0,55 (Punktzahl, höchste Punktzahl = beste Punktzahl) in 2020. Ein zusammengesetzter Index, der den durchschnittliche Fortschritt dreier grundlegender Dimensionen der menschlichen Entwicklung misst - ein langes und gesundes Leben, Wissen und einen annehmbaren Lebensstandard

Zimbabwe: Human Development Index (0 - 1): Pour cet indicateur, The United Nations fournit des données pour la Zimbabwe de 1980 à 2023. La valeur moyenne pour Zimbabwe pendant cette période était de 0.492 points avec un minimum de 0.425 points en 2005 et un maximum de 0.598 points en 2023.

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

Zimbabwe Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 25.800 % in 2019. Zimbabwe Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 25.800 % from Dec 2019 (Median) to 2019, with 1 observations. The data reached an all-time high of 25.800 % in 2019 and a record low of 25.800 % in 2019. Zimbabwe Multidimensional Poverty Headcount Ratio: UNDP: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zimbabwe – Table ZW.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;

In 2024, Sudan was ranked as the most miserable country in the world, with a misery index score of 374.8. Argentina ranked second with an index score of 195.9. Quality of life around the worldThe misery index was created by the economist Arthur Okun in the 1960s. The index is calculated by adding the unemployment rate, the lending rate and the inflation rate minus percent change of GDP per capita. Another famous tool used for the comparison of development of countries around the world is the Human Development Index, which takes into account such factors as life expectancy at birth, literacy rate, education level and gross national income (GNI) per capita. Better economic conditions correlate with higher quality of life Economic conditions affect the life expectancy, which is much higher in the wealthiest regions. With a life expectancy of 85 years, Liechtenstein led the ranking of countries with the highest life expectancy in 2023. On the other hand, Nigeria was the country with the lowest life expectancy, where men were expected to live 55 years as of 2024. The Global Liveability Index ranks the quality of life in cities around the world, basing on political, social, economic and environmental aspects, such as personal safety and health, education and transport services and other public services. In 2024, Vienna was ranked as the city with the highest quality of life worldwide.

Abstract

The MIMS 2009 is a customised version of the third Multiple Indicator Cluster Survey1 (MICS3), which collects a broad array of valuable information on the situation of children and women in Zimbabwe. The MICS has been harmonized with other data collection efforts so that it produces internationally comparable information, which is the cornerstone of evidence-based decision making and formulation of policies, strategies and interventions, aimed at the improvement of the lives of children, women and other vulnerable groups.

The MICS uses three modular questionnaires that can be customized to fit national data needs. It measures key indicators on the following topics: nutrition, child mortality, child health, reproductive health, child development, education, child protection, HIV and AIDS, sexual behaviour and Orphans and Vulnerable Children (OVC). In the process of customizing MICS3 to MIMS, additional non-MICS questions on household expenditure, migration, and environmental assessment were added and some modules such as child development and sexual behaviour were excluded. However, the MIMS data collection instruments remained mostly the same as the global MICS instruments to ensure comparability with national data sets such as the Zimbabwe Demographic and Health Survey (ZDHS) as well as data from other countries.

The MIMS was based on the need to monitor progress towards goals and targets emanating from recent international agreements such as the Millennium Declaration which enshrines the Millennium Development Goals (MDGs), adopted by all 191 United Nations Member States in September 2000; the Plan of Action of A World Fit For Children (WFFC), adopted by 189 Member States at the United Nations Special Session on Children in May 2002; the Convention on the Rights of the Child, 1989; and the Convention on the Elimination of All Forms of Discrimination against Women, 1979 and the United Nations General Assembly Special Session (UNGASS), 2001 on the human immuno-deficiency virus (HIV) and the acquired immunodeficiency syndrome (AIDS). All these commitments build upon promises made by the international community at the 1990 World Summit for Children. In signing these international agreements, governments committed themselves to improving conditions for women and children and to monitor progress towards that end.

Specifically, the MIMS 2009 objectives were to: • collect socio-economic data that will bring out an array of information on health, human capital and well-being of the population that can be used as a baseline for development interventions; • provide decision makers with evidence on children’s and women’s rights and other vulnerable groups in Zimbabwe; • serve as a monitoring tool on almost half of all the 2015 Millennium Development Goal (MDG) indicators, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; and • build capacity of national partners in data collection, compilation, processing, analysis and reporting.

