Demographic and Health Survey 2014
Cambodia, 2014
Get Microdata
Reference ID
KHM_2014_DHS_v01_M
Producer(s)
National Institute of Statistics (NIS), Directorate General for Health (DGH)
Collection(s)
Metadata
Created on
Nov 09, 2015
Last modified
Nov 09, 2015
Page views
33841
Downloads
3098
Identification
Survey ID Number
KHM_2014_DHS_v01_M
Title
Demographic and Health Survey 2014
Country/Economy
| Name | Country code |
|---|---|
| Cambodia | KHM |
Study type
Demographic and Health Survey (Standard) - DHS VII
Series Information
The 2014 Cambodia Demographic and Health Survey is the fourth of its kind and follows similar surveys conducted in 2000, 2005, and 2010. The 2014 CDHS included a nationally representative sample of 15,825 households. All women age 15-49 who were usual members of a sampled household or who slept in the sampled household the night before the survey were eligible to be individually interviewed. The survey resulted in completed interviews with 17,578 de facto women. Similar to previous surveys, the 2014 CDHS was designed to provide information on fertility and childhood mortality, family planning, maternal and child health, and knowledge and behavior regarding AIDS and other sexually transmitted infections (STIs). The survey also collected data on domestic violence among women and micronutrients among mothers and children age 0-5.
Abstract
The 2014 Cambodia Demographic and Health Survey (CDHS) is the fourth nationally representative survey conducted in Cambodia on population and health issues. It uses the same methodology as its predecessors, the 2000, 2005, and 2010 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.
The long-term objectives of the survey are to build the capacity of the Ministry of Health and the National Institute of Statistics (NIS) of the Ministry of Planning for planning, conducting, and analyzing the results of further surveys.
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.
The long-term objectives of the survey are to build the capacity of the Ministry of Health and the National Institute of Statistics (NIS) of the Ministry of Planning for planning, conducting, and analyzing the results of further surveys.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Household
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15-49
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15-49
Scope
Notes
The 2014 Cambodia Demographic and Health Survey covered the following topics:
HOUSEHOLD
• Identification
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, marital status, survivorship and residence of bilogical parents, and highest educational attainment
• Disability
• Physical impairment
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor, roof and walls of the house, and ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status)
• Weight, height, hemoglobin and malaria measurement for children age 0-5
• Weight, height, hemoglobin measurement for women age 15-49
INDIVIDUAL WOMAN
• Respondent background characteristics
• Reproduction, including a complete birth and death history of respondents' live births and information on abortion
• Contraception
• Pregnancy, postnatal care, and women's nutrition
• Immunization, health, children's nutrition, and early childhood development
• Marriage and sexual activity
• Fertility preferences
• Husbands' background and women's work
• HIV/AIDS and other sexually transmitted infections
• Other health issues
• Maternal mortality
• Domestic violence
INDIVIDUAL MAN
• Respondent background characteristics
• Reproduction
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
MICRONUTRIENT
• Micronutrient for children age 6-59 months
• Micronutrient for women age 14-49
HOUSEHOLD
• Identification
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, marital status, survivorship and residence of bilogical parents, and highest educational attainment
• Disability
• Physical impairment
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor, roof and walls of the house, and ownership of various durable goods (these items are used as proxy indicators of the household's socioeconomic status)
• Weight, height, hemoglobin and malaria measurement for children age 0-5
• Weight, height, hemoglobin measurement for women age 15-49
INDIVIDUAL WOMAN
• Respondent background characteristics
• Reproduction, including a complete birth and death history of respondents' live births and information on abortion
• Contraception
• Pregnancy, postnatal care, and women's nutrition
• Immunization, health, children's nutrition, and early childhood development
• Marriage and sexual activity
• Fertility preferences
• Husbands' background and women's work
• HIV/AIDS and other sexually transmitted infections
• Other health issues
