Cambodia KH: Birth Rate: Crude: per 1000 People data was reported at 20.752 Ratio in 2023. This records a decrease from the previous number of 21.279 Ratio for 2022. Cambodia KH: Birth Rate: Crude: per 1000 People data is updated yearly, averaging 33.607 Ratio from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 51.415 Ratio in 1984 and a record low of 19.576 Ratio in 1977. Cambodia KH: Birth Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cambodia – Table KH.World Bank.WDI: Population and Urbanization Statistics. Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.;(1) United Nations Population Division. World Population Prospects: 2024 Revision; (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics; (4) United Nations Statistics Division. Population and Vital Statistics Reprot (various years).;Weighted average;

Cambodia KH: Death Rate: Crude: per 1000 People data was reported at 6.390 Ratio in 2023. This records an increase from the previous number of 6.323 Ratio for 2022. Cambodia KH: Death Rate: Crude: per 1000 People data is updated yearly, averaging 12.052 Ratio from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 93.923 Ratio in 1978 and a record low of 6.010 Ratio in 2014. Cambodia KH: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cambodia – Table KH.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.;(1) United Nations Population Division. World Population Prospects: 2024 Revision; (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics; (4) United Nations Statistics Division. Population and Vital Statistics Reprot (various years).;Weighted average;

In 2023, the death rate in deaths per 1,000 inhabitants in Cambodia stood at ****. Between 1960 and 2023, the figure dropped by ****, though the decline followed an uneven course rather than a steady trajectory.

Cambodia KH: Maternal Mortality Ratio: Modeled Estimate: per 100,000 Live Births data was reported at 137.000 Ratio in 2023. This records a decrease from the previous number of 159.000 Ratio for 2022. Cambodia KH: Maternal Mortality Ratio: Modeled Estimate: per 100,000 Live Births data is updated yearly, averaging 344.000 Ratio from Dec 1985 (Median) to 2023, with 39 observations. The data reached an all-time high of 874.000 Ratio in 1985 and a record low of 137.000 Ratio in 2023. Cambodia KH: Maternal Mortality Ratio: Modeled Estimate: per 100,000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cambodia – Table KH.World Bank.WDI: Social: Health Statistics. Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births. The data are estimated with a regression model using information on the proportion of maternal deaths among non-AIDS deaths in women ages 15-49, fertility, birth attendants, and GDP measured using purchasing power parities (PPPs).;WHO, UNICEF, UNFPA, World Bank Group, and UNDESA/Population Division. Trends in maternal mortality estimates 2000 to 2023. Geneva, World Health Organization, 2025;Weighted average;This indicator represents the risk associated with each pregnancy and is also a Sustainable Development Goal Indicator (3.1.1) for monitoring maternal health.

Cambodia KH: Life Expectancy at Birth: Total data was reported at 70.668 Year in 2023. This records an increase from the previous number of 70.528 Year for 2022. Cambodia KH: Life Expectancy at Birth: Total data is updated yearly, averaging 55.665 Year from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 70.668 Year in 2023 and a record low of 11.295 Year in 1977. Cambodia KH: 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 Cambodia – Table KH.World Bank.WDI: Social: 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: 2024 Revision; or derived from male and female life expectancy at birth from sources such as: (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics.;Weighted average;

Abstract

The primary objective of the Cambodia National Health Survey is to provide the Ministry of Health with reliable, population-based, nationally representative data or infant/child mortality, fertility, and related health service indicators.

A secondary objective was to provide the ADB-financed Basic Helath Services Project (BHSP) and the World Bank finaced Cambodia Disease Control and Health Development Project (CDCP) with baseline information about their respective Project areas, against which project impact could later be assessed.

Geographic coverage

National coverage

Analysis unit

Household Women age 15-49 Children under age 5

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design and Selection The NHS sample was designed to provide estimates of kwy health indicators including infant/ child mortality rates and fertility rates for the country as a whole, for urban and rural residence, and for the two project catchment areas (the Basic Health Services Project and the Cambodia Disease Control and Health Development Project). In addition, the design allows for estimates of most key variables (but not for the vaccination coverage of children, fertility rates, or mortality rates) for 14 Provinces. In the other Provinces, the sample size is not sufficiently large to allow for province-level estimates. In order to provide sufficient cases to meet the survey objectives, the number of households selected in the NHS sample from each Province was disproportional to the size of the population in the Province. The above arrangements imply stratification into 40 strata, with 40 different sampling fractions. These strata are 20 Provinces, each divided into an urban and a rural sector. As a result, the NHS sample is self-weighting within strata; weights are only necessary when making estimates across more than one stratum.

For a more complete description of the NHS sample design, see Appendix A of the survey final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The NHS involved two types of questionnaires: a household questionnaire and an individual questionnaire. The household questionnaire was administered to all selected households; the individual questionnaire was administered to all women aged 15-49 identified in the household questionnaire as either usual residents of the household or visitors who stayed there on the night before the day of interview. These questionnaires were developed to measure the desired indicators identified by the MOH and Technical Steering Committee. Wording and structure of the questionnaires, where applicable, was based on the model survey instruments Macro International has used in similar surveys worldwide.

The household questionnaire consisted of three parts: 1) a household schedule giving demographic details of all usual household members and overnight visitors; 2) a series of questions relating to the utilization of health services for any household members who had been ill or injured in the past 30 days; and 3) questions about wall and roof materials of the home and household possessions, which in turn were used to compose a measure of overall household socio-economic status.