Geographic coverage

National

Analysis unit

• Households
• Children under five years
• Women aged 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The MIMS 2009 was designed to provide estimates on a large number of indicators on the health status of women, children and other vulnerable populations at the national level, for urban and rural areas, as well as for the 10 administrative provinces in Zimbabwe namely; Manicaland, Mashonaland Central, Mashonaland East, Mashonaland West, Matabeleland North, Matabeleland South, Midlands, Masvingo, Harare, and Bulawayo. Harare and Bulawayo provinces are predominantly urban provinces whilst the rest are predominantly rural. The sampling frame for the MIMS was based on the 2002 Zimbabwe Master Sample (ZMS02),developed by the ZIMSTAT, then the CSO after the 2002 Population Census. With the exception of Harare and Bulawayo, each of the other eight provinces was stratified into four groups according to land use: (i) communal lands, (ii) large scale commercial farming areas (LSCFA), (iii) urban and semi-urban areas, and (iv) small scale commercial farming areas (SSCFA) and resettlement areas. Only one urban stratum each was formed for Harare and Bulawayo. There were a total of 34 strata for the whole country.

A representative probability sample of 12 500 households was selected for the MIMS 2009. The sample was selected in two stages with enumeration areas (EAs) as the first stage and households as the second stage sampling units. Each EA was delineated for the 2002 Population Census operations with well-defined boundaries identified on sketch maps, and the EA size was based on the expected workload for one interviewer. The EAs had an average of 100 households each, which was ideal for the survey listing operation.

In total the ZMS02 consists of 1 200 EAs selected with probability proportional to size (PPS), the size being the number of households enumerated in the 2002 Population Census. The MIMS EA selection was a systematic, one-stage operation, carried out independently for each of the 34 strata. In the second stage, a complete listing of households was conducted in the 500 sample EAs for the MIMS 2009 from 23 to 28 February 2009 concurrently for the 10 provinces. The list of households obtained was used as the frame for the second stage random systematic selection of 25 households from each sample EA. Within these selected households, all women aged 15-49 years identified were eligible for individual interviews. In addition, children under five years in the selected households were also identified and either their mothers or caretakers were interviewed on their behalf and children's measurements of weight, height and Mid-Upper-Arm Circumference (MUAC) taken and oedema checked.

The sample was stratified by province and land use and is not self-weighting. For reporting national level results, sample weights are used.

Note: Detailed sample design description can be found in Appendix B of the 2009 Zimbabwe MIMS final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the survey as follows: • A household questionnaire -- was used to collect information on all de-jure and defacto household members, dwelling units, household characteristics and to identify eligible individuals for the women and children questionnaire interviews; • A woman’s questionnaire -- was administered in each selected household to all women aged 15-49 years; and • A questionnaire for children under five years -- was administered to mothers or caretakers of all children under five years living in the household.

The questionnaires were based on the MICS model questionnaire with modifications and additions. Even though the questionnaires were in English, they were translated into the various vernacular languages during interviews.

PRE-TEST The MIMS questionnaires were pre-tested from 9 to 17 March, 2009. Ten (10) teams were formed, made up of a supervisor and five interviewers each for the pretest, after they were trained on the questionnaires. The pre-test training was conducted during the same period, for 92 participants, with 7 participants coming from each of Zimbabwe’s 10 provinces (including the provincial supervisor). The remainder were from the ZIMSTAT, then the CSO, Survey Management Team (SMT), UNICEF and the Steering and Technical Committee members who facilitated the training sessions. A pre-test was conducted in three selected localities (2 urban and 1 rural) in Harare and Mashonaland East provinces to test the entirety of survey procedures. Based on the results of the pre-test, further modifications were made to the wording and flow of the questionnaires.

Cleaning operations

Data was entered on 56 microcomputers by 56 data entry operators, four questionnaire administrators and four data entry supervisors using the Census and Survey Processing (CSPro) system. In order to ensure quality control, all questionnaires were double entered and Survey Management Team as secondary editors complemented the efforts of the data entry supervisors to perform internal consistency checks. Procedures and standard programs developed under the global MICS3 Project were adapted to the MIMS questionnaire and used throughout the processing. One week data entry training was organized for all data entry operators from 27 April to 1 May, 2009. Data entry began on 5 May two weeks after fieldwork had started and the two activities ran concurrently thereafter. Data entry was completed on 24 June, 2009 and the last ten days included secondary editing. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software and the model program syntax and tabulation plans were customized for the MIMS.

Sampling error estimates

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

Calculation of Sampling Errors The following sampling error measures are presented in this appendix for each of the selected indicators: - Standard error (se): Sampling errors are usually measured in terms of standard errors for particular indicators (means, proportions etc).