Link to this report's codebookUnfulfilled Promise of Racial EqualityUS states unequally distribute resources, services, and opportunities by raceThe US is failing to deliver on its promise of racial equality. While the US founding documents assert that ‘all men are created equal,’ this value is not demonstrated in outcomes across areas as diverse and varied as education, justice, health, gender, and pollution. On average, white communities receive resources and services at a rate approximately three times higher, than the least-served racial community (data on Asian, Black, Indigenous, Hawaiian and Pacific Islander, Hispanic, Multiracial and ‘Other’ racial communities, were used as available). Evidence shows that unequal treatment impacts each of these communities, however, it is most often Black and Indigenous communities that are left the furthest behind. When states are scored on how well they deliver the United Nations Sustainable Development Goals (SDGs) to the racial group least served, no state is even halfway to achieving the SDGs by 2030 (see Figure 1). To learn more about the Sustainable Development Goals, see the section “SDGs & Accountability.”One example of this inequality is in life expectancy. In Figure 2, the scatter plot on the left demonstrates a pattern in which Black and Indigenous communities, represented by orange and green dots closest to the bottom of the graph, are consistently the communities with least access to years of life. In the graph on the right, each box represents a racial population in a specific state, the boxes are organized from left to right, lowest to highest, according to the life expectancy for that group and state. The graph shows how large the gap is in life expectancy across racial communities and states, with green and orange boxes, representing Indigenous and Black communities respectively, clustered to the left of the graph.Patterns like this one, demonstrating both deep and wide racial inequalities, occur across the 51 indicators this analysis includes, covering 12 of 17 SDGs. In a similar example (Figure 3), a pattern emerges where white students are least likely to attend a school where 75 percent or more of its students receive free or reduced cost lunch when compared to all other racial groups. In the most unequal state, North Dakota, Indigenous students attend high poverty schools at a rate 42 times higher than white students. As Figure 3 shows, although the percentage of students from the least served racial group attending high poverty schools ranges from 2 percent in Vermont to 73 percent in Mississippi, the group least served, represented by the dots closest to the top of the graph, are most often Hispanic and Indigenous communities.Lack of Racial DataMore, and better, racially and ethnically disaggregated data are needed to assess delivery of racial equalityA significant barrier to evaluating progress is the unavailability of racial data across all areas of measurement. For too many important topic areas, such as food insecurity, maternal mortality and lead in drinking water, there is no racial data available at the state level. Even in the areas where there is some racial data, it is often not available for all groups (see Figure 4). Particularly missing, were measures of environmental justice; in Goals focusing on Water, Clean Energy, and Life on Land (Goals 6, 7, and 15), racial data was not found for any indicators, despite the fact that there is research indicating that clean water, for example, is unequally distributed across racial groups. The reasons for these gaps vary. For some indicators, data is not tracked through a nationally organized database, for other indicators, the data is old and out of date, and in many cases, surveys are not large enough to disaggregate by race. As was made clear with the disparate impacts of COVID-19 (for example, see CDC 2020), understanding to whom resources are being distributed has real life implications and is an important part of holding democratic institutions accountable to promises of equality.People are often left behind due to a combination of intersecting identities and factors; they remain hidden in averages. Evaluating the Leave No One Behind Agenda through the lens of gender, ability, class and other identities are undoubtedly important and urgent. Disaggregating data along two axes such as race and location—is revealing. But an even more refined analysis using multilevel disaggregation, such as looking at women and race in urban settings, would likely reveal even starker inequalities. Those are not included here and are important areas for future work. Other areas for further exploration include the use of longitudinal data to understand how these inequalities are changing over time.Though the full extent of this unequal treatment is unknown, this analysis sheds some light on the clouded story told by state averages. Whole group averages leave out important information, particularly about inequality. Racially disaggregated data is essential for holding governments accountable to the promise of racial equity. Without it, it is too easy to hide who is being excluded and left behind.SDGs and AccountabilitySDGs and AccountabilityThe SDGs can be an accountability tool to address racial inequality. This would not be the first time UN frameworks have been used to call attention to racial inequality in the US. In 1951, the Civil Rights Congress (CRC) led by William L. Patterson and Paul Robeson put a petition to the UN, named: “We Charge Genocide,” which charged that the United States government was in violation of the Charter of the United Nations and the Convention on the Prevention and Punishment of the Crime of Genocide (Figure 5). While this attempt did not succeed in charging the US government with genocide, it is a central example of how international instruments can be used to apply localized pressure to advance civil rights.All 193 member countries of the UN, including the United States, signed on to the Sustainable Development Goals in 2015, to be achieved by 2030. The Goals cover 17 wide-ranging topics, with 169 specific targets for action (Figure 6). The first agenda of the SDGs, the Leave No One Behind Agenda (LNOB), requires that those left furthest behind by governments must have the SDGs delivered to them first. The results of this project demonstrate that in a US-context, those left furthest behind would undoubtedly include Asian, Black, Indigenous, Hawaiian and Pacific Islander, Hispanic, Multiracial and ‘Other’ racial communities. The SDGs can offer a template for US states attempting to deliver on their promise of racial equality. The broad topic areas covered by the SDGs, in combination with the Leave No One Behind agenda, can be a tool to hold states accountable for addressing racial inequalities when and through developing solutions for clean water, quality education, ending hunger, delivering justice and more. This highlights an important implication of the Leave No One Behind Agenda, it is not meant to pit communities against each other, but rather to remind us how much everyone has to gain by building and advocating for sustainable communities that serve us all.Explore ResultsExplore the data from the In the Red: the US failure to deliver on a promise of racial equality in our interactive dashboards.These maps display how US states are delivering sustainability across different racial and ethnic groups. As part of the Leave No One Behind Agenda, which maintains that those who have been least served by development progress must be those first addressed through the SDGs, progress toward the goals in each state is displayed based on the racial group with the least access to resources, programs, and services in that state. In other words, the “Overall scores’’ map shows the score for the racial group least served in each state. Click on a state to toggle through the state’s performance by different SDGs, and click on an indicator to view how a state performs on a given indicator. At the indicator level, horizontal bar charts show the racial disparity in the selected indicator and state, when data is available.AboutIn the Red: the US Failure to Deliver on a Promise of Racial EqualityIn the Red: the US Failure to Deliver on a Promise of Racial Equality project highlights measurable gaps in how states deliver sustainability to different racial groups. The full report can be read here. It extends an earlier report, Never More Urgent, looking at policies and practices that have led to the inequalities described in this project. It was prepared by a group of independent experts at SDSN and Howard University.UN Sustainable Development Solutions Network (SDSN)The UN Sustainable Development Solutions Network (SDSN) mobilizes scientific and technical expertise from academia, civil society, and the private sector to support practical problem solving for sustainable development at local, national, and global scales. The SDSN has been operating since 2012 under the auspices of the UN Secretary-General Antonio Guterres. The SDSN is building national and regional networks of knowledge institutions, solution-focused thematic networks, and the SDG Academy, an online university for sustainable development.SDSN USASDSN USA is a network of 150+ research institutions across the United States and unincorporated territories. The network builds pathways toward achievement of the UN Sustainable Development Goals (SDGs) in the United States by mobilizing research, outreach, collective action, and global cooperation. SDSN USA is one of more than 40 national and regional SDSN networks globally. It is hosted by the UN Sustainable Development Solutions Network (SDSN) in New York City, and is chaired by Professors Jeffrey Sachs (Columbia University), Helen Bond (Howard University), Dan Esty (Yale University), and Gordon McCord (UC San Diego).

