The 2018 Tonga National Disabiltiy Survey was conducted jointly by the Tonga Department of Statistics (TDS) and the Ministry of Internal Affairs, Social Protection and Disability. It is the first population-based comprehensive disability survey in the country. Funding was provided through number of bodies including UNICEF, DFAT and Tonga Government. The Pacific Community provided technical supports through out different stages of the survey.

The main purpose of the survey is to desctibe demographic, social and economic characteristics of persons with disabilities and detemine the prevalence by type of disability in Tonga, and thus help the government and decision makers in formulating more suitable national plans and policies relevant to persons with disabilities.

The other objectives of the Disability survey were collect data that would determine but not limited to the following: a. Disability prevalence rate at the national, urban and rural based on the Washington Group recommendations; b. degree of activity limitations and participation restrictions and societal activities for persons with disability: c. ascertain the specific vulnerabilities that children and adults with disability face in Tonga d. establish the accessibility of health and social services for persons with disability in Tonga e. generate data that guides the development of policies and strategies that ensure equity and opportunities for children and adults with disabilities.

An additional module was included to collect information on people's perception/experiences of service delivery of Goverment to the public.

Version 01: Clean, labelled and de-identified version of the Master file.

The scope of the study involves Disability. Various sections of the Questionnaire are listed below.

HOUSEHOLDS:
-Basic household characteristics of the private dwellings, including sanitation, water, electricity, households materials and household wealth;

INDIVIDUALS:
-Basic demographic characteristics of individuals in a particular household dwelling, including age, sex, ethnicity, religion, marital status, educational attainment, and economic activity

(Children aged 2-4 years:
-Level of difficulty functioning by domain, tools and supports, age of onset of difficulty, cause of difficulty, health, transport;)

(Children aged 5-17 years:
-Level of difficulty functioning by domain, tools and supports received, age of onset of difficulty, cause of difficulty, health, transport, education, employment, income, participation and accessibility)

(Adult aged 18 years and older:
-Level of difficulty functioning by domain, tools and supports received, age of onset of difficulty, cause of difficulty, health, transport, education, employment, income, participation and accessibility).

• Collection start: 2018
• Collection end: 2018

Abstract

The 2007 Kenya National Survey for Persons with Disabilities (KNSPWD) was a national sample survey - the first of its kind to be conducted in Kenya - designed to provide up-to-date information for planning, monitoring and evaluating the various activities, programmes and projects intended to improve the wellbeing of persons with disabilities. The survey covered more than 14,000 households in a total of 600 clusters (436 rural and 164 urban).

The survey interviewed persons with disabilities of all ages in sampled areas to get estimates of their numbers; distribution; and demographic, socio-economic and cultural characteristics. The survey also sought to know the nature, types and causes of disabilities; coping mechanisms; nature of services available to them; and community perceptions and attitudes towards PWDs.

The survey was undertaken by the National Coordinating Agency for Population and Development (NCAPD) in collaboration with the Kenya National Bureau of Statistics (KNBS); Ministry of Gender, Sports, Culture and Social Services (MGSCSS); Ministry of Health (MOH); and the Ministry of Education Science and Technology (MOEST). Other participants were United Disabled Persons of Kenya (UDPK); Kenya Programmes of Disabled Persons (KPDP); Association for the Physically Disabled of Kenya (ADPK); and Africa Mental Health Foundation (AMHF). Technical and financial support came from the Department for International Development (DFID), the World Bank and the United States Agency for International Development (USAID) under the Statistical Capacity Building Project (STATCAP) project. The United Nations Population Fund (UNFPA) provided support for the design of survey instruments.

Geographic coverage

National

Analysis unit

Households and individuals

Universe

The survey covered all de jure household members (usual residents) and all women aged between 12-49 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

While the survey intended to estimate the number of PWDs, it was realized that a significant proportion of these individuals reside in institutions, which are not part of the household sampling frame. However, a comprehensive list of institutions that existed did not form sufficient sampling frame for estimation of numbers of institution-based PWDs for the entire country. A mechanism had to be devised for incorporating these persons into the survey to supplement the data derived from the household-based survey.