• Maternal mortality
• Domestic violence
INDIVIDUAL MAN
• Respondent background characteristics
• Reproduction
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• HIV/AIDS
• Other health issues
MICRONUTRIENT
• Micronutrient for children age 6-59 months
• Micronutrient for women age 14-49
Coverage
Geographic Coverage
National
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Institute of Statistics (NIS) | Ministry of Planning, Royal Government of Cambodia |
| Directorate General for Health (DGH) | Ministry of Health, Royal Government of Cambodia |
Producers
| Name | Role |
|---|---|
| ICF International | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Royal Government of Cambodia | GovKHM | Funded the study |
| United States Agency for International Development | USAID | Funded the study |
| Australian Department of Foreign Affairs and Trade | DFAT | Funded the study |
| United Nations Population Fund | UNFPA | Funded the study |
| United Nations Children’s Fund | UNICEF | Funded the study |
| Japan International Cooperation Agency | JICA | Funded the study |
| Korean International Cooperation Agency | KOICA | Funded the study |
| Health Sector Support Program—Second Phase | HSSP-2 | Funded the study |
Sampling
Sampling Procedure
The 2014 CDHS sample is a nationally representative sample of women and men between age 15 and 49 who completed interviews. To achieve a balance between the ability to provide estimates at the subnational level 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 Meanchey, Kampong Cham, Kampong Chhnang, Kampong Speu, Kampong Thom, Kandal, Kratie, Phnom Penh, Prey Veng, Pursat, Siem Reap, Svay Rieng, Takeo, and Otdar Meanchey
• Five groups of provinces: Battambang and Pailin, Kampot and Kep, Preah Sihanouk and Koh Kong, Preah Vihear and Stung Treng, and Mondul Kiri and Ratanak Kiri
The sample of households was allocated to the sampling domains in such a way that estimates of indicators could be produced with precision at the national level, as well as separately for urban and rural areas of the country and for each of the 19 sampling domains.
The sampling frame used for the 2014 CDHS was derived from the list of all enumeration areas (EAs) created for the 2008 Cambodia General Population Census (GPC), provided by NIS. The list had been updated in 2012, and it excluded 241 EAs that are special settlement areas and not ordinary residential areas. It included 28,455 EAs for the entire country. The GPC also created maps that delimited the boundaries of each EA. Overall, 4,245 EAs were designated as urban and 24,210 as rural, with an average size of 99 households per EA.
The survey used 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 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 before sample selection and by using a probability proportional to size selection strategy at the first stage of selection.
For further details on sample selection, see Appendix A of the final report.
• Fourteen individual provinces: Banteay Meanchey, Kampong Cham, Kampong Chhnang, Kampong Speu, Kampong Thom, Kandal, Kratie, Phnom Penh, Prey Veng, Pursat, Siem Reap, Svay Rieng, Takeo, and Otdar Meanchey
• Five groups of provinces: Battambang and Pailin, Kampot and Kep, Preah Sihanouk and Koh Kong, Preah Vihear and Stung Treng, and Mondul Kiri and Ratanak Kiri
The sample of households was allocated to the sampling domains in such a way that estimates of indicators could be produced with precision at the national level, as well as separately for urban and rural areas of the country and for each of the 19 sampling domains.
The sampling frame used for the 2014 CDHS was derived from the list of all enumeration areas (EAs) created for the 2008 Cambodia General Population Census (GPC), provided by NIS. The list had been updated in 2012, and it excluded 241 EAs that are special settlement areas and not ordinary residential areas. It included 28,455 EAs for the entire country. The GPC also created maps that delimited the boundaries of each EA. Overall, 4,245 EAs were designated as urban and 24,210 as rural, with an average size of 99 households per EA.
The survey used 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 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 before sample selection and by using a probability proportional to size selection strategy at the first stage of selection.
For further details on sample selection, see Appendix A of the final report.
Response Rate
All of the 611 clusters selected for the sample were surveyed in the 2014 CDHS. A total of 16,356 households were selected, of which 15,937 were found to be occupied during data collection. Among these households, 15,825 completed the Household Questionnaire, yielding a response rate of 99 percent.