The individual questionnaire administered to women aged 15-49 gathered detailed information about the woman's reproductive history, and maternal and child health related knowledge and practices. Questions specific to child health practices were limited to children born after January 1993. (i.e., children under age 5)

The questionnaire was developed in English, translated into Khmer, then back translated and corrected. Following this, a three day pretest covering 100 households was conducted in Phnom Penh and rural Kandal Province by twenty interviewers after initial two week training. The questionnaires were finalized following the pretest.

Cleaning operations

Data Processing was conducted by NIPH with technical assistance form Macro International. The NIPH central office collected questionnaires form supervisors as soon as a cluster was completed. Office editors reviewed questionnaires for consistency and completeness. The data from the questionnaires were then entered and edited on microcomputers using the Integrated System for Survey Analysis (ISSA), a software package developed especially for such surveys by Macro International. During the machine entry, all questionnaires were reentered for verification. Entry and editing of data began one week after the fieldwork started and was completed by the beginning of August 1998. To provide feedback for the field teams, quality tables were produced every two weeks during the fieldwork. These tables were designed to identify major systematic errors in data collection (e.g. age displacement). The fieldwork coordinators reviewed these tables and, if they found a problem, notified and advised all teams of the steps to be taken to avoid this problem in the future.

Response rate

A total of 7,654 women were identified as eligible to be interviewed. Questionnaires were completed for 7,630 of those women, a response rate of 99.7 precent. There is a little difference between the household and individual response rates in urban and rural areas. The same is true for the two project areas.

Sampling error estimates

The estimate from a sample survey is affected by two types of errors: 1) nonsampling errors, and 2) sampling errors. Nonsampling errors are the results of mistake made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the National Health Survey (NHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling error, on the other hand, can be evaluated statistically. The sample of respondents selected in the NHS is only one of many samples that could have been selected from the same population, using the same design and expected 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. Although the degree of variability is nor known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistics will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible sample of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the NHS sample is the result of a multi-stage stratified design and consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the NHS is the ISSA Sampling Error Module. This module used the Taylor linearization method of variance estimation for survey estimates that are means of proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

For details of sampling error estimations information see Appendix B of the final survey report.

Data appraisal

Data Quality Tables - Household age distribution - Births by calendar year - Reporting of age at death in days - Reporting of age at death in months

Note: See detailed tables in APPENDIX C of the survey report.

Abstract

The 2005 Cambodia Demographic and Health Survey (CDHS) is the second nationally representative survey conducted in Cambodia on population and health issues. It uses the same methodology as its predecessor, the 2000 Cambodia Demographic and Health Survey, allowing policymakers to use the two surveys to assess trends over time. The primary objective of the CDHS is to provide the Ministry of Health, Ministry of Planning (MOP), and other relevant institutions and users with updated and reliable data on infant and child mortality, fertility preferences, family planning behavior, maternal mortality, utilization of maternal and child health services, health expenditures, women’s status, domestic violence, and knowledge and behavior regarding HIV/AIDS and other sexually transmitted infections. This information contributes to policy decisions, planning, monitoring, and program evaluation for the development of Cambodia at both national- and local-government levels.The long-term objectives of the survey are to technically strengthen the capacity of the National Institute of Public Health (NIPH), Ministry of Health, and the National Institute of Statistics (NIS) of MOP for planning, conducting, and analyzing the results of further surveys.

Geographic coverage

The sample was designed to provide estimates of the indicators at the national level, for urban and rural areas, and for 19 domains: 1.Banteay Mean Chey, 2.Kampong Cham, 3.Kampong Chhnang, 4.Kampong Speu, 5.Kampong Thom, 6.Kandal, 7.Phnom Penh, 8.Prey Veng, 9.Pursat, 10.Svay Rieng, 11.Takeo, 12.Kratie, 13.Siem Reap, 14.Otdar Mean Chey, 15. Battambang and Krong Pailin, 16. Kampot and Krong Kep, 17.Krong Preah Sihanouk and Kaoh Kong, 18.Preah Vihear and Steng Treng; and 19.Mondol Kiri and Rattanak Kiri.

Analysis unit

Household, individual (including women and men between the ages of 15 and 49 and children aged 5 and below)

Universe

The survey covered the whole resident population (regular household) , with the exception of homeless in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

TThe 2005 CDHS sample is a stratified sample selected in two stages. Stratification is achieved by separating every study domain into urban and rural areas. Areas are defined as urban or rural based on the classification in the 1998 GPC, provided by NIS. Therefore the 19 domains are stratified into 38 sampling strata in total. Samples are selected independently in every stratum, by a two-stage selection. This means that 38 independent samples were selected, one from each sampling stratum. Implicit stratifications were achieved at each of the lower geographical or administrative levels by sorting the sampling frame according to the geographical/administrative order and by using a probability proportional to the size selection in the first stage of sampling. The explicit and implicit stratifications together guarantee a better scattering of the sampled points. In the first stage of selection, 557 villages were selected with a probability proportional to the village size. The village size is the number of households in the village. After this selection and before the data collection, an updating operation was conducted over all of the 557 selected villages. The updating operation consisted of visits to every selected village. During the visits, records were made of every structure found on the ground; structures were identified by type (residential or not); number of households in each residential structure were identified; location map and a sketch map were drawn showing the boundaries of the village and the location of each structure. This important operation guaranteed the quality of the fieldwork and prevented nonsampling errors. A household list was set up for each selected village. The resulting lists of households served as the sampling frame for the selection of households in the second stage. Some of the selected villages were big. To minimize the task of household listing, villages with more than 300 households were segmented. A segment corresponds to an enumeration area (EA) that was created for the GPC 1998. Size and boundaries were well-defined and maps were available. Among segmented villages, only one EA was selected from the village with a selection probability proportional to the EA size. Household listing was conducted only in the selected EA. Therefore, a CDHS cluster is either a village or an EA. Detailed information on the sampling methodology is available in Appendix A to the Survey Report.