Link to this report's codebookExecutive SummaryThe United Nations’s Sustainable Development Goals (SDGs) are a useful framework for collaboration because they are shared and supported by all 193 member countries of the UN. They provide a useful framework for sustainability because they require interdisciplinary and intersectoral collaboration. Therefore, understanding US state policy through the lens of the SDGs both connects state efforts to broader, international movements for an environmentally, socially, and economically just world, and supports an interdisciplinary approach to understanding state progress.To facilitate states and the communities that live in them in leveraging this framework, SDSN tracks SDG progress at the state level. This year, SDSN has expanded on its 2018 report to include information on if, and how quickly, states are approaching SDG achievement. With nine years to go before the 2030 Goals deadline, on average US states are less than halfway to achieving the SDGs. The report finds:States are not improving quickly enough to meet the SDGs by 2030 and at least 20 percent of indicators in every state are going in the wrong direction. US states are not doing what needs to be done to protect the environment, end inequality, or provide for healthy lives, among other things. In contrast to so many other places around the globe where progress is visible, US states are getting worse across a myriad of areas.Inequalities are deeply entrenched across US states. Twenty percent of the indicators used in this report measure how states were delivering aspects of sustainable development to excluded communities. Those indicators were among the poorest performers in the report, several of which were getting worse.Preliminary results show that COVID-19 has increased challenges to SDG delivery and its impacts underline the need for universal health coverage and universal access to key social and physical infrastructure. COVID-19 stay at home orders highlighted the disparity in access to adequate and affordable housing. Racial inequality in homelessness is so prevalent that every state scored a zero (out of a possible 100 points). Many US residents still do not have access to adequate healthcare, broadband, food, and employment. These systems required intervention before the pandemic: the situation is now even more urgent.Environmental justice efforts show a path forward through Black and Indigenous and other excluded community-led efforts. Lack of state action on climate change is putting all at risk. Excluded communities are already bearing the burden of inaction.Excluded communities have also demonstrated the ability to address both inequality and environmental impacts, and provide crucial leadership on a sustainable path forward.Data gaps, time lags, and lack of disaggregated data highlight the need for improvement in statistical capacity and new approaches to monitor SDG achievement. State-level data is missing on essential topics such as lead in water and outcomes for people with disabilities. Other areas, particularly those focused on justice and state violence, are woefully out of date and/or the official records are incomplete. Proper and safe stewardship of personal data and careful maintenance of data sovereignty must also be held in balance as data collection and demands grow. The SDGs provide a framework to advocate for a better world. Timely, disaggregated, boundaried, and complete data are essential to complete that aim.The SDGs were agreed upon at the national level, but local action is essential to their achievement. Universities, like those organized by SDSN’s network teams, have essential roles to play in fostering collaboration and local action, and providing technical expertise to community-led efforts. Tools for measuring SDG achievement have also been powerful ways to unite diverse stakeholders in goal setting and to drive accountability. Voluntary Local Reviews (VLRs), Voluntary University Reviews (VURs), and data dashboards like the open-source version provided by SDSN, can also be powerful tools for SDG achievement. The changes necessary to move the states to SDG achievement over the next nine years will need to be bold and courageous; that action is only possible through collaboration. It is possible to achieve these Goals, but business as usual won’t be nearly enough.

