Data Source: U.S. Census Bureau, American Community Survey (ACS) 5-year Estimates Special Tabulation on Aging and Disability 2016-2020.
*Note. The total population only includes individuals for whom the poverty status is determined, excluding institutionalized group quarter populations (e.g., college dormitories, military housing).

Abstract

The 2022 Philippines National Demographic and Health Survey (NDHS) was implemented by the Philippine Statistics Authority (PSA). Data collection took place from May 2 to June 22, 2022.

The primary objective of the 2022 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, fertility preferences, family planning practices, childhood mortality, maternal and child health, nutrition, knowledge and attitudes regarding HIV/AIDS, violence against women, child discipline, early childhood development, and other health issues.

The information collected through the NDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The 2022 NDHS also provides indicators anchored to the attainment of the Sustainable Development Goals (SDGs) and the new Philippine Development Plan for 2023 to 2028.

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the 2022 NDHS was based on a two-stage stratified sample design using the Master Sample Frame (MSF) designed and compiled by the PSA. The MSF was constructed based on the listing of households from the 2010 Census of Population and Housing and updated based on the listing of households from the 2015 Census of Population. The first stage involved a systematic selection of 1,247 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

In the second stage, an equal take of either 22 or 29 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the preselected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

All women age 15–49 who were either usual residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on women’s safety.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two questionnaires were used for the 2022 NDHS: the Household Questionnaire and the Woman’s Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, academe, and international agencies. The survey protocol was reviewed by the ICF Institutional Review Board.

After all questionnaires were finalized in English, they were translated into six major languages: Tagalog, Cebuano, Ilocano, Bikol, Hiligaynon, and Waray. The Household and Woman’s Questionnaires were programmed into tablet computers to allow for computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the languages for each questionnaire.

Cleaning operations

Processing the 2022 NDHS data began almost as soon as fieldwork started, and data security procedures were in place in accordance with confidentiality of information as provided by Philippine laws. As data collection was completed in each PSU or cluster, all electronic data files were transferred securely via SyncCloud to a server maintained by the PSA Central Office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the area of assignment. Timely generation of field check tables allowed for effective monitoring of fieldwork, including tracking questionnaire completion rates. Only the field teams, project managers, and NDHS supervisors in the provincial, regional, and central offices were given access to the CAPI system and the SyncCloud server.

A team of secondary editors in the PSA Central Office carried out secondary editing, which involved resolving inconsistencies and recoding “other” responses; the former was conducted during data collection, and the latter was conducted following the completion of the fieldwork. Data editing was performed using the CSPro software package. The secondary editing of the data was completed in August 2022. The final cleaning of the data set was carried out by data processing specialists from The DHS Program in September 2022.

Response rate

A total of 35,470 households were selected for the 2022 NDHS sample, of which 30,621 were found to be occupied. Of the occupied households, 30,372 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 28,379 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 27,821 women, yielding a response rate of 98%.

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 the results of mistakes made in implementing data collection and in 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 2022 Philippines National Demographic and Health Survey (2022 NDHS) 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 2022 NDHS 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% 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 2022 NDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. 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 displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Population pyramid
• Five-year mortality rates

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

Data Source: U.S. Census Bureau, American Community Survey (ACS) 5-year Estimates 2016-2020 .
*Note. The total population refers to households with at least one person aged 60 years and over.

Abstract

The 2017 Philippines National Demographic and Health Survey (NDHS 2017) is a nationwide survey with a nationally representative sample of approximately 30,832 housing units. The primary objective of the survey is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS 2017 collected information on marriage, fertility levels, fertility preferences, awareness and use of family planning methods, breastfeeding, maternal and child health, child mortality, awareness and behavior regarding HIV/AIDS, women’s empowerment, domestic violence, and other health-related issues such as smoking.