In the second stage of selection, a fixed number of 24 households were selected in every urban cluster, and 28 households were selected in every rural cluster. They were selected by an equal probability systematic sampling. The decision on number of households selected per cluster is a tradeoff between fieldwork efficiency and precision. All women ages 15-49 in the selected households were eligible for the interview. The advantages of this two-stage selection procedure are: 1. It is simple to implement and reduces possible nonsampling errors. 2. It is easy to locate the selected households, reducing nonsampling errors and nonresponse. 3. The interviewers interview only the households in the preselected dwellings. No allowance for replacement of dwellings prevents survey bias.

Sampling deviation

Creation of the 2005 CDHS sample was based on the objective of collecting a nationally representative sample of completed interviews with women and men between the ages of 15 and 49. To achieve a balance between the ability to provide estimates for all 24 provinces in the country and limiting the sample size, 19 sampling domains were defined, 14 of which correspond to individual

provinces and 5 of which correspond to grouped provinces.

• Fourteen individual provinces: Banteay Mean Chey, Kampong Cham, Kampong Chhnang, Kampong Speu, Kampong Thom, Kandal, Kratie, Phnom Penh, Prey Veng, Pursat, Siem Reap, Svay Rieng, Takeo, and Otdar Mean Chey;

• Five groups of provinces: Battambang and Krong Pailin, Kampot and Krong Kep, Krong Preah Sihanouk and Kaoh Kong, Preah Vihear and Steung Treng, Mondol Kiri, and Rattanak Kiri.

The sample of households was allocated to the sampling domains in such a way that estimates of indicators can be produced with known precision for each of the 19 sampling domains, for all of Cambodia combined, and separately for urban and rural areas of the country.

The sampling frame used for 2005 CDHS is the complete list of all villages enumerated in the 1998 Cambodia General Population Census (GPC) plus 166 villages which were not enumerated during the 1998 GPC, provided by the National Institute of Statistics (NIS). It includes the entire country and consists of 13,505 villages. The GPC also created maps that delimited the boundaries of every village. Of the total villages, 1,312 villages are designated as urban and 12,193 villages are designated as rural, with an average household size of 161 households per village. The survey is based on a stratified sample selected in two stages. Stratification was achieved by separating every reporting domain into urban and rural areas. Thus the 19 domains were stratified into a total of 38 sampling strata. Samples were selected independently in every stratum, by a two

stage selection. Implicit stratifications were achieved at each of the lower geographical or administrative levels by sorting the sampling frame according to the geographical/administrative order and by using a probability proportional to size selection at the first stage of selection.

(Please see the report of external resources)

Mode of data collection

Face-to-face [f2f]

Research instrument

There are three types of questionnaires used in the CDHS: the Household Questionnaire, the Individual Woman's Questionnaire, and the Individual Man's Questionnaire.

The households that have been scientifically selected to be included in the CDHS sample were visited and interviewed using a Household Questionnaire. The Household Questionnaire consisted of a cover sheet to identify the household and a form on which all members of the household and visitors were listed. Data collected about each household member were name, sex, age, education, and survival of parents for children under age 18 years, etc. The Household Questionnaire was used to collect information on housing characteristics such as type of water, sanitation facilities, quality of flooring, and ownership of durable goods.

The Household Questionnaire permitted the interviewer to identify women and men who were eligible for the Individual Questionnaire. Women ages 15-49 years in every selected household who are members of the household (those that usually live in the household) and visitors (those who do not usually live in the household but who slept there the previous night) were eligible to be interviewed with the individual Woman's Questionnaire.

After all of the eligible women in a household have been identified, female interviewers used the Woman's Questionnaire to interview the women. The Woman's Questionnaire collected information on the following topics:

 · socio-demographic characteristics

 · reproduction

 · birth spacing

 · maternal health care and breastfeeding

 · immunization and health of children

 · cause of death of children

 · marriage and sexual activity

 · fertility preferences

 · characteristics of the husband and employment activity of the woman

 · HIV/AIDS and other sexually transmitted infections

 · maternal mortality

 · women's status

 · household

Abstract

The 2021-22 Cambodia Demographic and Health Survey (2021-22 CDHS) was implemented by the National Institute of Statistics (NIS) in collaboration with the Ministry of Health (MoH). Data collection took place from September 15, 2021, to February 15, 2022.

The primary objective of the 2021-22 CDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking.