The report presents the SDG baseline for the Asia and the Pacific both at the regional and sub-regional level for selected targets of each SDG. It uses the latest country data and supplementary statistical information aligned to the proposed global indicators. Based on this evidence the report summarizes key findings and analysis. It outlines ways to gradually improve the availability of data and refine our ability to assess progress. Disaggregated data has a critical role to play in our efforts to achieve the 2030 Agenda’s ambition to “leave no one behind”. The report shows that Asia and the Pacific, a region with an impressive development track record, needs to step up its overall development reform effort. For over one third of the SDGs, existing data point to slow or stagnating progress since 2000. For another third (reducing inequalities, sustainable cities and communities, responsible consumption and production, and life on land) the data suggest the region is moving in the wrong direction, a trend we must reverse. For only five SDGs (no poverty; quality education; decent work and economic growth; industry, innovation, and infrastructure; and life below water), do the current trends set the region on the path to achieve the desired development outcomes by 2030. But even in these areas, there is a need to redouble our efforts.

The new scorecard tracks progress toward the World Bank Group's vision to create a world free of poverty on a livable planet. The Scorecard includes three types of indicators: - Vision indicators - reflect the new vision for the WBG, showing the WBG’s ambition and providing high-level measures to gauge the direction and pace of progress in tackling global challenges. Vision indicators contain aggregated and disaggregated development context data for all countries in the world, where data is available. The Scorecard reports the latest available global updates for each of these indicators. - Client context indicators - reflect the circumstances in client countries, including multidimensional aspects of poverty, and are aligned with the Sustainable Development Goals (SDGs). They serve to frame the challenges clients face, and the context in which the WBG operates. Client Context indicators contain aggregated and disaggregated development context data for World Bank client countries, based on country eligibility for financing and where data is available. The Scorecard also reports the latest available update for each of these indicators. - WBG Results indicators monitor WBG progress on some of the most critical global challenges. Results data include: - Active Portfolio Results: Contain achieved and expected results of WBG operations based on its active portfolio as of end of June 2024. Includes aggregated and disaggregated data. - Results achieved since July 1st, 2023: Contain cumulative results achieved between July 1st, 2023 - June 30, 2024 from active and closed projects. Results achieved before July 1st, 2023 are excluded from this calculation. Includes aggregated data for World Bank, IBRD and IDA only. IFC and MIGA do not currently report this data. - Operations Details: Operation-level detail is provided for World Bank projects. However, in alignment with IFC and MIGA Access to Information Policies, project-level data is available in an aggregated format on the WBG Scorecard, provided the minimum threshold to secure individual clients' data is satisfied.

This collection includes only a subset of indicators from the source dataset.

The Kazakhstan Multiple Indicator Cluster Survey (MICS) was conducted in 2015 by the Statistics Committee of the Ministry of National Economy of the Republic of Kazakhstan (herein MNE RK). This is the third MICS Survey in Kazakhstan. The findings from these surveys were used in development and implementation of state programmes in the areas of mother and child health, as well as country programmes of the United Nation Children’s Fund (UNICEF) in Kazakhstan, highlighting the need to improve the statistical data management system with regard to children. Such surveys are crucially important in terms of assessing the state of children and women in Kazakhstan as they provide unique information for development of the national child-centred policy and for international positioning of Kazakhstan. The survey provides statistically sound and internationally comparable data essential for development of evidence base and programmes, and for monitoring country progress towards national goals and global (international) commitments. Among these global commitments are those emanating from international agreements the World Fit for Children Declaration and its Plan of Action, the goals of the United Nations General Assembly Special Session on HIV/AIDS, the Education for All Declaration and the Millennium Development Goals (MDGs). In addition, the 2015 Kazakhstan MICS results will contribute to establishing a baseline for monitoring the state of women and children in the context of the Sustainable Development Goals (SDGs). OBJECTIVES To provide up-to-date information for assessing the situation of children and women in the Republic of Kazakhstan; To collect information that will help to improve national policies in the area of childhood and motherhood protection; To generate data for the critical assessment of the progress made in various areas, and to put additional efforts in areas that require more attention; To collect disaggregated data for the identification of disparities, to allow for evidence based policy-making aimed at social inclusion of the most vulnerable; To validate data from other sources and the results of focused interventions; To contribute to the generation of baseline data for the post-2015 agenda; To contribute to the improvement of data and monitoring systems in the Republic of Kazakhstan and to strengthen technical expertise in the design and implementation of such systems as well as in a better analysis of available data.

Abstract

The Government of Iraq, with support from UNICEF finalized and launched a Multiple Indicator Cluster Survey (MICS 6) in 2018. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Data and information from MICS6 provides credible and reliable evidence for the Government of Iraq to monitor the National Development Plan and establish baselines and monitor progress towards Sustainable Development Goals (SGDs). It helps the government and its stakeholders to understand disparities and the wider development challenges in the country.

