18 datasets found
  1. w

    National Demographic and Health Survey 2022 - Philippines

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jun 7, 2023
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    Philippine Statistics Authority (PSA) (2023). National Demographic and Health Survey 2022 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/5846
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    Dataset updated
    Jun 7, 2023
    Dataset authored and provided by
    Philippine Statistics Authority (PSA)
    Time period covered
    2022
    Area covered
    Philippines
    Description

    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.

  2. Total population of the Philippines 2030

    • statista.com
    • ai-chatbox.pro
    Updated May 6, 2025
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    Statista (2025). Total population of the Philippines 2030 [Dataset]. https://www.statista.com/statistics/578726/total-population-of-philippines/
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    Dataset updated
    May 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    In 2024, the total population of the Philippines was at approximately 114.17 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.

  3. Population Philippines 2020, by region

    • statista.com
    • ai-chatbox.pro
    Updated Nov 22, 2023
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    Statista (2023). Population Philippines 2020, by region [Dataset]. https://www.statista.com/statistics/1173624/philippines-population-by-region/
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    Dataset updated
    Nov 22, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    As of May 2020, Region 4-A had the largest population in the Philippines, with approximately 16.2 million inhabitants living in the region. The region is part of the Island of Luzon along with regions one, two, three, 4-B, five, the Cordillera Administrative Region (CAR), and the National Capital Region (NCR).

  4. d

    Data from: Spatio-temporal analysis of remotely sensed forest loss data in...

    • datadryad.org
    • search.dataone.org
    • +1more
    zip
    Updated Nov 2, 2021
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    Bernard Peter Daipan; Franco Jenner (2021). Spatio-temporal analysis of remotely sensed forest loss data in the Cordillera Administrative Region, Philippines [Dataset]. http://doi.org/10.5061/dryad.v41ns1rvb
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    zipAvailable download formats
    Dataset updated
    Nov 2, 2021
    Dataset provided by
    Dryad
    Authors
    Bernard Peter Daipan; Franco Jenner
    Time period covered
    2021
    Area covered
    Cordillera Administrative Region, Philippines
    Description

    The Hansen Global Forest Change version 1.7 datasets generated during and/or analysed during the current study are available in the earth engine partner’s website repository http://earthenginepartners.appspot.com/science-2013-global-forest. The datasets were developed by Hansen et al. (2013) in their paper "High-resolution global maps of 21st-century forest cover change". Science, 342 (6160), 850-853. https://doi.org/10.1126/science.1244693

    The census of population in the Philippines, including the project populations, used in this study can be retrieved from the Philippine Statistics Authority (PSA) website https://psa.gov.ph/statistics/census/projected-population

    The datasets were processed using an open source GIS software (QGIS version 3.16 Hannover) which can be downloaded from the QGIS website https://www.qgis.org/en/site/.

  5. Children as a percentage of the population Philippines 2015-2024

    • statista.com
    • ai-chatbox.pro
    Updated Jun 25, 2025
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    Statista (2025). Children as a percentage of the population Philippines 2015-2024 [Dataset]. https://www.statista.com/statistics/678279/philippines-children-as-a-percentage-of-the-population/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    In 2024, children below 15 years old accounted for **** percent of the total population in the Philippines. The population share of children in the country has been declining over the past decade.

  6. i

    National Demographic and Health Survey 2017 - Philippines

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Mar 29, 2019
    + more versions
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    Philippines Statistics Authority (PSA) (2019). National Demographic and Health Survey 2017 - Philippines [Dataset]. https://catalog.ihsn.org/index.php/catalog/7779
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    Philippines Statistics Authority (PSA)
    Time period covered
    2017
    Area covered
    Philippines
    Description

    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.

  7. Philippines - Subnational Administrative Boundaries

    • data.amerigeoss.org
    emf, geodatabase +4
    Updated Jan 4, 2022
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    UN Humanitarian Data Exchange (2022). Philippines - Subnational Administrative Boundaries [Dataset]. https://data.amerigeoss.org/fi/dataset/philippines-administrative-levels-0-to-3
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    geoservice, pdf(259640), xlsx(2751328), geodatabase(345969786), emf(1020569), shp(149832100), shp(850666253), xlsx(202257), geodatabase(59501273)Available download formats
    Dataset updated
    Jan 4, 2022
    Dataset provided by
    United Nationshttp://un.org/
    Area covered
    Philippines
    Description

    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)

    The original datasets were 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.

    Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.

    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.

    For administrative level 4 (Barangay) please contact the contributor (OCHA Philippines) via the 'Contact the contributor' button near the top of this page.

    These shapefiles are suitable for database or ArcGIS joins to the Philippines - Subnational Population Statistics.

  8. i

    Census of Population 2015 - Philippines

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    Updated Oct 10, 2017
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    Philippine Statistics Authority (2017). Census of Population 2015 - Philippines [Dataset]. https://catalog.ihsn.org/catalog/7186
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    Dataset updated
    Oct 10, 2017
    Dataset authored and provided by
    Philippine Statistics Authority
    Time period covered
    2015
    Area covered
    Philippines
    Description

    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

  9. Household population share with religious affiliation Philippines 2020, by...

    • statista.com
    • ai-chatbox.pro
    Updated Feb 22, 2024
    + more versions
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    Statista (2024). Household population share with religious affiliation Philippines 2020, by type [Dataset]. https://www.statista.com/statistics/1452406/philippines-household-population-with-religious-affiliation-by-type/
    Explore at:
    Dataset updated
    Feb 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    Philippines
    Description

    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.