The information collected through the NDHS 2017 is intended to assist policymakers and program managers in the Department of Health (DOH) and other organizations in designing and evaluating programs and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents) and all women age 15-49 years resident in the sample household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the NDHS 2017 is based on a two-stage stratified sample design using the Master Sample Frame (MSF), designed and compiled by the PSA. The MSF is constructed based on the results of the 2010 Census of Population and Housing and updated based on the 2015 Census of Population. The first stage involved a systematic selection of 1,250 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

In the second stage, an equal take of either 20 or 26 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the pre-selected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on domestic violence.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two questionnaires were used for the NDHS 2017: the Household Questionnaire and the Woman’s Questionnaire. Both questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, universities, and international agencies.

Cleaning operations

The processing of the NDHS 2017 data began almost as soon as fieldwork started. As data collection was completed in each PSU, all electronic data files were transferred via an Internet file streaming system (IFSS) to the PSA central office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the PSU. Secondary editing involved resolving inconsistencies and the coding of openended questions; the former was carried out in the central office by a senior data processor, while the latter was taken on by regional coordinators and central office staff during a 5-day workshop following the completion of the fieldwork. Data editing was carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage, because it maximized the likelihood of the data being error-free and accurate. Timely generation of field check tables allowed for more effective monitoring. The secondary editing of the data was completed by November 2017. The final cleaning of the data set was carried out by data processing specialists from The DHS Program by the end of December 2017.

Response rate

A total of 31,791 households were selected for the sample, of which 27,855 were occupied. Of the occupied households, 27,496 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 25,690 women age 15-49 were identified for individual interviews; interviews were completed with 25,074 women, yielding a response rate of 98%.

The household response rate is slightly lower in urban areas than in rural areas (98% and 99%, respectively); however, there is no difference by urban-rural residence in response rates among women (98% for each).

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and 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 Philippines National Demographic and Health Survey (NDHS) 2017 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 NDHS 2017 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 among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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 NDHS 2017 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. 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 final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

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

Data Source: U.S. Census Bureau, American Community Survey (ACS) 5-year Estimates Special Tabulation on Aging and Disability 2016-2020.
*Note. People who are actively working or are not currently working but have recently and would like to work are considered in the labor force. Those who have never worked or are retired are not in the labor force.

These datasets are derived from the boundaries of the Barangays as observed at the end of April 2016 as per the Philippine Geographic Standard Code (PSGC) dataset. It has been generated on the basis of the layer created by the Philippine Statistics Authority (PSA) in the context of the 2015 population census. These datasets have been vetted by staff at The Carl Vinson Institute of Government's Office of Information Technology Outreach Services (ITOS) according to their COD assessment protocol found in the COD Technical Support Package (https://sites.google.com/site/commonoperationaldataset/geodata-preparation-manual/itos-process).
Acknowledge PSA and NAMRIA as the sources. LMB is still the source of official administrative boundaries of the Philippines. In the absence of available official administrative boundary, the IMTWG have agreed to clean and use the PSA administrative boundaries which are used to facilitate data collection of surveys and censuses. The dataset can only be considered as indicative boundaries and not official. * For administrative level 4 (Barangay) please contact the contributor (OCHA Philippines) via this page. This COD replaces https://data.humdata.org/dataset/philippines-administrative-boundaries

Philippines administrative levels:

(0) Country

(1) Region (Filipino: rehiyon)

(2) Provinces (Filipino: lalawigan, probinsiya) and independent cities (Filipino: lungsod, siyudad/ciudad, dakbayan, lakanbalen)

(3) Municipalities (Filipino: bayan, balen, bungto, banwa, ili) and component cities (Filipino: lungsod, siyudad/ciudad, dakbayan, dakbanwa, lakanbalen)

These shapefiles are suitable for database or ArcGIS joins to the sex and age disaggregated population statistics found on HDX here.