The information collected through the 2021-22 CDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of Cambodia’s population. The survey also provides data on indicators relevant to the Sustainable Development Goals (SDGs) for Cambodia.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used in the 2021-22 CDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Cambodia. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

Cleaning operations

The processing of the 2021-22 CDHS data began as soon as the fieldwork started. When data collection was completed in each cluster, the electronic data files were transferred via the IFSS to the NIS central office in Phnom Penh. The data files were registered and checked for inconsistencies, incompleteness, and outliers. Errors and inconsistencies were communicated to the field teams for review and correction. Secondary editing, done by NIS data processors, was carried out in the central office and included resolving inconsistencies and coding open-ended questions. The paper Biomarker Questionnaires were collected by field coordinators and then compared with the electronic data files to assess whether any inconsistencies arose during data entry. Data processing and editing were carried out using the CSPro software package. The concurrent data collection and processing offered an advantage because it maximized the likelihood of the data being error-free. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in March 2022.

Response rate

A total of 21,270 households were selected for the CDHS sample, of which 20,967 were found to be occupied. Of the occupied households, 20,806 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 19,845 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 19,496 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 9,079 men age 15-49 were identified as eligible for individual interviews and 8,825 were successfully interviewed, yielding a response rate of 97%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are errors that were made during data collection and data processing such as failure to locate and interview the correct household, misunderstanding of the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2021-22 Cambodia Demographic and Health Survey (CDHS) to minimize this type of error, nonsampling errors are impossible to eliminate completely and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2021-22 CDHS is only one of many possible samples that could have been selected from the same population, using exactly the same design. Each of those 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. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2021-22 CDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2021-22 CDHS was an SAS program. This program used the Taylor linearization method for estimate variances for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Height and weight data completeness and quality for children
• Height measurements from random subsample of measured children
• Interference in height and weight measurements of children
• Interference in height and weight measurements of women
• Heaping in anthropometric measurements for children (digit preference)
• Observation of handwashing facility
• School attendance by single-year age
• Vaccination cards photographed
• Number of enumeration areas completed by month and province
• Sibship size and sex ratio of siblings
• Pregnancy-related mortality trends
• Pregnancy-related mortality

See details of the data quality tables in Appendix C of the final report.

The life expectancy experiences significant growth in all gender groups in 2023. As part of the positive trend, the life expectancy reaches the maximum value for the different genders at the end of the comparison period. Particularly noteworthy is the life expectancy of women at birth, which has the highest value of 73.19 years. Life expectancy at birth refers to the number of years that the average newborn can expect to live, providing that mortality patterns at the time of their birth do not change thereafter.Find further similar statistics for other countries or regions like UAE and The Gambia.

Abstract

The Cambodia Demographic and Health Survey in 2010 (CDHS 2010) is the third nationally representative survey conducted in Cambodia on population and health issues. It uses the same methodology as its predecessors, the 2000 and the 2005 Cambodia Demographic and Health Surveys, allowing policymakers to use these surveys to assess trends over time. The primary objective of the CDHS is to provide the Ministry of Health (MOH), Ministry of Planning (MOP), and other relevant institutions and users with updated and reliable data on infant and child mortality, fertility preferences, family planning behavior, maternal mortality, utilization of maternal and child health services, health expenditures, women’s status, and knowledge and behavior regarding HIV/AIDS and other sexually transmitted infections. This information contributes to policy decisions, planning, monitoring, and program evaluation for the development of Cambodia at both the national and local government levels.

Geographic coverage

The sample was designed to provide estimates of the indicators at the national level, for urban and rural areas, and for 19 domains: 1.Banteay Mean Chey, 2.Kampong Cham, 3.Kampong Chhnang, 4.Kampong Speu, 5.Kampong Thom, 6.Kandal, 7.Phnom Penh, 8.Prey Veng, 9.Pursat, 10.Svay Rieng, 11.Takeo, 12.Kratie, 13.Siem Reap, 14.Otdar Mean Chey, 15. Battambang and Krong Pailin, 16. Kampot and Krong Kep, 17.Krong Preah Sihanouk and Kaoh Kong, 18.Preah Vihear and Steng Treng; and 19.Mondol Kiri and Rattanak Kiri.

Analysis unit

Household, individual (including women and men between the ages of 15 and 49), and children aged 5 and below.

Universe

The survey covered the whole resident population (regular household) , with the exception of homeless in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey was based on a stratified sample selected in two stages. Stratification was achieved by separating every reporting domain into urban and rural areas. Thus, the 19 domains. Samples were selected independently in every stratum through a two-stage selection process. Implicit stratifications were achieved at each of the lower geographical or administrative levels by sorting the sampling frame according to geographical/administrative order and by using a probability proportional to size selection strategy at the first stage of selection. (Please refer to technical doccuments for details).

Mode of data collection

Face-to-face [f2f]

Research instrument

There are three types of questionnaires used in the CDHS: the Household Questionnaire, the Individual Woman's Questionnaire, and the Individual Man's Questionnaire.

The households that have been scientifically selected to be included in the CDHS sample were visited and interviewed using a Household Questionnaire. The Household Questionnaire consisted of a cover sheet to identify the household and a form on which all members of the household and visitors were listed. Data collected about each household member were name, sex, age, education, and survival of parents for children under age 18 years, etc. The Household Questionnaire was used to collect information on housing characteristics such as type of water, sanitation facilities, quality of flooring, and ownership of durable goods.

The Household Questionnaire permitted the interviewer to identify women and men who were eligible for the Individual Questionnaire. Women ages 15-49 years in every selected household who are members of the household (those that usually live in the household) and visitors (those who do not usually live in the household but who slept there the previous night) were eligible to be interviewed with the individual Woman's Questionnaire.