In these interviewed households, 18,012 women were identified as eligible for the individual interview. Interviews were completed with 98 percent of these women. Of the 5,484 eligible men identified in every third household, 95 percent were successfully interviewed. There was little variation in response rates by urban-rural residence.
In these interviewed households, 18,012 women were identified as eligible for the individual interview. Interviews were completed with 98 percent of these women. Of the 5,484 eligible men identified in every third household, 95 percent were successfully interviewed. There was little variation in response rates by urban-rural residence.
Weighting
Due to the nonproportional allocation of the sample to the different domains and to urban and rural areas, along with possible differences in response rates, sampling weights are required for any analysis using the 2014 CDHS data to ensure the actual representativeness of the survey results at the national as well as the regional level. Since the 2014 CDHS sample was a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately for each sampling stage and for each cluster.
Sampling weights were adjusted for household nonresponse as well as for individual nonresponse in order to calculate the survey weights. A spreadsheet containing all sampling parameters and selection probabilities was prepared to facilitate the calculation of survey weights. Several sets of survey weights were calculated:
• one set for all households and for women’s individual surveys
• one set for households selected for the male survey and for men’s individual surveys
• one set for women selected for the domestic violence survey
• one set for households in the clusters selected for the micronutrient survey
The differences between the household weights and the individual weights are due to individual nonresponse. The domestic violence survey weight takes the number of eligible women in the household into account because of the selection of only one woman per household. The final survey weights were normalized so that the total number of weighted cases was equal to the total number of unweighted cases at the national level, for both household weights and individual women’s and men’s weights. The normalized weights are relative weights that are valid for estimating means, proportions, and ratios but are not valid for estimating population totals or pooled data.
Sampling weights were adjusted for household nonresponse as well as for individual nonresponse in order to calculate the survey weights. A spreadsheet containing all sampling parameters and selection probabilities was prepared to facilitate the calculation of survey weights. Several sets of survey weights were calculated:
• one set for all households and for women’s individual surveys
• one set for households selected for the male survey and for men’s individual surveys
• one set for women selected for the domestic violence survey
• one set for households in the clusters selected for the micronutrient survey
The differences between the household weights and the individual weights are due to individual nonresponse. The domestic violence survey weight takes the number of eligible women in the household into account because of the selection of only one woman per household. The final survey weights were normalized so that the total number of weighted cases was equal to the total number of unweighted cases at the national level, for both household weights and individual women’s and men’s weights. The normalized weights are relative weights that are valid for estimating means, proportions, and ratios but are not valid for estimating population totals or pooled data.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2014-06 | 2014-12 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
TRAINING AND FIELDWORK
The goal of training was to create 19 field teams capable of collecting data for the 2014 CDHS. Each team was responsible for data collection in one of the 19 survey domains (comprising the 23 provinces and the capital city of Phnom Penh). Field teams were composed of five people (5 teams) or six people (14 teams): a team leader, a field editor, two or three female interviewers, and one male interviewer. Nineteen fully staffed field teams would require 114 field personnel, and at the end of training 109 field personnel were retained. Twenty-six days of training included four days of field practice in Kandal province. Data processing personnel (3 data processing supervisors, 10 office editors/coders, 19 data entry operators, and 5 reserves) also attended classroom training.
Training began with the Household Questionnaire and was followed by the Woman’s Questionnaire. Additional time was spent reviewing the Household Questionnaire, including consent statements for hemoglobin testing, and conversion of ages and dates of birth from the Khmer calendar to the Gregorian calendar. One week was devoted to additional activities, including the Man’s Questionnaire, measurement of women’s and children’s height and weight, sample implementation and household selection, testing of household salt for iodine, and organization of documents and materials for return to the head office. After completion of training, including field practice, fieldwork was launched and teams disbursed to their assigned provinces.