The Census 2000: Special Tabulation on Aging provides information for each of the 50 states along with the District of Columbia and Puerto Rico with a special focus on persons age 60 and older. Population topics (Tables P001 through P116 for each state and state equivalent file) include basic population totals, age, sex, race, Hispanic or Latino origin, households and families, group quarters, marital status, grandparents as caregivers, ability to speak English, place of birth, citizenship status, migration, educational attainment, veteran status, disability, employment status, income, and poverty status. Household topics (tables H01 through H69) include tenure (owner occupied or renter occupied), household size, units in structure, year structure was built, availability of plumbing and kitchen facilities, and whether meals are included in the rent and value of home. Both the population and housing subjects may be cross tabulated. Files are organized according to the ten regions as defined by the Administration on Aging. Each table provides information at a number of geographical levels: United States (50 states + DC), state, Planning and Service Area (PSA -- the geographic area served by a single area agency on aging), county, county subdivision in 12 states with a population of 2,500 or more, places with a population of 2,500 or more, and census tract, as well as American Indian and Alaska Native areas. Also, the urban and rural components of states and PSAs are shown. The data are in the form of Excel tables. The technical documentation provides extensive details about such topics as the tabulation specifications, the geographical levels shown, how to use the statistical tables, and the measures used to protect confidentiality.

Figures are calculated as those achieving at least 5 GCSE grades A*-C (or equivalent) divided by the number of all 16 year old pupils (those pupils on the school roll at the time of the Annual School Census each year, who were aged 15 at the start of that academic year), expressed as a percentage at both national and school level. Education plays a number of roles in influencing inequalities in health, if health is viewed in its widest sense. Firstly, it has an important role in influencing inequalities in socioeconomic position. Educational qualifications are a determinant of an individual's labour market position, which in turn influences income, housing and other material resources. These are related to health and health inequalities. As a consequence, education is a traditional route out of poverty for those living in disadvantage. The roles of education set out above imply a range of outcomes which are not readily measurable. However, inequality is observed when looking at educational achievement. Children from disadvantaged backgrounds, as measured by being in receipt of free school meals, have lower educational achievement than other children. This indicator relates to the Public Service Agreement (PSA) performance management framework 2008-2011, as follows: • PSA Delivery Agreement 10 Indicator 4 Increase the proportion achieving 5 A*-C GCSEs (or equivalent) including GCSEs in both English and Maths at KS4 to 53% by 2011 (baseline 2006 of 46%); • PSA Delivery Agreement 11 Indicator 2 Decrease the achievement gap between pupils eligible for free school meals and their peers achieving the expected level at key stages 2 and 4. Legacy unique identifier: P01092

Abstract

Philippines Population Census 2015 was designed to take an inventory of the total population in the country and collect information about its characteristics. The census of population is the source of information on the size, distribution, and composition of the population in each barangay, city/municipality, province, and region in the country, as well as information about its demographic, social, and economic characteristics. These indicators are vital in the formulation of rational plans and programs towards national and local development.

Specifically, POPCEN 2015 gathered data on: - size and geographic distribution of the population; - population composition in terms of age, sex, and marital status; - religious affiliation; - school attendance, literacy, highest grade/year completed, and technical/vocational course obtained; - usual activity/occupation, and whether overseas worker for members 15 years old and over; - registration of birth and death; - household-level characteristics such as fuel used for lighting and source of water supply for drinking and cooking; - housing characteristics such as the type of building, construction materials of the roof of the building, construction materials of the outer walls of the building/housing unit, and tenure status of the housing unit/lot; and - barangay characteristics such as the presence of selected facilities and establishments; and presence of informal settlers, relocation areas, and in-movers in the barangay due to natural and man-made disasters.

August 1, 2015 was designated as Census Day for the POPCEN 2015, on which date the enumeration of the population in the Philippines was referred. For the purpose of this census, all information collected about the population were as of 12:01 a.m., Saturday, August 1, 2015.

Enumeration lasted for about 25 days, from 10 August to 6 September 2015. In some areas, enumeration was extended until 15 September 2015 for large provinces.

Geographic coverage

The population count is available at the barangay, city/municipal, provincial, regional, and national levels. Demographic, social, and economic characteristics are tabulated at the city/municipal, provincial, regional, and national levels.