The targeted survey population for the institutional based survey was defined as all people living in homes and occupying long-stay beds in public or private hospitals; or living in long-stay residential units for people with an intellectual, psychiatric/physical disability, vision or hearing impairments, or with multiple disabilities. The following types of institutions were covered: · Hospitals (acute care, chronic care hospitals, nursing homes) · Psychiatric institutions · Treatment centres for persons with physical disabilities · Residential special schools · Private and non-private group homes · Private and non-private children's homes · Orphanages · Private and non-private residences for senior citizens (Mji wa wazee) · Other residential institutions with people with disabilities

The sampling frame compiled for the institutional survey comprised all institutions indicated above. The frame included the name of the institution, type, number of individuals, location and type of disability. The frame was compiled from various sources, including MOH, MOEST, MSGSS and various organizations dealing with disabilities, among others.

In order to achieve representation, the institutions were first stratified according to location (provinces) and then by nature of disability. The institutions were further classified into two broad categories depending on nature and size (number of PWDs). All key institutions were sampled with certainty (that is, all selected in the sample). The remaining institutions within a province were arranged and serially listed by disability type and a systematic random sampling procedure used to select the sample.

A sample size of 102 institutions catering for different population sizes of PWDs was covered. Once the institutions were sampled, the next exercise involved selection of individuals for the survey. Five bands were created depending on the size of the sampled institution. The bands were: less than or equal to 30; 31-50; 51-100; 101-200; and above 200. A listing of all residents was compiled during the day of the interview and a systematic random sample drawn. Five respondents were selected from each of the sampled institutions with up to 30 PWDs, eight from those having 31-50, and ten from those having 51-100. For institutions having 100-200 PWDs, 15 were chosen, and from those having 201 and above, 20.

The KNSPWD household sample was constructed to allow for estimation of key indicators at the provincial level as well as of the urban and rural components separately. The survey utilized a multi-stage cluster sample design and was based on a master sample frame developed and maintained by KNBS. The master sampling frame is the National Sample Survey and Evaluation Programme (NASSEP) IV. It has 1,800 clusters (data collection area points) that were developed with probability proportional to size (PPS) from the enumeration areas (EAs) delineated during the 1999 Kenya Population and Housing Census. Of the 1,800 clusters, 1,260 are rural based and the other 540 are located in urban areas.

In the frame, the first stage involved selecting the census EAs using PPS and developing them into clusters. The process involved quick counting of the selected EA and dividing into segments depending on the measure of size (MOS). The MOS was defined as an average of 100 households, with lower and upper bounds of 50 and 149 households, respectively. The EAs that were segmented had only one segment selected randomly to form a cluster. The EAs that had fewer than 50 households were merged prior to the selection process. During the creation of NASSEP IV, other than each of the 69 districts being a stratum, the six major urban areas (Nairobi, Mombasa, Kisumu, Nakuru, Eldoret and Thika) were further stratified into five income classes: upper, lower upper, middle, lower middle and lower. The aim was to ensure that different social classes within these areas were well represented in any time sample that was drawn.

The second sampling stage involved selecting clusters for the KNSPWD from all the clusters in the NASSEP IV master sampling frame. A total of 600 clusters (436 rural and 164 urban) was sampled from all the districts in the country with boundaries as defined in the 1999 Kenya population and housing census. The third stage of selection involved systematically sampling 25 households from each cluster, hence producing 15,000 households in total.

Mt. Elgon district was excluded from the survey because of persistent insecurity in the area. The effect of exclusion of the district in the sample is minimal since it contributes 0.5% of the population according to 1999 census.