During the training period, the 19 CDHS team leaders were provided with the cluster information for the provinces in which they would be working so that they could devise a data collection sequence for their sample points. Team leaders were best equipped to perform this task because they hailed from their own provinces. They also conducted the CDHS household listing operation (described in Appendix A) and therefore were well acquainted with the areas in which they would be working. The progression of fieldwork by geographic location had to take into account weather conditions during the rainy season.
Fieldwork supervision was carried out regularly by three CDHS survey coordinators from NIS and MOH along with an ICF Macro consultant. Supervision visits were conducted throughout the six months of data collection and included retrieval of questionnaires from the field. In addition, a quality control program was run by the data processing team to detect key data collection errors for each team. These data checks were used to provide regular feedback to each team based on its specific performance. Data collection was conducted from June 2 to December 12, 2014.
The training and fieldwork for collection of stool, urine, and venous blood samples were conducted separately by UNICEF in collaboration with the Institut de Recherche pour le Développement (France) and Cambodia’s Ministry of Agriculture, Forestry, and Fisheries. Details are provided in the micronutrient chapter.
The goal of training was to create 19 field teams capable of collecting data for the 2014 CDHS. Each team was responsible for data collection in one of the 19 survey domains (comprising the 23 provinces and the capital city of Phnom Penh). Field teams were composed of five people (5 teams) or six people (14 teams): a team leader, a field editor, two or three female interviewers, and one male interviewer. Nineteen fully staffed field teams would require 114 field personnel, and at the end of training 109 field personnel were retained. Twenty-six days of training included four days of field practice in Kandal province. Data processing personnel (3 data processing supervisors, 10 office editors/coders, 19 data entry operators, and 5 reserves) also attended classroom training.
Training began with the Household Questionnaire and was followed by the Woman’s Questionnaire. Additional time was spent reviewing the Household Questionnaire, including consent statements for hemoglobin testing, and conversion of ages and dates of birth from the Khmer calendar to the Gregorian calendar. One week was devoted to additional activities, including the Man’s Questionnaire, measurement of women’s and children’s height and weight, sample implementation and household selection, testing of household salt for iodine, and organization of documents and materials for return to the head office. After completion of training, including field practice, fieldwork was launched and teams disbursed to their assigned provinces.
During the training period, the 19 CDHS team leaders were provided with the cluster information for the provinces in which they would be working so that they could devise a data collection sequence for their sample points. Team leaders were best equipped to perform this task because they hailed from their own provinces. They also conducted the CDHS household listing operation (described in Appendix A) and therefore were well acquainted with the areas in which they would be working. The progression of fieldwork by geographic location had to take into account weather conditions during the rainy season.
Fieldwork supervision was carried out regularly by three CDHS survey coordinators from NIS and MOH along with an ICF Macro consultant. Supervision visits were conducted throughout the six months of data collection and included retrieval of questionnaires from the field. In addition, a quality control program was run by the data processing team to detect key data collection errors for each team. These data checks were used to provide regular feedback to each team based on its specific performance. Data collection was conducted from June 2 to December 12, 2014.
The training and fieldwork for collection of stool, urine, and venous blood samples were conducted separately by UNICEF in collaboration with the Institut de Recherche pour le Développement (France) and Cambodia’s Ministry of Agriculture, Forestry, and Fisheries. Details are provided in the micronutrient chapter.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| National Institute of Statistics | NIS | Ministry of Planning, Royal Government of Cambodia |
Questionnaires
Questionnaires
Four questionnaires were used in the 2014 CDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Micronutrient Questionnaire. These questionnaires are based on the questionnaires developed by the worldwide Demographic and Health Surveys (DHS) Program and on the questionnaires used during the 2010 CDHS survey. To reflect relevant population and health issues in Cambodia, the questionnaires were adapted during a series of technical meetings with various stakeholders from government ministries and agencies, nongovernmental organizations, and international donors. The final drafts of the questionnaires were discussed at a stakeholders’ meeting organized by the National Institute of Statistics. The adapted questionnaires were translated from English into Khmer and pretested in February and March 2014.