The 2018 Iraq MICS has as its primary objectives:

• To provide high quality data for assessing the situation of children, adolescents, women and households in Iraq;

• To furnish data needed for monitoring progress towards national goals, as a basis for future action;

• To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable;

• To validate data from other sources and the results of focused interventions;

• To generate data on national and global SDG indicators;

• To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention.

Geographic coverage

The sample for the Iraq MICS 2018 was designed to provide estimates at the national, regional and governorates level, for urban and rural areas. Specifically the sample for the Iraq MICS 2018 survey includes 2 regions - Kurdistan and South/Central Iraq and 18 governorates - Duhok, Nainawa, Sulaimaniya, Kirkuk, Erbil, Diala, Anbar, Baghdad, Babil, Karbalah, Wasit, Salahaddin, Najaf, Qadissiyah, Muthana, Thiqar, Musan, and Basra.

Analysis unit

• Individuals

• Households

Universe

The MICS survey considers the households and their members in all urban and rural areas of Iraq as the Universe. Thus, the Universe for Iraq consists of all persons in the country residing in various geographic locations considering all special ethnic or economic groups in the rural and urban areas of Iraq. For the purposes of this survey, Internally Displaced Persons living in United Nations/government notified camps, military installations, and non-residential units such as business establishments were not considered in the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The last census in Iraq was carried out in 1998 and the sampling frame was developed during that time. The most recent update of this sampling frame was done in 2009 which was used by Central Statistical Office (CSO) for the selection of the Clusters in Iraq region. On the other hand, the Kurdistan Region Statistical Office (KRSO) has updated the 2009 sampling frame for the 3 main cities of Kurdish region and their periphery and used it to draw the Clusters. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs). A listing of households was conducted in each sample EA, and a sample of households was selected at the second stage.

SAMPLE SIZE AND SAMPLE ALLOCATION

The sample size has been calculated using the prevalence rates of key indicators from the 2011 MICS. For the purpose of identifying the optimal sample size for 2018 MICS, all the factors such as time, cost, domain of estimation, sampling and non-sampling errors were taken into account, as well as the desired level of precision of the key prevalence indicator. The sample size was calculated at the governorate level. It was decided that 2018 MICS will provide the estimates at the governorate level, so the indicative sample size has been calculated using governorate as the domain for the geographic representation. The formula for calculating the sample size is described in Appendix A of report available in related materials.

A number of meetings were held in the CSO to finalize the sample size, and various refinements were studied using the referred formula. As a result of these discussions the MICS Technical Committee reached a consensus on a sample size of 1,080 households for each governorate of Iraq, where each governorate was divided into 90 sample clusters and 12 households were selected per cluster (90 clusters x 12 households = 1,080 households). Baghdad was sub-divided into two administrative areas, therefore 19 total individual domains were used for a total sample size of 20,520 households (19 domains x 1,080 households).

One-third of the sampled households was selected for water quality testing, which means 360 households per governorate or 6,840 (360 X 19) households for the overall survey. The subsample of 4 households for the water quality testing in each cluster are selected using systematic random sampling.

Each Governorate is further stratified into urban and rural areas, and the sample within each governorate is allocated proportionately to the urban and rural strata based on the population. The urban and rural areas within each governorate are the main sampling strata. Within each stratum, a specified number of clusters is selected systematically using probability proportionate to size (PPS) sampling methodology. After the selection of the clusters in each rural and urban stratum, a new listing of households was conducted in each sample cluster. Then a systematic random sample of 12 households per cluster is drawn from the listing for each rural and urban sample cluster.

SELECTION OF ENUMERATION AREAS (CLUSTERS):

Census enumeration areas were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeration area from the Iraq 2009 sampling frame. The first stage of sampling was thus completed by selecting the required number of sample EAs (specified in Table SD.2) from each of the 19 sampling domains, separately for the urban and rural strata. However, there are a few areas belonging to two governorates that were not accessed due to security reasons. These governorates are Nainawa and Kirkuk. In Nainawa 5 districts were excluded (Ba'aj, Al-Hadar, Telafer, Sinjar and Makhmoor), while only Haweja district in Kirkuk was excluded. The excluded districts represent around 22% of the urban population and 51% of the rural population in Nainawa. The percentage of not accessed area in final sample for Kirkuk represents 5% of the Urban and 42% of the rural population, following the exclusion of Haweja district.

SELECTION OF HOUSEHOLDS:

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to Mhi (the total number of households in each enumeration area) at the Central Statistical Office, where the selection of 12 households in each enumeration area was carried out using random systematic selection procedures. The MICS6 spreadsheet template for systematic random selection of households was adapted for this purpose.