Mode of data collection

Face-to-face [f2f]

Research instrument

Models of questionnaires and survey instruments developed by the World Health Organization (WHO), Washington Group Consortium and organizations in other countries were tailored to the Kenyan context. The purpose was not only to make the instruments responsive to the country situation, but also to ensure that the results would be comparable to those from other countries.

With input from a wide range of people who have worked in the area of disability, and who have conducted national surveys, a workshop was held to develop and adopt the following instruments for Kenya:

· Household questionnaire: Designed to collect background information at the household level for all the usual members as well as any visitors who slept in the household the night before the interview. This questionnaire was also used to screen PWDs by type to identify those who were eligible for the individual disability questionnaire. This instrument was administered to the most knowledgeable person in the household on the day of the visit. · Individual questionnaire: Administered to any PWDs who had been identified using the household questionnaire. The questionnaire included the following key sections: activity limitation; environmental factors; situation analysis; support services; education; employment and income; immediate surroundings; assistive devices; attitudes towards disability; and health and general well-being · Reproductive health questionnaire: Administered to all eligible females aged 12 to 49 who were living with any form of disability. It collected information on reproductive health. · Institutional questionnaire: Administered to the heads of the various categories of institutions serving PWDs. Randomly selected PWDs in these institutions were interviewed using the individual questionnaire. · Focus group discussion guide: Used to collect qualitative information from a group of 6-10 members within each of the sampled clusters. The groups comprised PWDs, community leaders, service providers, opinion leaders and teachers. The focus group discussions collected information on knowledge, attitudes and beliefs of community members about PWDs and the different services available for PWDs in the different communities. Likewise, focus group discussions were used to collect qualitative information about problems faced by PWDs, their coping mechanisms and their access to essential basic services, as well as an overview of community perceptions of PWDs and views on how best to

Survey participants (≥18 years).

Association between anxiety and depression and functional difficulties in vision*.

Abstract

Objectives: To provide information about the general characteristics of persons with disability or difficulty through a specialized questionnaire designed to meet the needs of the Palestinian Territory, the recommendation of the World Health Organization (WHO) and the Washington Group for Disability Statistics.

Reference Period: 1st quarter of 2011

Periodicity of Data Collection: Every 10 years

Geographic coverage

Areas excluded: Israeli settlements

Analysis unit

Individuals

Universe

Population groups: All age groups

Total population covered: 97.6%

Economic activities: All economic activities

Sectors covered: All sectors

Labor force status: Employed persons, unemployed persons, persons outside labour force

Status in Employment: Employees, employers, own-account workers, contributing family workers, members of producers' cooperatives

Establishments: NR

Other limitations: No

Classifications: Sex, age, level of education, other personal characteristics (e.g. marital status), status in employment, occupation, economic activity

Cross-classification: No

Kind of data

Census/enumeration data [cen]

