). Primary sampling units are selected within each stratum using systematic probability proportional to size sampling with a random starting point. In the second stage households from each sampled PSU are selected by simple random sampling. The annual household sample is evenly distributed over time (the same number of households participates in the survey within each of the 52 weeks of the year) and space. Primary sampling units are selected within each stratum using systematic probability proportional to size sampling with a random starting point. In the second stage households from each sampled PSU are selected by simple random sampling.

Households are stratified by the degree of urbanization (location): the capital city of Riga, six other largest cities, towns, and rural areas.

The sampling frame has been constructed using information from Population Census carried out in spring 2000. The sampling frame is updated before drawing the sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of survey instruments are used for Latvia HBS: Household Questionnaire and Household Diary.

1) Household Questionnaire. The Household Questionnaire is filled by interviewers. It consists of questionnaires for an introductory interview and a final interview.

• Household Introductory Interview covers social and demographic composition of a household, housing conditions, the possibility to use (cultivate) land, employment of household members (age 15 years and above);
• The Final Interview covers questions on income of the household members in cash, transfers (different recall periods), income in kind received from the employer, and different benefits from the state and local government social assistance, possession of durable goods in the household, household expenditure on the purchase of durable goods and other goods that are bought more seldom, on services during the last 12 months, self evaluation of living conditions (subjective poverty indicators).

Individual diary is designed for household members who are temporally absent (students, etc.).

2) Household Diary. Respondents themselves fill in the diary during four weeks. All regular household consumption expenditure as well as consumption of food products received free of charge are registered. The households are asked to record food quantities and the prices actually paid. In 2001, the design of the diary has been changed to facilitate better response. During the first two weeks (intensive diary keeping period) a separate page is used for each day. It consists of four tables according to the type of consumption expenditure: - Expenditure on food products, tobacco products and alcoholic beverages; - Meals out of doors; - Expenditure on non-food products and services; - Food products that are obtained for the household consumption from the personal farm plot, or received free of charge.

The diary recording period is 2 weeks (starting from 2009).