The Iraq 2018 MICS also included water quality testing for a subsample of households within each sample cluster. A subsample of 4 of the 12 selected households was selected in each sample cluster using random systematic sampling for conducting water quality testing, for both water in the household and at the source, including a chlorine test. The MICS6 household selection template includes an option to specify the number of households to be selected for the water quality testing, and the spreadsheet automatically selected the corresponding subsample of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a water quality testing questionnaire administered in 4 households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 5) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

The questionnaires were based on the MICS6 standard questionnaires. From the MICS6 model Arabic version, the questionnaires were customised and translated to two Kurdish dialects and were pre-tested in 3 governorates (Baghdad, Najaf and Basra) in South/Central Iraq region and 3 governorates (Duhok, Erbil & Sulaimaniya) in Kurdistan region of Iraq during Dec 2017/Jan 2018. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

Cleaning operations

Data were received at the Central Statistical Organization (CSO) via Internet File Streaming System (IFSS), integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in details in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data

The Multiple Indicator Cluster Survey (MICS) is a primary source of information on women and children as it provides statistical indicators that are critical for the measurement of human development. It is an international household survey programme developed by United Nations Children’s Fund (UNICEF). The MICS is designed to collect statistically sound and internationally comparable estimates of key indicators that are used to assess the situation of children and women in the areas of health, education, child protection and HIV/AIDS. It can also be used as a data collection tool to generate data for monitoring the progress towards national goals and global commitments which aimed at promoting the welfare of children and women such as MDGs and SDGs. OBJECTIVES The primary objectives of Multiple Indicator Cluster Survey (MICS) Nigeria 2016-17 are: To provide up-to-date information for assessing the situation of children and women in Nigeria; To generate data for the critical assessment of the progress made in various programme areas, and to identify areas that require more attention; To contribute to the generation of baseline data for the SDG; To furnish data needed for monitoring progress toward goals established in the post Millennium Declaration and other internationally agreed goals, as a basis for future action; To provide disaggregated data to identify disparities among various groups to enable evidence based actions aimed at social inclusion of the most vulnerable.

IntroductionThe “percentage of births attended by a skilled birth attendant" (SBA) is an indicator that has been adopted by several global monitoring frameworks, including the Sustainable Development Goal (SDG) agenda for regular monitoring as part of target 3.1 for reducing maternal mortality by 2030. However, accurate and consistent measurement is challenged by contextual differences between and within countries on the definition of SBA, including the education, training, competencies, and functions they are qualified to perform. This scoping review identifies and maps the health personnel considered SBA in low-to-middle-income-countries (LMIC).Methods and analysisA search was conducted inclusive to the years 2000 to 2015 in PubMed/MEDLINE, EMBASE, CINAHL Complete, Cochrane Database of Systematic Reviews, POPLINE and the World Health Organization Global Index Medicus. Original primary source research conducted in LMIC that evaluated the skilled health personnel providing interventions during labour and childbirth were considered for inclusion. All studies reported disaggregated data of SBA cadres and were disaggregated by country.ResultsThe search of electronic databases identified a total of 23,743 articles. Overall, 70 articles were included in the narrative synthesis. A total of 102 unique cadres names were identified from 36 LMIC countries. Of the cadres included, 16% represented doctors, 16% were nurses, and 15% were midwives. We found substantial heterogeneity between and within countries on the reported definition of SBA and the education, training, skills and competencies that they were able to perform.ConclusionThe uncertainty and diversity of reported qualifications and competency of SBA within and between countries requires attention in order to better ascertain strategic priorities for future health system planning, including training and education. These results can inform recommendations around improved coverage measurement and monitoring of SBA moving forward, allowing for more accurate, consistent, and timely data able to guide decisions and action around planning and implementation of maternal and newborn health programmes.

Abstract

The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. The Kiribati Social Development Indicator Survey (SDIS) results are critically important for the purposes of Sustainable Development Goal (SDG) monitoring, as the survey produces information on 32 global SDG indicators adopted by the National Development Indicators framework, either in their entirety or partially.

The 2018-19 Kiribati SDIS has as its primary objectives: • To provide high quality data for assessing the situation of children, adolescents, women and households in KSDIS; • To furnish data needed for monitoring progress toward national goals, as a basis for future action; • To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable; • To validate data from other sources and the results of focused interventions; • To generate data on national and global SDG indicators; • To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention; • To generate behavioural and attitudinal data not available in other data sources.

Geographic coverage

National Coverage: covering rural-urban areas and for the five district/island groups of the country (South Tarawa, Northern Gilbert, Central Gilbert, Southern Gilbert, and Line and Phoenix groups).

Analysis unit

-Household; -Household member; -Mosquito nets; -Women in reproductive age; -Birth history; -Men in reproductive age; -Mothers or primary caretakers of children under 5; -Mothers or primary caretakers of children age 5-17.

Universe

The survey covered all de jure household members (usual residents), all women aged between 15 to 49 years, all men aged between 15 to 49 years, all children under 5 and those aged 5 to 17 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

-SELECTION PROCESS: The sample for the Kiribati Social Development Indicator Survey (SDIS) 2018-19 was designed to provide estimates for a large number of indicators on the situation of children and women at the national, rural-urban, South Tarawa, Northern Gilbert, Central Gilbert, Southern Gilbert and Line and Phoenix group. The urban and rural areas within each district were identified as the main sampling strata and the sample of households was selected in two stages. Within each stratum, a specified number of census Enumeration Areas (EAs) were selected systematically with probability proportional to size. After a household listing was carried out within the selected enumeration areas, a systematic sample of 3280 households was drawn in each sample enumeration area. All of the selected enumeration areas were visited during the fieldwork period.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The sampling frame was based on the full/national household listing (mini-census) conducted in 2018 because the last census (2015) could not be used as a sampling frame as the EA boundaries differed from the 2010 Kiribati Census. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs) defined for the census enumeration.