After all of the eligible women in a household have been identified, female interviewers used the Woman's Questionnaire to interview the women. The Woman's Questionnaire collected information on the following topics:

 · socio-demographic characteristics

 · reproduction

 · birth spacing

 · maternal health care and breastfeeding

 · immunization and health of children

 · cause of death of children

 · marriage and sexual activity

 · fertility preferences

 · characteristics of the husband and employment activity of the woman

 · HIV

 · maternal mortality

 · women's status

 · household relations

In one-half of the households, men were identified as eligible for individual interview, and the male interviewer of each team used the Man's Questionnaire to interview the eligible men. Team leaders informed their teams which households in the sample have been selected for including interviews with men. The Man's Questionnaire collected information on the following topics:

 · socio-demographic characteristics

 · reproduction

 · birth spacing

 · marriage and sexual activity

 · HIV

Biomarker data collection were conducted in the same one-half of the households which were selected to include men for interview. The biomarker data collection included: measuring the height and weight of women and children (under age 6 years), anemia testing of women and children, and drawing blood samples from women and men for laboratory testing of HIV. Biomarker data collection were recorded in the Household Questionnaire.

Cleaning operations

Data editing was done in the following data processing stages:

a. Office editing and coding - minimal since CSPro has been designed to be an intelligent data entry program

b. Data entry

c. Completeness of data file

d. Verification of Data - prior to this stage, data are again entered and tagged as V to indicate that the dataset is a verification data

e. Secondary editing

Response rate

Response rate:

Households: 99 per cent

Women ages 15-49: 98 per cent

Men ages 15-49: 95 per cent

See Table 1. Results of the household and individual interviews in the CDHS 2010 Preliminary Report (Refer to technical documents)

Sampling error estimates

The computer software used to calculate sampling errors for the 2010 CDHS is a Macro SAS procedure. This procedure used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. ISSA also computes ISSA computes the design effect (DEFT) for each estimate.

Sampling errors for the 2010 CDHS are calculated for selected variables considered to be of primary interest for woman’s survey and for man’s surveys, respectively for the country as a whole, for urban and rural areas, and for each of the 19 study domains.

In South-East Asia, the maternal and child mortality rate has declined over the past decades; however, it varies among and within the countries in the region, including Cambodia. The continuum of care is an integrated series of care that women and children are required to avail continuously from pregnancy to the child/motherhood period. This study aimed to assess the completion rate of the continuum of care and examine the factors associated with the continuum of care in Ratanakiri, Cambodia. A cross-sectional study was conducted in Ratanakiri. Overall, 377 women were included, and data were collected via face-to-face interviews using a semi-structured questionnaire. Among them, 5.0% completed the continuum of care (antenatal care at least four times, delivery by skilled birth attendant, and postnatal care at least once). Meanwhile, 18.8% did not receive any care during pregnancy, delivery, and after birth. The highest discontinuation rate was at the postnatal care stage (73.6%). Not receiving any perinatal care was associated with neonatal complications at 6 weeks after birth (adjusted odds ratio [AOR]: 3.075; 95% confidence interval [CI]: 1.310–7.215). Furthermore, a long distance to the health center was negatively associated with completion of the continuum of care (AOR: 0.877; 95% CI: 0.791–0.972). This study indicates the need for efforts to reduce the number of women who discontinue from the continuum of care, as well as who do not receive any care to avoid neonatal complications. Since the discontinuation rate was highest at the postnatal care, postnatal care needs to be promoted more through the antenatal care and delivery services. Furthermore, given that long distance to health facilities was a barrier for receiving the care continuously, our findings suggest the need for a village-based health care system that can provide the basic continuum of care in remote areas.

The total life expectancy at birth in Cambodia was 70.67 years in 2023. Between 1960 and 2023, the life expectancy at birth rose by 28.54 years, though the increase followed an uneven trajectory rather than a consistent upward trend.

In 2010, cancer deaths accounted for more than 15% of all deaths worldwide, and this fraction is estimated to rise in the coming years. Increased cancer mortality has been observed in immigrant populations, but a comprehensive analysis by country of birth has not been conducted. We followed all individuals living in Sweden between 1961 and 2009 (7,109,327 men and 6,958,714 women), and calculated crude cancer mortality rates and age-standardized rates (ASRs) using the world population for standardization. We observed a downward trend in all-site ASRs over the past two decades in men regardless of country of birth but no such trend was found in women. All-site cancer mortality increased with decreasing levels of education regardless of sex and country of birth (p for trend <0.001). We also compared cancer mortality rates among foreign-born (13.9%) and Sweden-born (86.1%) individuals and determined the effect of education level and sex estimated by mortality rate ratios (MRRs) using multivariable Poisson regression. All-site cancer mortality was slightly higher among foreign-born than Sweden-born men (MRR = 1.05, 95% confidence interval 1.04–1.07), but similar mortality risks was found among foreign-born and Sweden-born women. Men born in Angola, Laos, and Cambodia had the highest cancer mortality risk. Women born in all countries except Iceland, Denmark, and Mexico had a similar or smaller risk than women born in Sweden. Cancer-specific mortality analysis showed an increased risk for cervical and lung cancer in both sexes but a decreased risk for colon, breast, and prostate cancer mortality among foreign-born compared with Sweden-born individuals. Further studies are required to fully understand the causes of the observed inequalities in mortality across levels of education and countries of birth.