Frequency of data collection

Periodicity of Data collection: Every 10 years

The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated).The variables for part 1 of the dataset are:Census usually resident population countCensus night population countAge (5-year groups)Age (life cycle groups)Median ageBirthplace (NZ born/overseas born)Birthplace (broad geographic areas)Ethnicity (total responses) for level 1 and ‘Other Ethnicity’ grouped by ‘New Zealander’ and ‘Other Ethnicity nec’Māori descent indicatorLanguages spoken (total responses)Official language indicatorGenderCisgender and transgender status – census usually resident population count aged 15 years and overSex at birthRainbow/LGBTIQ+ indicator for the census usually resident population count aged 15 years and overSexual identity for the census usually resident population count aged 15 years and overLegally registered relationship status for the census usually resident population count aged 15 years and overPartnership status in current relationship for the census usually resident population count aged 15 years and overNumber of children born for the sex at birth female census usually resident population count aged 15 years and overAverage number of children born for the sex at birth female census usually resident population count aged 15 years and overReligious affiliation (total responses)Cigarette smoking behaviour for the census usually resident population count aged 15 years and overDisability indicator for the census usually resident population count aged 5 years and overDifficulty communicating for the census usually resident population count aged 5 years and overDifficulty hearing for the census usually resident population count aged 5 years and overDifficulty remembering or concentrating for the census usually resident population count aged 5 years and overDifficulty seeing for the census usually resident population count aged 5 years and overDifficulty walking for the census usually resident population count aged 5 years and overDifficulty washing for the census usually resident population count aged 5 years and over.The variables for part 2 of the dataset are:Individual home ownership for the census usually resident population count aged 15 years and overUsual residence 1 year ago indicatorUsual residence 5 years ago indicatorYears at usual residenceAverage years at usual residenceYears since arrival in New Zealand for the overseas-born census usually resident population countAverage years since arrival in New Zealand for the overseas-born census usually resident population countStudy participationMain means of travel to education, by usual residence address for the census usually resident population who are studyingMain means of travel to education, by education address for the census usually resident population who are studyingHighest qualification for the census usually resident population count aged 15 years and overPost-school qualification in New Zealand indicator for the census usually resident population count aged 15 years and overHighest secondary school qualification for the census usually resident population count aged 15 years and overPost-school qualification level of attainment for the census usually resident population count aged 15 years and overSources of personal income (total responses) for the census usually resident population count aged 15 years and overTotal personal income for the census usually resident population count aged 15 years and overMedian ($) total personal income for the census usually resident population count aged 15 years and overWork and labour force status for the census usually resident population count aged 15 years and overJob search methods (total responses) for the unemployed census usually resident population count aged 15 years and overStatus in employment for the employed census usually resident population count aged 15 years and overUnpaid activities (total responses) for the census usually resident population count aged 15 years and overHours worked in employment per week for the employed census usually resident population count aged 15 years and overAverage hours worked in employment per week for the employed census usually resident population count aged 15 years and overIndustry, by usual residence address for the employed census usually resident population count aged 15 years and overIndustry, by workplace address for the employed census usually resident population count aged 15 years and overOccupation, by usual residence address for the employed census usually resident population count aged 15 years and overOccupation, by workplace address for the employed census usually resident population count aged 15 years and overMain means of travel to work, by usual residence address for the employed census usually resident population count aged 15 years and overMain means of travel to work, by workplace address for the employed census usually resident population count aged 15 years and overSector of ownership for the employed census usually resident population count aged 15 years and overIndividual unit data source.Download lookup file for part 1 from Stats NZ ArcGIS Online or Stats NZ geographic data service.Download lookup file for part 2 from Stats NZ ArcGIS Online or Stats NZ geographic data service.FootnotesTe Whata Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.Geographical boundaries Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018. Subnational census usually resident population The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. Population counts Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts. Caution using time series Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data). Study participation time seriesIn the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.About the 2023 Census dataset For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings. Data quality The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.Concept descriptions and quality ratingsData quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.Disability indicatorThis data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.Using data for good Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.Confidentiality The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3)

Abstract

Due to the lack of disability data in the Syria crisis context, Humanity & Inclusion (HI) and iMMAP conducted a disability assessment in 2017 and 2018 with the following objectives:

1. Provide statistically reliable data on the prevalence of disabilities as well as data on access to services disaggregated by disability.

2. Increase the understanding of the situation of Syrian refugees with disabilities and their households compared to their peers without disabilities in relation to access to services, including education.

3. Recommend inclusive actions to be prioritized by humanitarian actors.

Quantitative data was collected in Lebanon in December 2017 and in Jordan in between October 2017 and January 2018. In Lebanon, 2,495 refugees from 506 households were randomly sampled in urban settings in Bar Elias as well as Informal Tented Settlements (ITS) in Bar Elias and Arsal. In Jordan, 6,381 refugees were randomly sampled in 1,159 households in Azraq and Zaatari camps and Irbid. In light of the United Nations Convention on the Rights of Persons with Disabilities (UN CRPD), the study defined disability as interactions between personal and environmental factors. Disability was measured by the level of difficulties a person faces when performing basic activities (referred as “domains”) regardless of impairments, using the modified Washington Group’s Extended Set (WG-ES) (more precisely, Short Set Enhanced plus fatigue) and Child Functioning Module (CFM).