-SAMPLE SIZE AND SAMPLE ALLOCATION: Since the overall sample size for the Kiribati SDIS partly depends on the geographic domains of analysis that are defined for the survey tables, the distribution of EAs and households in Kiribati from the 2018 Household Listing /Mini Census sampling frame was first examined by region, urban and rural strata.

The overall sample size for the Kiribati SDIS was calculated as 3,280 households. For the calculation of the sample size, the key indicator used was the underweight prevalence among children age 0-4 years. Since the survey results are tabulated at the regional level, it was necessary to determine the minimum sample size for each region.

For the calculation, r (underweight prevalence) was assumed to be 15 percent based on the national estimate from the Demographic and Health SUrvey (DHS) 2009. -The value of deff (design effect) was taken as 1.0 based on the estimate from the DHS 2009, -pb (percentage of children age 0-4 years in the total population) was taken as 12 percent, -AveSize (mean household size) was taken as 6.0 based on the 2018 mini-Census, and the response rate was assumed to be 98 percent, based on experience from the DHS 2009. -It was decided that an RME of at most 20 percent was needed for the district/island group estimates; this would result in an RME of 10 percent for the national estimate. The calculations resulted in a total sample size of 3,280 households, with the sample sizes in the districts varying between 515 and 780. The sample size in South Tarawa (urban) was adjusted upwards from 780 to 1,080 households in order to improve the precision in urban/rural comparisons. The sample sizes in the other districts/island groups were reduced by 75 households each.

The number of households selected per cluster for the Kiribati SDIS was determined as 20 households, based on several considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster.

Census enumeration areas were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeration area from the 2018 Mini- Census frame. The first stage of sampling was thus completed by selecting the required number of sample EAs (specified in Table SD.2) from each of the five district/Island groups.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

-QUESTIONNAIRE DESCRIPTION: Six questionnaires were used in the survey: 1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a water quality testing questionnaire administered in 4 households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) a questionnaire for individual men administered in every second household to all men age 15-49 years; 5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

The questionnaires were based on the Multiple Indicator Cluster Surveys 6 (MICS6) standard questionnaires except for questionnaire for individual women/men had some add-on questions and/or modules from the Demographic and Health Surveys (DHS) programme. From the MICS6 model English version, the questionnaires were customised and translated into Kiribati language and were pre-tested in South Tarawa during September, 2018. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the Kiribati Social Development Indicator Survey (SDIS) 2018-19 questionnaires is provided in the External Resources of this documentation.

-COMPOSITION OF THE QUESTIONNAIRES: The questionnaires included the following modules: -Household questionnaire: List of household members, Education, Household characteristics, Social transfers, Household energy use, Dengue, Water and sanitation, Handwashing, Salt iodisation.

-Water Quality Testing questionnaire: Water quality tests, Water quality testing results.

-Individual Women questionnaire: Background, ICT, Fertility/Birth history, Desire for last birth, Maternal and newborn health, Post-natal health checks, Contraception, Unmet need, Attitudes toward domestic violence, Victimisation, Marriage/union, Adult functioning, Sexual behaviour, HIV/AIDS, STI, Tobacco and alcohol use, Domestic violence, Life satisfaction.

-Individual Men questionnaire: Background, ICT, Fertility, Contraception, Unmet need, Attitudes toward domestic violence, Victimisation, Marriage/union, Adult functioning, Sexual behaviour, HIV/AIDS, STI, Circumcision, Tobacco and alcohol use, Life satisfaction.

-Children Under 5 questionnaire: Background, Birth registration, Early childhood development, Chil discipline, Child functioning, Breastfeeding and dietary intake, Immunisation, Care of illness, Anthropometry.

-Children Age 5-17 Years questionnaire: Background, Child labour, Child discipline, Child functioning, Parental involvment, Foundational learning skills.

Cleaning operations

Data were received at the National Statistical Office's central office via Internet File Streaming System (IFSS) integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in detail in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) During data collection b) Structure checking and completeness c) Secondary editing d) Structural checking of SPSS data files

Detailed documentation of the editing of

The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. The Kiribati Social Development Indicator Survey (SDIS) results are critically important for the purposes of Sustainable Development Goal (SDG) monitoring, as the survey produces information on 32 global SDG indicators adopted by the National Development Indicators framework, either in their entirety or partially.

The 2018-19 Kiribati SDIS has as its primary objectives: • To provide high quality data for assessing the situation of children, adolescents, women and households in KSDIS; • To furnish data needed for monitoring progress toward national goals, as a basis for future action; • To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable; • To validate data from other sources and the results of focused interventions; • To generate data on national and global SDG indicators; • To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention; • To generate behavioural and attitudinal data not available in other data sources.

Version 01: This is the final clean, labelled, and anonymized version of the master file.