Analysis unit

The following are the units of analysis in POPCEN 2015: 1. Individual person 2. Household 3. Housing unit 4. Institutional Population 5. Barangay

Universe

The POPCEN 2015 covered all persons who were alive as of 12:01 a.m. August 1, 2015, and who were members of the household and institution as follows:

Persons Enumerated as Members of the Household:

1. Those who were present at the time of visit and whose usual place of residence was the housing unit where the household lived;

2. Family members who were overseas workers and who were away at the time of the census and were expected to be back within five years from the date of last departure. These included household members who may or may not have had a specific work contract or had been presently at home on vacation but had an existing overseas employment to return to. Undocumented overseas workers were still considered as members of the household for as long as they had been away for not more than five years. Immigrants, however, were excluded from the census.

3. Those whose usual place of residence was the place where the household lived but were temporarily away at the time of the census for any of the following reasons: a. on vacation, business/pleasure trip, or training somewhere in the Philippines and was expected to be back within six months from the date of departure. An example was a person on training with the Armed Forces of the Philippines for not more than six months; b. on vacation, business/pleasure trip, on study/training abroad and was expected to be back within a year from the date of departure; c. working or attending school outside their usual place of residence but usually came home at least once a week; d. confined in hospitals for a period of not more than six months as of the time of enumeration, except when they were confined as patients in mental hospitals, leprosaria/leper colonies or drug rehabilitation centers, regardless of the duration of their confinement; e. detained in national/provincial/city/municipal jails or in military camps for a period of not more than six months as of the time of enumeration, except when their sentence or detentionwas expected to exceed six months; f. on board coastal, interisland, or fishing vessels within Philippine territories; and g. on board oceangoing vessels but expected to be back within five years from the date of departure.

4. Boarders/lodgers of the household or employees of household-operated businesses who did not return/go home to their respective households weekly;

5. Citizens of foreign countries who resided or were expected to reside in the Philippines for at least a year from their arrival, except members of diplomatic missions and non-Filipino members of international organizations;

6. Filipino balikbayans with usual place of residence in a foreign country but resided or were expected to reside in the Philippines for at least a year from their arrival; and

7. Persons temporarily staying with the household who had no usual place of residence or who were not certain to be enumerated elsewhere.

Persons Enumerated as Members of the Institutional Population:

1. Permanent lodgers in boarding houses;

2. Dormitory residents who did not usually go home to their respective households at least once a week;

3. Hotel residents who stayed in the hotel for more than six months at the time of the census;

4. Boarders in residential houses, provided that their number was 10 or more. However, if the number of boarders in a house was less than 10, they were considered as members of regular households, not of institutions;

5. Patients in hospitals who were confined for more than six months;

6. Patients confined in mental hospitals, leprosaria or leper colonies, and drug rehabilitation centers, regardless of the length of their confinement;

7. Wards in orphanages, homes for the aged, and other welfare institutions;

8. Prisoners of corrective and penal institutions;

9. Seminarians, nuns in convents, monks, and postulants;

10. Soldiers residing in military camps; and

11. Workers in mining and similar camps.

All Filipinos in Philippine embassies, missions, and consulates abroad were also included in the enumeration.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The POPCEN 2015 is a complete enumeration of all persons, households and institutional population in the country. No sampling was done.

Mode of data collection

Face-to-face interview [f2f] and self-administered; Paper and Pencil

Research instrument

Listed below are the basic census forms that were used during the field enumeration:

• CP Form 1 - Listing Booklet This booklet was used to list the buildings, housing units, households, and ILQs within an EA. It was also used to record other information such as the address of the household head or ILQ, total population, and number of males and females corresponding to each household and ILQ listed.

• CP Form 2 - Household Questionnaire This four-page questionnaire was used to record information about the households. Specifically, this form was used to gather information on selected demographic and socio-economic characteristics of the population and some information on housing characteristics.

• CP Form 4 - Institutional Population Questionnaire This four-page questionnaire was used to record information on selected demographic and socio-economic characteristics of the population residing in ILQs.

• CP Form 5 - Barangay Schedule This four-page questionnaire was used to record the physical characteristics (e.g. street pattern) and the presence of service facilities and establishments by kind and emplyment size in the barangay. It was also used to record the presence of informal settlers, relocation areas, and in-movers in the barangay due to natural and man-made disasters.

