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Population, female (% of total population) in Kazakhstan was reported at 51.29 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kazakhstan - Population, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.
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Kazakhstan KZ: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.060 Ratio in 2016. This stayed constant from the previous number of 1.060 Ratio for 2015. Kazakhstan KZ: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.061 Ratio from Dec 1962 (Median) to 2016, with 20 observations. The data reached an all-time high of 1.065 Ratio in 1982 and a record low of 1.057 Ratio in 2002. Kazakhstan KZ: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kazakhstan – Table KZ.World Bank: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;
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Kazakhstan Population: Urban: Non Labour Force: Male Over 59, Female Over 54 Years Old data was reported at 1,188.316 Person th in 2016. This records an increase from the previous number of 1,143.215 Person th for 2015. Kazakhstan Population: Urban: Non Labour Force: Male Over 59, Female Over 54 Years Old data is updated yearly, averaging 987.900 Person th from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 1,188.316 Person th in 2016 and a record low of 910.600 Person th in 2007. Kazakhstan Population: Urban: Non Labour Force: Male Over 59, Female Over 54 Years Old data remains active status in CEIC and is reported by The Agency of Statistics of the Republic of Kazakhstan. The data is categorized under Global Database’s Kazakhstan – Table KZ.G002: Population: by Age.
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Kazakhstan Population: Rural: Non Labour Force: Male Over 59, Female Over 54 Years Old data was reported at 787.276 Person th in 2016. This records an increase from the previous number of 761.420 Person th for 2015. Kazakhstan Population: Rural: Non Labour Force: Male Over 59, Female Over 54 Years Old data is updated yearly, averaging 685.150 Person th from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 802.100 Person th in 1995 and a record low of 601.300 Person th in 2003. Kazakhstan Population: Rural: Non Labour Force: Male Over 59, Female Over 54 Years Old data remains active status in CEIC and is reported by The Agency of Statistics of the Republic of Kazakhstan. The data is categorized under Global Database’s Kazakhstan – Table KZ.G002: Population: by Age.
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This scatter chart displays male population (people) against female population (people) in Kazakhstan. The data is filtered where the date is 2021. The data is about countries per year.
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This scatter chart displays proportion of seats held by women in national parliaments (%) against male population (people) in Kazakhstan. The data is filtered where the date is 2023. The data is about countries per year.
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
A description of the modelling methods used for age and gender structures can be found in
"https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank">
Tatem et al and
Pezzulo et al. Details of the input population count datasets used can be found here, and age/gender structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined
here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646
Russia had the highest population in the Commonwealth of Independent States (CIS), at around 144.8 million in 2023. Women made up approximately 53.6 percent of the population. It was followed by Ukraine and Uzbekistan, with populations of 37.9 and 35.4 million people, respectively. The CIS country whose population grew at the highest rate was Kazakhstan in 2022.
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This scatter chart displays proportion of seats held by women in national parliaments (%) against male population (people) in Kazakhstan. The data is filtered where the date is 2021. The data is about countries per year.
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This dataset is about countries per year in Kazakhstan. It has 1 row and is filtered where the date is 2023. It features 4 columns: country, male population, and proportion of seats held by women in national parliaments.
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Kazakhstan KZ: Life Expectancy at Birth: Total data was reported at 72.300 Year in 2016. This records an increase from the previous number of 72.000 Year for 2015. Kazakhstan KZ: Life Expectancy at Birth: Total data is updated yearly, averaging 65.866 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 72.300 Year in 2016 and a record low of 58.368 Year in 1960. Kazakhstan KZ: Life Expectancy at Birth: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kazakhstan – Table KZ.World Bank: Health Statistics. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision, or derived from male and female life expectancy at birth from sources such as: (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;
Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.
The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.
The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.
The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.
The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.
There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.
Households and individuals
The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.
If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.
The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.
Sample survey data [ssd]
SAMPLING GUIDELINES FOR WHS
Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.
The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.
The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.
All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO
STRATIFICATION
Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.
Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).
Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.
MULTI-STAGE CLUSTER SELECTION
A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.
In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.
In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.
It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population, female (% of total population) in Kazakhstan was reported at 51.29 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kazakhstan - Population, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.