-HOUSEHOLD: Household characteristics; Household belongings; Communication; Agriculture; Social Transfers; Household Energy use; Dengue; Water and sanitation; Handwashing; Salt iodisation.

-HOUSEHOLD MEMBER: Individual charateristics; Education; Dengue.

-MOSQUITO NETS: Dengue.

-WOMEN IN REPRODUCTIVE AGE: Education; Literacy; Individual characteristics; Communication; Fertility and birth history; Maternal and newborn health; Post-natal health checks; Contraception; Unmet need; Attitudes toward domestic violence; Victimisation; Marriage/union; Adult functioning; Sexual behaviour; HIV/AIDS; Sexually transmitted infections; Tobacco and alcohol use; Life satisfaction; Domestic violence.

-BIRTH HISTORY: Birth history.

-MEN IN REPRODUCTIVE AGE: Education; Literacy; Individual characteristics; Communication; Fertility, Contraception, Attitudes toward domestic violence, Victimisation; Marriage/union; Adult functioning; Sexual behaviour; HIV/AIDS; Sexually transmitted infections; Circumcision, Tobacco and alcohol use; Life satisfaction.

-MOTHERS OR PRIMARY CARETAKERS OF CHILDREN UNDER 5: Education; Individual characteristics; Birth registration; Early childhood development; Child discipline; Child functioning; Breastfeeding and dietary intake; Immunisation; Care of illness.

-MOTHERS OR PRIMARY CARETAKERS OF CHILDREN AGE 5-17: Education; Child's background; Child labour; Child discipline; Child functioning; Parental involvement; Foundational learning skills.

• Collection start: 2018
• Collection end: 2019

The Suriname 2018 MICS results are critically important for the purposes of SDG monitoring, as the survey produces information on 31 global SDG indicators. Since the Government is in the process of drafting the development indicators for Suriname aligned with the SDG's, the MICS data is a valuable source of information for planning and monitoring purposes. The Suriname 2018 MICS has as its primary objectives: To provide high quality data for assessing the situation of children, adolescents, women and households in Suriname; To furnish data needed for monitoring progress toward national goals, as a basis for future action; To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable; To validate data from other sources and the results of focused interventions; To generate data on national and global SDG indicators; To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention; To generate behavioural and attitudinal data not available in other data sources.

Abstract

Executive Summary

Introduction
This report is based on the Nigeria Multiple Indicator Cluster Survey (MICS 5) 2016-17, conducted between September 2016 and January 2017 by National Bureau of Statistics (NBS), with technical and financial support from UNICEF, WHO, UNFPA, Bill and Melinda Gates Foundation, Save One Million Lives and NACA. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Among these global commitments are those emanating from the World Fit for Children Declaration and Plan of Action, the goals of the United Nations General Assembly Special Session on HIV/AIDS, the Education for All Declaration and the Millennium/Sustainable Development Goals (MDGs/SDGs). The Nigeria Multiple Indicator Cluster Survey 2016-17 has been designed to measure achievements of MDGs and provide baseline for SDGs. More specifically, Nigeria MICS 2016-17 will assist UNICEF in monitoring and evaluating its country programmes including those on child survival, development, protection and rights of children, women and men. The 2016-17 Nigeria National immunisation Coverage Survey (NICS) was embedded within the Nigeria Multiple Indicator Cluster Survey (MICS) 2016-17 and designed to provide routine immunisation vaccination coverage in children aged 12 to 23 months at the national level, 36 States and the Federal Capital Territory (Abuja). MICS is a household survey designed to provide information on indicators related to the situation of children, women and men.

Survey Objectives The objectives of Nigeria Multiple Indicator Cluster Survey (MICS) 2016-17 and NICS 2016/17 are to: (1) Provide up-to-date information for assessing the situation of children and women in Nigeria (2) Generate data for the critical assessment of the progress made in various programme areas, and to identify areas that require more attention (3) Contribute to the generation of baseline data for the SDG (4) Provide data needed for monitoring progress toward goals established in the post Millennium Declaration and other internationally agreed goals, as a basis for future action (5) Provide disaggregated data to identify disparities among various groups to enable evidence based actions aimed at social inclusion of the most vulnerable. (6) Provide reliable data for: a. Immunisation coverage of children age 12 to 23 months for the basic antigens: BCG, DPT 1-3, OPV 0-3, Measles b. Immunisation coverage of children age 12 to 23 months for complementary antigens: Yellow fever, Hepatitis B and Vitamin A (7) Estimate the trend of Immunisation coverage since 2006 (8) Provide a geographical database on Immunisation coverage (for mapping) (9) Determine the most frequent obstacles to utilization of Immunisation services (10) Provide information on reasons for utilization or non-utilization of Immunisation services

Sample and Survey Methodology
MICS sample design The Nigeria MICS 2016-17 was designed to provide estimates for a number of indicators on the situation of children women and men at national, urban/rural, states and for the six geopolitical zones. States in each zone were identified as the main sampling strata and were also the principal units in which Nigeria MICS 2016-17 indicators were reported while enumeration areas (EAs) within each state were used as the primary sampling units (PSUs). The sample size computation of the Nigeria MICS 2016-17 was based on the estimated prevalence of stunting in children aged below five years of age – it was proposed that 60 randomly selected EAs per state would be sufficient for estimating MICS indicators at state level. In Kano and Lagos states the respective state bureaus of statistics requested for larger sample sizes to allow for reporting of indicators by senatorial districts. A senatorial district is an administrative region represented by a senator in Nigeria; there are three (3) senatorial districts in each of the 36 states and one senatorial district in the FCT (Abuja). The sample required to allow for reporting by senatorial district level in both Kano and Lagos was 120 EAs. The combined sample of 60 enumeration areas per state and 120 enumeration areas in Lagos and Kano is referred to as as the “MICS sample”.