The Household Questionnaire was used to list all of the usual members and visitors in the selected households. Basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. The Household Questionnaire was also used to identify women and men eligible for an individual interview.
The Woman’s Questionnaire was used to collect information from all women age 15-49 and the Man’s Questionnaire was administered to all men age 15-49 living in one-third of the households in the CDHS sample.
The Micronutrient Questionnaire was implemented in a subsample of one-sixth of the sampled clusters for the collection of micronutrient specimens among eligible women and children. Specimens collected included venous blood, urine, and stool samples.
The Household Questionnaire was used to list all of the usual members and visitors in the selected households. Basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. The Household Questionnaire was also used to identify women and men eligible for an individual interview.
The Woman’s Questionnaire was used to collect information from all women age 15-49 and the Man’s Questionnaire was administered to all men age 15-49 living in one-third of the households in the CDHS sample.
The Micronutrient Questionnaire was implemented in a subsample of one-sixth of the sampled clusters for the collection of micronutrient specimens among eligible women and children. Specimens collected included venous blood, urine, and stool samples.
Data Processing
Data Editing
Completed questionnaires were returned from the field to NIS headquarters, where they were entered and edited by data processing personnel who were specially trained for this task and had also attended questionnaire training of field staff. Data processing personnel included a data processing chief, two assistants, four secondary editors and coordinators, 25 entry operators, and eight office editors.
Data processing for the 2014 CDHS began on 25 personal computers on July 6, 2014, five weeks after the first interviews were conducted. Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during the data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of high quality and to correct areas of needed improvement. Feedback was individually tailored to each team. Data entry, which included 100 percent double entry to minimize keying errors, and data editing were completed on January 8, 2015. Data cleaning and finalization were completed on January 23, 2015.
Data processing for the 2014 CDHS began on 25 personal computers on July 6, 2014, five weeks after the first interviews were conducted. Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during the data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of high quality and to correct areas of needed improvement. Feedback was individually tailored to each team. Data entry, which included 100 percent double entry to minimize keying errors, and data editing were completed on January 8, 2015. Data cleaning and finalization were completed on January 23, 2015.
Data Appraisal
Estimates of Sampling Error
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes 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 2014 Cambodia Demographic and Health Survey (CDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2014 CDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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 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 percent 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 2014 CDHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2014 CDHS is an SAS program. This program 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.
The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.
Note: A more detailed description of estimate of sampling error is presented in APPENDIX B of the survey report.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2014 CDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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 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 percent 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 2014 CDHS sample is the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2014 CDHS is an SAS program. This program 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.
The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.
Note: A more detailed description of estimate of sampling error is 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
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Nutritional status of children based on the NCHS/CDC/WHO International Reference Population
Note: See detailed data quality tables in APPENDIX C of the report.
- Household age distribution
- Age distribution of eligible and interviewed women
- Age distribution of eligible and interviewed men
- Completeness of reporting
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
- Nutritional status of children based on the NCHS/CDC/WHO International Reference Population
Note: See detailed data quality tables in APPENDIX C of the report.
Access policy
Contacts
Access conditions
Request Dataset Access
The following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV).
To request dataset access, you must first be a registered user of the website. You must then create a new research project request. The request must include a project title and a description of the analysis you propose to perform with the data.
The requested data should only be used for the purpose of the research or study. To request the same or different data for another purpose, a new research project request should be submitted. The DHS Program will normally review all data requests within 24 hours (Monday - Friday) and provide notification if access has been granted or additional project information is needed before access can be granted.
DATASET ACCESS APPROVAL PROCESS
Access to DHS, MIS, AIS and SPA survey datasets (Surveys, HIV, and GPS) is requested and granted by country. This means that when approved, full access is granted to all unrestricted survey datasets for that country. Access to HIV and GIS datasets requires an online acknowledgment of the conditions of use.