Geographic coverage

Jordan: Azraq, Zaatari and Irbid camps Lebanon: Urban setting in Bar Elias as well as Informal Tented Settlements (ITS) in Bar Elias and Arsal

Analysis unit

Households

Universe

All households in selected camps

Kind of data

Sample survey data [ssd]

Sampling procedure

Lebanon: Random sampling was adopted to reflect and compare the experiences of both registered and non-registered Syrian refugees with the United Nations High Commissioner for Refugees (UNHCR), as well as of both persons with and without disabilities. For Bar Elias, a random sample was generated covering all parts of the town. For ITS, random shelters were selected by satellite

Jordan: Random sampling was adopted to reflect and compare the experiences of both registered and non-registered Syrian refugees with United Nations High Commissioner for Refugees (UNHCR), as well as of both persons with and without disabilities. - All the residents in Azraq and Zaatari camps are registered. A random sample of shelters was constituted using available data relating to the structure of the camps. - Irbid is a city located North of Jordan’s capital Amman, and hosts approximately 20% of Syrian refugees in the country (UNHCR, 2018b). As there is no list of unregistered Syrian refugees in the city, the study employed twostage sampling. The first stage identified 3,600 random locations in the city, taking Irbid’s population density into account. Among these random locations, enumerators randomly visited households (including those of Jordanian families) until the Syrian refugee household/family sample size was large enough to enable generalization of statistical results to the entire study population.

Mode of data collection

Face-to-face [f2f]

The study conducted in partnership with IMMAP and funded by the Australian Government includes a literature review, quantitative data collection as well as qualitative data collection. Quantitative data was collected from 8,876 persons from 1,665 households from 5 locations in Jordan and Lebanon. In the light of the UN Convention on the Rights of Persons with Disabilities (UNCRPD), the study defined disability as interactions between personal and environmental factors. Disability was measured the level of difficulties a person faces when performing basic activities (referred as “domains”) regardless of impairments, using the modified Washington Group’s Extended Set (WG-ES) (more precisely, Short Set Enhanced plus fatigue) and Child Functioning Module (CFM).

Persons with disabilities are disadvantaged in accessing sexual and reproductive health services, including condoms. In this study, we investigated whether condom access and use and their associated factors differed between persons with and without disabilities. We used data from adults in households receiving the Government of Zambia social cash transfers (SCT) in four districts of Luapula province. Condom access and use was the outcome. Disability, defined by the Washington Group Short Set Questions on Disability, was the main predictor. We performed logistic regression analyses to determine the associations between condom access and use and disability. In multivariable analyses, we controlled for covariates including age, sex, marital status, poverty status, HIV testing, and receiving the SCT. The sample comprised 1,143 people aged 16–49, with a median age of 21 years (interquartile range 18–28); 57.4% (n = 656) were female, 86.5% (n = 989) accessed and used condoms, and 17.9% (n = 205) were disabled, rating themselves with a 3 or a 4 on a scale of 1 = “not limited” to 4 = “cannot at all” in performing any of the six daily functions (seeing, hearing, walking, cognition, self-care, or communicating). Nearly sixty percent(58.5% (n = 120)) of persons with disabilities were female, 79.5% (n = 163) reported being very poor, 87.8% (n = 180) reported receiving SCT, and 86.3% (n = 177) reported accessing and using condoms. Condom access and use did not differ between persons with and without disabilities (adjusted odds ratio: 1.09; 95% confidence interval [CI]: 0.60–1.98]). We found no differences between persons with and without disabilities in condom access and use. We established that individual-level factors such as age, sex, marital status, and knowledge of being HIV positive might play a more important role in condom access and use than disability. Condom promotion interventions should account for these factors.