NICS (National Immunisation Coverage Survey) Sample design The Nigeria NICS 2016-17 sample design based on precise estimation of pentavalent 3 vaccination coverage within ±10% in each state (reporting domain). When the proposed MICS samples were evaluated, it was realised that the “MICS sample” would not have been sufficient to estimate state vaccination coverage for children aged 12 to 23 months in 20 out of the 37 states based on the desired precision parameters. These states were Abia, Akwa Ibom, Anambra, Bayelsa, Benue, Cross River, Delta, Edo, Ekiti, Enugu, Imo, Kogi, Kwara, Ogun, Ondo, Osun, Oyo, Plateau, Rivers and FCT (Abuja). Consequently, to enable precise estimation of vaccination indicators in each state, supplemental sampling was conducted to meet the requirements for vaccine coverage estimation, in the 20 whose MICS 2016-17 was deficient. Immunisation indicators in these 20 states were estimated from analysis of the combined sample (supplemental sample + original MICS sample), while estimation of other MICS indicators these 20 states were done exclusively using the MICS sample.

Questionnaires
Nigeria MICS 2016-17 questionnaires Questionnaires for the Nigeria, MICS 2016-17 were based on adaptations of standard MICS questionnaires and were used to collect data on household and individual level parameters including information on immunisation status of children aged 12 to 23 months. A household questionnaire was administered to the household head or their representative to ascertain household level characteristics such as the size of the household, household composition, occupation of household head, household asset ownership and access to water and sanitation. Individual level question o3 months and that only components of the questionnaire collecting age, gender and vaccination status were administered. The questionnaires used in Nigeria, NICS 2016/17 were based on the MICS5 questionnaire adapted for Nigeria. NICS 2016/17 was based on information collected from a household and an immunisation questionnaire. The household questionnaire was used to collect socio-demographic information and other general characteristics on all members of the household (usual residents), household and the dwelling units. Responses needed for computation of immunisation coverage indicators were contained in the household questionnaire and in the under-five questionnaire from the MICS set of questionnaires

Fieldwork and Data Processing
Training for the fieldwork was conducted in thirty-one (31) days in August 2016. The data were collected by 78 teams; each team comprised of four interviewers, one driver, the measurer and a supervisor. Fieldwork began in September, 2016 and concluded in January 2017. Using Computer Assisted Personal Interviewing (CAPI), the data were electronically captured from the field and transmitted to a central server, using CSPro CAPI application, Version 5.0. Data were analysed using the Statistical Package for Social Scientists (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF MICS team were customized and used for this purpose.

Data management and analysis Data were simultaneously collected in the core (MICS) and in the supplemental EAs by teams of enumerators who had attended similar training. All data were collected electronically using CAPI program designed using CSPro and running on tablet computers. Collected data were synchronized with a centralized, password protected server managed by NBS. Data processing included identification and resolution of inconsistencies and recoding of variables. Following data cleaning, two datasets were generated:

1) MICS dataset containing data collected only from the core (MICS) EAs MICS dataset was used for the analysis of all non-immunisation related indicators in the Nigeria MICS 2016-17 report and table CH.1: of the child health chapter while the MICS/NICS dataset was used for generation of tables CH.2A to CH.2F of the same report. In addition, further analysis of the MICS/NICS dataset is presented as a separate report Nigeria, National Immunisation Coverage Survey 2016/17, Final Report.

MICS dataset can be found on the Nigeria Data Archive (NADA) page hosted on the NBS website http://www.nigerianstat.gov.ng/nada/index.php/catalog/57

2) MICS/NICS dataset which was an aggregation of data collected from the core (MICS) EAs and the supplemental EAs. Link to MICS/NICS dataset can be found here http://www.nigerianstat.gov.ng/nada/index.php/catalog/57 A variable labelled source is used to identify whether data for an observation was collected from the core (MICS) EAs or from the supplemental EAs. In the Nigeria MICS 2016-17 report, table CH.1 has been generated from the core MICS sample and includes 5577 children aged between 12 and 23 months. Tables CH2.A to tables CH2.F are computed from the combined sample of core MICS enumeration areas and the supplemental enumeration of 6268 children aged between 12 and 23 months. Given that tables CH.2.1 to CH.2.6 have been produced from a larger sample, their estimates have much narrower confidence bounds especially for state level estimates.

Steps for combining data from core (MICS) EAs and data from supplemental (NICS) EAs to 1) Filter CH dataset from core EAs and extract data for children aged between 12 and 23 months and keeping only variables related to child demographic characteristics and immunisation. 2) Combine data from core EAs and data from supplemental EAs

Characteristics of Households