Required Information
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
Restricted Datasets
A few datasets are restricted and these are noted. Access to restricted datasets is requested online as with other datasets. An additional consent form is required for some datasets, and the form will be emailed to you upon authorization of your account. For other restricted surveys, permission must be granted by the appropriate implementing organizations, before The DHS Program can grant access. You will be emailed the information for contacting the implementing organizations. A few restricted surveys are authorized directly within The DHS Program, upon receipt of an email request.
When The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP.
GPS/HIV Datasets/Other Biomarkers
Because of the sensitive nature of GPS, HIV and other biomarkers datasets, permission to access these datasets requires that you accept a Terms of Use Statement. After selecting GPS/HIV/Other Biomarkers datasets, the user is presented with a consent form which should be signed electronically by entering the password for the user's account.
Dataset Terms of Use
Once downloaded, the datasets must not be passed on to other researchers without the written consent of The DHS Program. All reports and publications based on the requested data must be sent to The DHS Program Data Archive in a Portable Document Format (pdf) or a printed hard copy.
Download Datasets
Datasets are made available for download by survey. You will be presented with a list of surveys for which you have been granted dataset access. After selecting a survey, a list of all available datasets for that survey will be displayed, including all survey, GPS, and HIV data files. However, only data types for which you have been granted access will be accessible. To download, simply click on the files that you wish to download and a "File Download" prompt will guide you through the remaining steps.
The following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV).
To request dataset access, you must first be a registered user of the website. You must then create a new research project request. The request must include a project title and a description of the analysis you propose to perform with the data.
The requested data should only be used for the purpose of the research or study. To request the same or different data for another purpose, a new research project request should be submitted. The DHS Program will normally review all data requests within 24 hours (Monday - Friday) and provide notification if access has been granted or additional project information is needed before access can be granted.
DATASET ACCESS APPROVAL PROCESS
Access to DHS, MIS, AIS and SPA survey datasets (Surveys, HIV, and GPS) is requested and granted by country. This means that when approved, full access is granted to all unrestricted survey datasets for that country. Access to HIV and GIS datasets requires an online acknowledgment of the conditions of use.
Required Information
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
Restricted Datasets
A few datasets are restricted and these are noted. Access to restricted datasets is requested online as with other datasets. An additional consent form is required for some datasets, and the form will be emailed to you upon authorization of your account. For other restricted surveys, permission must be granted by the appropriate implementing organizations, before The DHS Program can grant access. You will be emailed the information for contacting the implementing organizations. A few restricted surveys are authorized directly within The DHS Program, upon receipt of an email request.
When The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP.
GPS/HIV Datasets/Other Biomarkers
Because of the sensitive nature of GPS, HIV and other biomarkers datasets, permission to access these datasets requires that you accept a Terms of Use Statement. After selecting GPS/HIV/Other Biomarkers datasets, the user is presented with a consent form which should be signed electronically by entering the password for the user's account.
Dataset Terms of Use
Once downloaded, the datasets must not be passed on to other researchers without the written consent of The DHS Program. All reports and publications based on the requested data must be sent to The DHS Program Data Archive in a Portable Document Format (pdf) or a printed hard copy.
Download Datasets
Datasets are made available for download by survey. You will be presented with a list of surveys for which you have been granted dataset access. After selecting a survey, a list of all available datasets for that survey will be displayed, including all survey, GPS, and HIV data files. However, only data types for which you have been granted access will be accessible. To download, simply click on the files that you wish to download and a "File Download" prompt will guide you through the remaining steps.
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Access authority
| Name | URL | |
|---|---|---|
| The DHS Program | archive@dhsprogram.com | Link |
Location of Data Collection
The DHS Program
Archive where study is originally stored
The DHS Program
http://dhsprogram.com/data/available-datasets.cfm
Cost: None
http://dhsprogram.com/data/available-datasets.cfm
Cost: None
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Metadata production
DDI Document ID
DDI_KHM_2014_DHS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2015-11-06
DDI Document version
Version 01 (November 2015). Metadata is excerpted from "Cambodia Demographic and Health Survey 2014" Report.