• CP Form 7 - Household Self-Administered Questionnaire Instructions This form contains specific and detailed instructions on how to fill out/accomplish each item in CP Form 2. It was used as guide/reference by respondents who were not, for some reasons, personally interviewed by the EN.

• CP Form 8 - Institutional Population Self-Administered Questionnaire Instructions This form contains specific and detailed instructions for the managers/administrators to guide them in accomplishing each item in CP Form 4. It was used as guide/reference by managers or administrators of an ILQ.

Listed below are the major administrative and accomplishment forms that were also used to facilitate data collection and supervision, and monitoring of enumeration and personnel:

• Mapping Form This form was used to plot buildings, either occupied by households or vacant, ILQs and important physical landmarks in the area. It was also used to enlarge a map or a block of an EA/barangay if the area being enumerated is too large or congested. CP Form 1 - Listing Booklet

• CP Form 6 - Notice of Listing/Enumeration This form is a sticker. After listing and interviewing a household or ILQ, this sticker was posted in a very conspicuous place, preferably in front of the house or at the gate of the building. This form was used for control and monitoring purposes as its presence indicates that a particular housing unit or ILQ had already been listed/interviewed.

• CP Form 9 - Appointment Slip to the Household/Institution/Barangay Official This form was used to set an appointment with the

Philippines administrative level 0-4 boundaries (COD-AB) dataset.

The date that these administrative boundaries were established is unknown.

NOTE: See COD-PS caveat about treatment of National Capital (Manila) data. OCHA acknowledges PSA and the National Mapping and Resource Information Authority (NAMRIA) as the sources. LMB is the source of official administrative boundaries of the Philippines. In the absence of available official administrative boundary, the IMTWG have agreed to clean and use the PSA administrative boundaries which are used to facilitate data collection of surveys and censuses. The dataset can only be considered as indicative boundaries and not official. Its updated to reflect the new areas within BARMM; It uses the new 10-digit pcode consistent with government PSGC as of 2023

This COD-AB was most recently reviewed for accuracy and necessary changes in April 2024. The COD-AB does not require any update.

Sourced from National Mapping and Resource Information Authority (NAMRIA), Philippines Statistics Authority (PSA)

Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID.

This COD-AB is suitable for database or GIS linkage to the Philippines COD-PS.

As this is an island country, no edge-matched (COD-EM) version of this COD-AB is required.

Please see the COD Portal.

Administrative level 1 contains 17 feature(s). The normal administrative level 1 feature type is ""currently not known"".

Administrative level 2 contains 88 feature(s). The normal administrative level 2 feature type is ""currently not known"".

Administrative level 3 contains 1,642 feature(s). The normal administrative level 3 feature type is ""currently not known"".

Administrative level 4 contains 42,048 feature(s). The normal administrative level 4 feature type is ""currently not known"".

Recommended cartographic projection: Asia South Albers Equal Area Conic

This metadata was last updated on January 13, 2025.

Patient demographics and clinical characteristics at the time of diagnosis.

Chart and table of Philippines population from 1950 to 2025. United Nations projections are also included through the year 2100.

Based on the 2020 census, the majority of Filipino households were affiliated with the Roman Catholic religion, accounting for about 79 percent. Meanwhile, the share of the Muslim population was 6.4 percent. The Philippines is one of the countries in the world with the highest population professing the Catholic faith, after Brazil and Mexico.

According to the 2020 population census, the average size of households in the Philippines was 4.1. This was lower than the average household size in 2015 which was 4.4. Overall, the average size of households in the country had been declining.

Demographics for study participants with and without prostate cancer.

Abstract

The Palay Production Survey is one of the two modules of the Palay and Corn Production Survey (PCPS), formerly known as the Rice and Corn Production Survey (RCPS). The Palay Production Survey (PPS) 2016 is a quarterly survey conducted by the Philippine Statistics Authority (PSA). It aims to generate estimates on palay production, area and yield and other related information at the provincial level. The four rounds are conducted in January, April, July and October. Each round generates estimates for the immediate past quarter and forecasts for the next two quarters. Results of the survey serve as inputs to planners and policy makers on matters concerning the rice industry.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

Farming households in palay producing barangays.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling procedure used in the Palay Production Survey 2016 (PPS 2016) is first implemented in 1994. This is a replicated two-stage stratified sampling design with province as the domain, barangay as the Primary Sampling Unit (PSU) and farming household as the Secondary Sampling Unit (SSU).