Abstract

The Cambodia Inter-Censal Population Survey, 2004 was designed not only to obtain the much-needed demographic data following the census, but also to serve as a means to train the staff of the NIS and Provincial Planning Offices in demographic data collection.

There are plans to produce in-depth studies on fertility, mortality, migration, literacy and education, labour force, housing and household amenities, and population projections based on the results of the survey.

The Cambodia Inter-Censal Population Survey 2004 (CIPS) is a nationally representative sample survey taken between two censuses, the 1998 census and the proposed 2008 census, in order to update information on population size and growth and other population characteristics as well as household facilities and amenities. Due to the national elections and administrative issues, the CIPS was undertaken in March 2004 instead of 2003, which would have been the five-year midpoint between the 1998 and 2008 censuses.

The conduct of the CIPS 2004 is an important step in the creation of a continuous flow of data that will allow Cambodia to prepare plans and programmes supported by a strong database.

The Cambodia Inter-Censal Population Survey 2004 was conducted with the objective of providing information on the following indicators: - Sex, age and marital status - Births and Deaths - Migration status - Literacy/Educational level - Economic characteristics - Housing and household amenities - Other population and household information

These fresh data will allow for calculations and reliable projections of: - Population size and growth - Fertility - Mortality - Migration

The survey was also intended to train the national staff in sampling, data collection, data processing, analysis and dissemination.

Geographic coverage

National

Analysis unit

Individual, Household

Universe

All Population and housing for all regular households in Cambodia excluding special settlements and institutional households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design for the CIPS 2004 is a three-stage stratified cluster sampling design, it is a probability sample selection of 100 percent of the Cambodian villages coverage areas, the survey covered only regular households and excludes special settlements and institutional households.

The CIPS 2004 was conducted in a nationwide representative sample of 21,000 households within selected 700 villages (primary sampling units) out of 13,886 villages in Cambodia. The 700 villages were selected from updated frame (list of villages for Cambodia).

The General Population Census 1998 databases of the National Institute of Statistics together with the new updated list of villages that were excluded in the general population census of 1998 was used as the sampling frame for the sampling design of the CIPS 2004.

The frame has the following identification particulars: 1- Province code 2- Province name 3- District code 4- District name 5- Commune code 6- Commune name 7- Village Code 8- Village name 9- Size of village (number of households) 10- Area code (1 = Urban, 2 = Rural)

A three-stage sample design has been used for the CIPS. In the first stage a sample of villages was selected. The villages were implicitly stratified into 45 strata (21 provinces each with rural/urban strata i.e. 42 strata plus 3 provinces each totally urban, i.e. 3 urban strata). The villages were selected using linear systematic sampling with probabilities proportionate to size (PPS). The size measure used for the selection was number of households in the village according to the 1998 Census with estimation for a few additional villages not in the 1998 census frame.

In the second stage one Census Enumeration Area was selected randomly (in the head office) in each selected PSU. At the beginning of the fieldwork all households in the EA were listed. A systematic sample of 30 non-vacant households was selected as the third stage of selection.

The listing of households in the EA would become cumbersome if there are many households in the EA. This might be the case when the enumeration area had grown substantially since the census. When the EA was large (population wise) the interviewer was instructed to split the EA into two or more approximately equal-sized segments and to select one segment randomly. All households in the selected segment were listed. Out of the 700 Sample PSUs, 598 were from the rural super stratum and the remaining 102 were from the urban super stratum. For more information on sampling for the survey the general report at national level may be referred to.

Note: All provincial headquarters were treated as urban. In the case of Sihanoukville, Kep and Pailin, the entire province was treated as urban. In Phnom Penh province, the four districts of Doun Penh, Chamkar Mon, 7 Makara and Tuol Kouk were classified as urban. All the remaining areas of the country were rural. Further, urban and rural areas are being reclassified in Cambodia. While these reclassifications have already been drafted, they have not yet been approved by the Royal Government of Cambodia. Upon endorsement and adoption, the new classifications will be used in future census/surveys.

Mode of data collection

Face-to-face [f2f]

Research instrument

The draft questionnaires for the CIPS 2004 were more or less on the 1998 General Census pattern. Some modifications, however, were made by adding new questions on

(i) Whether children aged 0-14 living with own mother (ii) Whether a person's mother is alive and (iii) Details of deaths in households in the last one year with focus on maternal mortality.

Questions mentioned at (i) and (ii) were intended respectively to estimate fertility (by application of own child method) and mortality (by application of orphan hood method). The questions to be included were carefully considered by a Working Group of Cambodia Inter-Censal Population Survey 2004, whose members were mostly from Ministries, NGOs and International Agencies. The Questionnaires were tested twice in the field (both urban and rural) by NIS staff in November 2003. The purpose of the pre-test was to have a full-dressed rehearsal of the whole process and particularly to test the questions in the field so as to make corrections in wording or definitions and to estimate the time taken for enumeration area mapping, house listing, sampling and enumeration of selected household. Based on the pre-test experience the questionnaires were modified and finalized.

Two types of questionnaires were used in the CIPS 2004: Form A House-list and Form B Household Questionnaire.

The Form A was used to collect information on buildings containing one or more households during the preliminary round preceding survey night (March 3, 2004). The information collected related to: construction material of wall, roof and floor, whether it is a wholly or partly residential building, number of households within the building, name and sex of head of household and number of persons usually living in the household.

The Form B, which has five parts, was used for survey enumeration in the period closely following the reference time.

In Part I, information on usual members of the selected household present on survey night, visitors present as well as usual members absent on survey night, was collected.

Part II was used to collect information on each usual member of the household and each visitor present on survey night. The information collected included: full name, relationship to household head, sex, age, natural mother, child aged 0-14 living with own mother, marital status, age at first marriage, mother tongue, religion, place of birth, previous residence, duration of stay, reason for migration, literacy, full time education and economic characteristics.

Part III was used to collect information on females of reproductive age (15-49) as well as children born to these women.

The information collected in part IV related to household conditions and facilities: main source of light, main cooking fuel used, whether toilet facility is available, main source of drinking water and number of living rooms occupied by household.

Part V was used to record the following information in respect of deaths in the household within the last one year:- name of deceased, sex, relationship to head of household, age at death, whether the death has been registered with the civil authorities or not, the cause of death and maternal mortality information.

Cleaning operations

The completed records (Forms A, Form B, Form I, Form II, Map, and other Forms) were systematically collected from the provinces by NIS Survey Coordinators on the due date and submitted to the team receptionist at NIS. NIS Survey Coordinators formed into three teams of two persons were trained during March 7-10 to receive and arrange the completed forms and maps for processing after due checking form the field. Control forms were prescribed by DUC to record every form without any omission. These records were carefully checked, registered and stored in the record room. Editing and coding of the questionnaires were done manually, after which the questionnaires were submitted to the computer section for further processing. The instruction for editing and coding were revised and expanded. Training on editing and coding was conducted for senior staff, who in turn had to train other editors and coders.

The purpose of the editing process was to remove matters of obvious inconsistency, incorrectness and incompleteness, and to improve the quality of data collected. Coding had to be done very carefully in

UNICEF's country profile for Chad, including under-five mortality rates, child health, education and sanitation data.

Cambodia KH: Life Expectancy at Birth: Female data was reported at 73.187 Year in 2023. This records an increase from the previous number of 73.072 Year for 2022. Cambodia KH: Life Expectancy at Birth: Female data is updated yearly, averaging 57.928 Year from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 73.187 Year in 2023 and a record low of 12.749 Year in 1977. Cambodia KH: Life Expectancy at Birth: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cambodia – Table KH.World Bank.WDI: Social: 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: 2024 Revision; (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics.;Weighted average;

In 2023, the number of refugees residing in Cambodia did not change in comparison to the previous year. The number of refugees residing remained at 24 refugees. Refugee population includes people who are outside of their country of origin for reasons of feared persecution, conflict, generalized violence, or other circumstances that have seriously disturbed public order and, therefore, require international protection. Country or territory of asylum is the country or territory where an asylum claim was filed and granted.Find more statistics on other topics about Cambodia with key insights such as male smoking rate, total fertility rate, and infant mortality rate.

This statistic shows the life expectancy at birth in the ASEAN countries in Asia from 2013 to 2023. The ASEAN (Association of Southeast Asian Nations) countries are Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam. In 2023, the average life expectancy at birth in Cambodia was ***** years.

In 2025, the average age in the Philippines is expected to reach 26.1 years, increasing to roughly 46.1 years of age by 2100. This is a significant rise, considering that until the year 2000, the country’s median age was under 20 years old. From 2011 to 2021, the share of very young people decreased, while the age brackets for people aged 15-64 and 65 or older grew. This shift in age structure implies a lower birth rate, as well as an aging population. Birth and family size As of 2020, the birth rate in the Philippines is just under 22 children born per thousand inhabitants each year, about 3 less than in the decade before. The fertility rate has likewise been decreasing since 2007, but is still higher than the Oceania region’s average as of 2020. Fewer newborns each year contributes to a lower median age. High mortality in the Philippines is preventable Life expectancy is also factor in a rising median age, although increasing only marginally in the Philippines compared with neighboring countries Cambodia, Myanmar, and Laos (but still higher than in these countries). The life expectancy in the Philippines was just under 72 years of age in 2017, and roughly three years shorter than in Thailand or Vietnam. One factor that lowers the life expectancy is the high mortality rate due to noncontagious diseases, such as cancer and heart and respiratory problems, accounting for more than a quarter of early deaths from ages 30 to 70 in the Philippines.

Abstract

The Cambodia Inter-censal Population Survey, 2013 was conducted with the following objectives:

i. To strengthen the capacity of the staff of NIS and the provincial and district staff in demographic data collection; and

ii. To provide information to government and data users on population and household characteristics such as household size, age, sex, marital status, literacy and educational characteristics, economic characteristics, fertility, mortality and migration as well as housing and household characteristics and amenities. This should be useful to the government to evaluate the Rectangular Strategy Plan in achieving its intended goals. It will help outline priority goals and strategies to reduce poverty rapidly, and develop Cambodia Millennium Development Goals (CMDG’s) and other Socioeconomic Development Goals. It will also be useful to the National Institute of Statistics (NIS) in improving data availability and accessibility and in utilization of data until the 2018 census information is made available.