The results of the 1991 Census of Agriculture and Fisheries (CAF 1991) serve as sampling frame at the PSU and SSU levels. In the said census, the largest barangay in a municipality is taken with certainty while a 50 percent sampling rate is used for selecting the remaining barangays in the municipality. This scheme effectively resulted in the generation of two sub-universes: a sub universe of barangays with probability of selection equal to one (these barangays are called 'certainty barangays') and another sub-universe of barangays with probability of selection equal to 0.5. This characteristic of the CAF 1991 data is used in the selection of sample barangays for the PPS.

The barangays are arrayed in ascending order based on palay area which are stratified such that the aggregate palay area of the barangays belonging to one stratum is more or less equal to the aggregate palay area of the barangays in any other stratum. Ten strata are formed for major palay producing provinces and five for minor producing provinces. In all these provinces, the last stratum consisted of the certainty barangays per CAF 1991 design.

For each stratum, four (4) sample barangays are drawn independently using probability proportional to size (pps) sampling with the barangay's palay area as size measure. This resulted with four (4) independent sets of barangays (i.e., four replicates) for the province. Systematic sampling is used in drawing the sample farming households in each sample barangay.

For economic reasons, sample size per barangay is limited to a minimum of four (4) and a maximum of twenty-five (25). To correct for this limitation of the design, the use of household weights is instituted. A detailed discussion of weighting in the PPS is included in the survey's estimation procedure attached as a technical document.

In November 2007, an updating of the list of farming households in all palay sample barangays nationwide is done to address the problem of non-response due to transfer of residence, stoppage of farm operation, passing away of operator etc. Consequently, a new set of sample households is drawn.

Respondents who refused to be interviewed, not a home, unknown and transferred to another barangay are treated as missing and are replaced at the Central Office for the next quarter's survey. The replacement samples are taken from the list of replacements (farming households) for the barangay and are reflected in the list of sample households for the next round.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Prior to data encoding, the accomplished survey returns are manually edited and coded. Manual editing is checking of responses to the Palay Production Survey (PPS) questionnaire in terms of acceptability and validity. This activity aims at improving the quality of data collected by the SRs. It involves the checking of data items based on criteria like completeness of data, consistency with other data items and data ranges. Coding is the assignment of alpha-numeric codes to questionnaire items to facilitate encoding.

Encoded data are subjected to computerized editing using a customized editing program. The editing program take into consideration the validation criteria such as validity, completeness and consistency with other data items. This activity is done to capture invalid entries that were overlooked during manual editing. An error listing is produced as output of the process. The errors reflected in said lists are verified vis-à-vis the questionnaires. The data files are updated based on the corrections made. Editing and updating are performed iteratively until a clean, error-free data file is generated.

Completeness check is done to compare the data file against a master file of barangays to check if the sample barangays have been completely surveyed or not. This activity is done after a clean, error-free data file is generated.

Response rate

PPS 2016 registered response rates which averaged 85.0% across its quarterly surveys - April 2016 Round, July 2016 Round, October 2016 Round and January 2017 Round.

Abstract

The 2013 NDHS is designed to provide information on fertility, family planning, and health in the country for use by the government in monitoring the progress of its programs on population, family planning and health.

In particular, the 2013 NDHS has the following specific objectives: • Collect data which will allow the estimation of demographic rates, particularly fertility rates and under-five mortality rates by urban-rural residence and region. • Analyze the direct and indirect factors which determine the level and patterns of fertility. • Measure the level of contraceptive knowledge and practice by method, urban-rural residence, and region. • Collect data on health, immunizations, prenatal and postnatal check-ups, assistance at delivery, breastfeeding, and prevalence and treatment of diarrhea, fever and acute respiratory infections among children below five years old. • Collect data on environmental health, utilization of health facilities, health care financing, prevalence of common non-communicable and infectious diseases, and membership in the National Health Insurance Program (PhilHealth). • Collect data on awareness of cancer, heart disease, diabetes, dengue fever and tuberculosis. • Determine the knowledge of women about AIDS, and the extent of misconception on HIV transmission and access to HIV testing. • Determine the extent of violence against women.

Geographic coverage

National coverage

Analysis unit

• Household
• Individuals/ persons
• Woman age 15 to 49

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample selection methodology for the 2013 NDHS is based on a stratified two-stage sample design, using the 2010 Census of Population and Housing (CPH) as a frame. The first stage involved a systematic selection of 800 sample enumeration areas (EAs) distributed by stratum (region, urban/rural). In the second stage, 20 sample housing units were selected from each sample EA, using systematic random sampling.

All households in the sampled housing units were interviewed. An EA is defined as an area with discern able boundaries consisting of contiguous households. The sample was designed to provide data representative of the country and its 17 administrative regions.

Further details on the sample design and implementation are given in Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2013 NDHS used three questionnaires: Household Questionnaire, Individual Woman’s Questionnaire, and Women’s Safety Module. The development of these questionnaires resulted from the solicited comments and suggestions during the deliberation in the consultative meetings and separate meetings conducted with the various agencies/organizations namely: PSA-NSO, POPCOM, DOH, FNRI, ICF International, NEDA, PCW, PhilHealth, PIDS, PLCPD, UNFPA, USAID, UPPI, UPSE, and WHO. The three questionnaires were translated from English into six major languages - Tagalog, Cebuano, Ilocano, Bicol, Hiligaynon, and Waray.

The main purpose of the Household Questionnaire was to identify female members of the sample household who were eligible for interview with the Individual Woman’s Questionnaire and the Women’s Safety Module.

The Individual Woman’s Questionnaire was used to collect information from all women aged 15-49 years.

The Women’s Safety Module was used to collect information on domestic violence in the country, its prevalence, severity and frequency from only one selected respondent from among all the eligible women who were identified from the Household Questionnaire.

Cleaning operations

All completed questionnaires and the control forms were returned to the PSA-NSO central office in Manila for data processing, which consisted of manual editing, data entry and verification, and editing of computer-identified errors. An ad-hoc group of thirteen regular employees from the DSSD, the Information Resources Department (IRD), and the Information Technology Operations Division (ITOD) of the NSO was created to work fulltime and oversee data processing operation in the NDHS Data Processing Center that was carried out at the NSO-CVEA Building in Quezon City, Philippines. This group was responsible for the different aspects of NDHS data processing. There were 19 data encoders hired to process the data who underwent training on September 12-13, 2013.

Data entry started on September 16, 2013. The computer package program called Census and Survey Processing System (CSPro) was used for data entry, editing, and verification. Mr. Alexander Izmukhambetov, a data processing specialist from ICF International, spent two weeks at NSO in September 2013 to finalize the data entry program. Data processing was completed on December 6, 2013.

Response rate

For the 2013 NDHS sample, 16,732 households were selected, of which 14,893 were occupied. Of these households, 14,804 were successfully interviewed, yielding a household response rate of 99.4 percent. The household response rates in urban and rural areas are almost identical.

Among the households interviewed, 16,437 women were identified as eligible respondents, and the interviews were completed for 16,155 women, yielding a response rate of 98.3 percent. On the other hand, for the women’s safety module, from a total of 11,373 eligible women, 10,963 were interviewed with privacy, translating to a 96.4 percent response rate. At the individual level, urban and rural response rates showed no difference. The principal reason for non-response among women was the failure to find individuals at home, despite interviewers’ repeated visits to the household.

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 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 2013 National Demographic and Health Survey (NDHS) 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 2013 NDHS 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 error is a measure of the variability between the results of all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey data.

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 2013 NDHS 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 2013 NDHS is a SAS program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replications 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 weighted cases in the group or subgroup under consideration.