Geographic coverage

National Provincial

Analysis unit

Units of Analysis: 1. Individual 2. Household 3. Province

Universe

Population and housing units of all regular households in Cambodia excluding special settlements and institutional households

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

The draft questionnaires for the CIPS 2013 were more or less on the 2008 General Census pattern. Some modifications, however, were made by adding new questions on

(i) whether children aged 0-14 living with own mother (ii) whether a person's mother is alive and (iii) details of deaths in households in the last one year with focus on maternal mortality.

Questions mentioned at (i) and (ii) were intended respectively to estimate fertility (by application of own child method) and mortality (by application of orphan hood method). The questions to be included were carefully considered by a Working Group of Cambodia Inter-Censal Population Survey 2013, whose members were mostly from Ministries, NGOs and International Agencies. The Questionnaires were tested twice in the field (both urban and rural) by NIS staff in November 2012. The purpose of the pre-test was to have a full-dressed rehearsal of the whole process and particularly to test the questions in the field so as to make corrections in wording or definitions and to estimate the time taken for enumeration area mapping, house listing, sampling and enumeration of selected household. Based on the pre-test experience the questionnaires were modified and finalized.

Two types of questionnaires were used in the CIPS 2013: Form A House-list and Form B Household Questionnaire.

The Form A was used to collect information on buildings containing one or more households during the preliminary round preceding survey night (March 3, 2013). The information collected related to: construction material of wall, roof and floor, whether it is a wholly or partly residential building, number of households within the building, name and sex of head of household and number of persons usually living in the household.

The Form B, which has five parts, was used for survey enumeration in the period closely following the reference time.

In Part I, information on usual members of the selected household present on survey night, visitors present as well as usual members absent on survey night, was collected.

Part II was used to collect information on each usual member of the household and each visitor present on survey night. The information collected included: full name, relationship to household head, sex, age, natural mother, child aged 0-14 living with own mother, marital status, age at first marriage, mother tongue, religion, place of birth, previous residence, duration of stay, reason for migration, literacy, full time education and economic characteristics.

Part III was used to collect information on females of reproductive age (15-49) as well as children born to these women.

The information collected in part IV related to household conditions and facilities: main source of light, main cooking fuel used, whether toilet facility is available, main source of drinking water and number of living rooms occupied by household.

Part V was used to record the following information in respect of deaths in the household within the last one year:- name of deceased, sex, relationship to head of household, age at death, whether the death has been registered with the civil authorities or not, the cause of death and maternal mortality information.

Cleaning operations

The completed records (Forms A, Form B, Form I, Form II, Map, and other Forms) were systematically collected from the provinces by NIS Survey Coordinators on the due date and submitted to the team receptionist at NIS. NIS Survey Coordinators formed into three teams of two persons were trained from March 7 to 10 to receive and arrange the completed forms and maps for processing after due checking form the field.

Control forms were prescribed by DUC to record every form without any omission. These records were carefully checked, registered and stored in the record room. Editing and coding of the questionnaires were done manually, after which the questionnaires were submitted to the computer section for further processing.

The instruction for editing and coding were revised and expanded. Training on editing and coding was conducted for senior staff, who in turn had to train other editors and coders. The purpose of the editing process was to remove matters of obvious inconsistency, incorrectness and incompleteness, and to improve the quality of data collected. Coding had to be done very carefully in respect of birthplace and previous place of residence by using the district and province codes, and occupation and industry by using the UN International Standard Classification of Occupation (ISCO) and the International Standard Industrial Classification (ISIC) respectively. For these purposes, NIS utilized staff with sound knowledge and experience of the survey and its concepts. Those who worked as trainers or supervisors were put on this job supplemented by well-trained and tested staff. Editing and Coding was done by two teams (each with six editors and one team leader); so that one of the editors who was trained specifically in occupation/industry coding should do that coding for columns 20 and 22 of part 2 household questionnaire. The work of team members was completely checked by the Team leaders. The training on editing and coding was done from 23 to 26 March. The manual processing commenced on March 29 and was completely done by the end of May 2013.

Response rate

Response rate is 95 per cent.

Sampling error estimates

Calculations of sampling errors have been made for some estimates of totals, means and proportions for variables in Form B (annex 3).

The software used for the calculations is STATA 8.0. For the calculations presented here we have assumed that stratification was done on provinces and urban/rural (an implicit57 stratification on province and urban/rural was used for the sample selection).

In seven of the 45 strata there are only one PSU (EA) selected. This causes a problem for the standard error calculations. It is not possible get standard errors in these strata. In these strata we have split the sole EA in two parts and defined the parts as two PSUs.

The standard errors are generally rather small for estimates for major domains like urban/rural and men/women. The coefficients of variation (CV)1 are below 1% in many cases. The coefficients of variation are substantially higher for provincial estimates, especially for provinces with a small sample (e.g. province19). Design effects (Deff) have been calculated for some estimates. They are, as expected, quite low for estimates of demographic characteristics. They are considerably higher for estimates of socio-economic characteristics like employment status (also as expected). For the demographic characteristics "age at first marriage" and "marital status" we find design effects below 5 for major domains like men/women and urban/rural. The socio-economic characteristics are typically more "clustered" than the demographic characteristics, this shows up in generally higher design effects. For the major domain estimates we find design effects up to 20 and occasionally very high values of 200 or more. These "freak" values occur when the sample in terms of number of PSUs is small and when the PSU averages (or proportions) show large variation. One example is the design effect of 285 for the estimate of proportion of government employees in urban areas. The proportion is varying substantially between the 102 PSUs in the domain, the range is from 0 % to75%.