Further details on sampling errors calculation are given in Appendix B of the final report.

Data appraisal

Data quality tables were produced to review the quality of the data: - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

Note: The tables are presented in APPENDIX C of the final report.

In 2023, the total population of the Philippines was at approximately 111.91 million inhabitants. For the foreseeable future, the Filipino population is expected to increase slightly, despite a current overall downward trend in population growth. The dwindling Filipino population For now, the population figures in the Philippines still show a steady increase and the country is still one of the most densely populated countries in the Asia-Pacific region, however, all signs point to a decline in the number of inhabitants in the long run: Just like the population growth rate, the country’s fertility rate, for example, has also been decreasing for years now, while the death rate has been increasing simultaneously.   Poor healthcare to blame One of the reasons for the downward trend is the aging population; fewer babies are born each year, while life expectancy at birth has been steady over the years. Another reason is poor healthcare in the country: The Philippines have a high tuberculosis incidence rate, a highly infectious disease, and are among the countries with a high probability of death from noncommunicable diseases as well.

Abstract

The Labor Turnover Survey (LTS) aims to generate quarterly data on labor turnover (accession and separation rates) as indicators of labor market activity in large business enterprises.

The information gathered in this survey is intended to generate timely labor market signals as sound basis in planning, policy formulation and decision making in goverment, business and industry.

Geographic coverage

National capital region

Analysis unit

Enterprise

Universe

The sampling frame for the 2016 LTS is an integrated list from enterprises culled from the 2015 List of Establishments in the NCR prepared by the Philippine Statistics Authority (PSA) and the updated sampling frames of LTS 2014 and LTS 2015. This comprises 16,194 business firms/enterprises with an employment size of at least 20.

Kind of data

Sample survey data [ssd]

Sampling procedure

The enterprise is the unit of enumeration in the LTS and it has for its sampling domain the eighteen (18) major industry groups (1-digit) based on the 2009 PSIC. The survey covered business enterprises located in the National Capital Region (NCR) to provide a quick and timely assessment of the labor market activity through a sample survey with manageable sample size given the limited budget. NCR accounts for one-third of the country's gross domestic product and about two-thirds of the total large business enterprises in the Philippines.

The sampling frame for the 2016 LTS is an integrated list from enterprises culled from the 2015 List of Establishment in the NCR prepared by the Philippine Statistics Authority (PSA) in coordination with Service and Industry Census Division (SICD) the updated sampling frames of LTS 2014 and LTS 2015. This comprises 16,194 business firms/enterprises with an employment size of at least 20. This list was obtained and updated prior to the conduct of LTS for the first quarter of 2016. The updated frame was used in the sample size determination and sample selection for the first quarter survey round. The same sample size was retained in all quarters of the year.

After each survey round, all enterprises that responded are automatically considered as samples for the next survey rounds. To fill up the lack in the computed sample size, samples will be drawn by industry from the updated sampling frame. In cases where there are no enterprises to sample in some industries, the total number of samples needed for these industries will be allocated proportionally to other industries with available samples.

The sample enterprises in each domain were drawn through simple random sampling.

Sampling deviation

Replacement of sample enterprise is done when the sampled enterprise falls in one of the following situation during the field operation: (1) cannot be located; (2) refuse to answer; (3) temporarily closed; (4) duplicate of another sample enterprise; (5) permanently closed; or (6) on strike.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire contained the following information:

1. Name and Address of Enterprise

2. Main Economic Activity and Major Products/Goods or Services

3. Item of Information

I. Employment A. Total Employment ( Month 1. Month 2, Month 3)

II. Labor Turnover A. Total Accessions (New Hires) 1. Expansion 2. Replacement

B. Total Separation 1. Employee-initiated 2. Employer-initiated

III. Agency-hired Workers

IV. Existing Job Vacancies

1. Certification of Respondents

2. Survey Personnel

Response rate

1st Qtr - 96.59 % 2nd Qtr - 98.22 % 3rd Qtr - 97.33 % 4th Qtr - 100.00 %