  10. W

    Philippines administrative level 0 (country), 1 (region), 2 (province), and...

    • cloud.csiss.gmu.edu
    • data.wu.ac.at
    csv, kml, kmz +3
    Updated Jun 18, 2019
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    UN Humanitarian Data Exchange (2019). Philippines administrative level 0 (country), 1 (region), 2 (province), and 3 (municipality) boundaries, points, and lines, shapefiles and live services [Dataset]. http://cloud.csiss.gmu.edu/dataset/caf116df-f984-4deb-85ca-41b349d3f313
    Explore at:
    zipped shapefile(204037), zipped shapefile(145720425), zipped shapefile(140313868), zipped shapefile(141598788), live service, kmz(77928), kml(129671719), xlsx(188322), zipped shapefile(149538908), kmz(139845073), kmz(374), zipped shapefile(139335705), csv(154689), kmz(378), kmz(380)Available download formats
    Dataset updated
    Jun 18, 2019
    Dataset provided by
    UN Humanitarian Data Exchange
    Area covered
    Philippines
    Description

    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.

  11. i

    National Demographic and Health Survey 2013 - Philippines

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Jul 6, 2017
    + more versions
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    National Statistics Office (NSO) (2017). National Demographic and Health Survey 2013 - Philippines [Dataset]. https://catalog.ihsn.org/index.php/catalog/5449
    Explore at:
    Dataset updated
    Jul 6, 2017
    Dataset authored and provided by
    National Statistics Office (NSO)
    Time period covered
    2013
    Area covered
    Philippines
    Description

    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.

  12. T

    Philippines Unemployment Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 7, 2025
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    TRADING ECONOMICS (2025). Philippines Unemployment Rate [Dataset]. https://tradingeconomics.com/philippines/unemployment-rate
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    json, excel, xml, csvAvailable download formats
    Dataset updated
    May 7, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 31, 1986 - Apr 30, 2025
    Area covered
    Philippines
    Description

    Unemployment Rate in Philippines increased to 4.10 percent in April from 3.90 percent in March of 2025. This dataset provides - Philippines Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  13. i

    Labor Force Survey 2016 - Philippines

    • catalog.ihsn.org
    Updated Sep 19, 2018
    + more versions
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    Philippine Statistics Authority (PSA) (2018). Labor Force Survey 2016 - Philippines [Dataset]. https://catalog.ihsn.org/catalog/7417
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    Dataset updated
    Sep 19, 2018
    Dataset authored and provided by
    Philippine Statistics Authority (PSA)
    Time period covered
    2016
    Area covered
    Philippines
    Description

    Abstract

    The Labor Force Survey (LFS) is a nationwide survey of households conducted quarterly to gather data on the demographic and socio-economic characteristics of the population. It is primarily geared towards the estimation of the levels of employment and unemployment in the country. One of the objectives of the Labor Force Survey is to provide a quantitative framework for the preparation of plans and formulation of policies affecting the labor market. Specifically, the survey is designed to provide statistics on levels and trends of employment, unemployment and underemployment of the country, as a whole, and for the 17 administrative regions.

    A total national sample of 42,768 sample housholds (rounds with Batanes sample) or 42,576 sample households (rounds without Batanes sample) will be alloted per survey round deemed sufficient to provide more precise and reliable estimates at the national and regional levels only.

    The survey involves the collection of data on demographic and socio-economic characteristics of the population in general. The reporting unit is the household which means that statistics emanating from this survey refers to the characteristics of the population residing in private households. Persons who belongs to the institutional population are not within the scope of the survey.

    Geographic coverage

    The sample was selected to allow separate estimates for the national level, and regional levels only (17 administrative regions).

    National Capital Region (NCR) Cordillera Administrative Region (CAR) Region I - Ilocos Region Region II - Cagayan Valley Region III - Central Luzon Region IV-A - CALABARZON Region IV-B - MIMAROPA Region V - Bicol Region Region VI - Western Visayas Region VII - Central Visayas Region VIII - Eastern Visayas Region IX - Zamboanga Peninsula Region X - Northern Mindanao Region XI - Davao Region Region XII - SOCCSKSARGEN Caraga Autonomous Region in Muslim Mindanao (ARMM)

    Analysis unit

    Individual or Person Persons 15 years old and over

    Universe

    The survey covered all household members of the sample households.

    Considered as members of a household are:

    a. Persons who are present at the time of visit, whose usual place of residence is the sample household regardless of their length of stay in the household;

    b. Persons who are present at the time of visit, whose usual place of residence is outside the sample household but have stayed temporarily with the sample household, for at least 30 days;

    c. Persons who are present at the time of visit, whose usual place of residence is outside the sample household but have stayed with the sample household even for less than 30 days, provided that they have been away from their usual place of residence for 30 days or more;

    d. Persons who are not present at the time of visit, but are expected to return within 30 days from date of departure to their usual place of residence, which is the sample household; and

    e. The following family members who are away at the time of visit:

     1 . Overseas contract workers (OCWs);
    
     2. Other overseas Filipino workers who have been away for not more than five years from the date of departure, and are expected to be back within five years from the date of last departure;
    
     3. Employees in Philippine embassies, consulates and other missions; and
    
     4. Students abroad/tourists who have been away for one year or less and are expected to be back within a year from the date of departure. This category also includes those attending training abroad, medical treatment and missionaries.
    

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The 2013 Master Sample for household-based survey:

    In order to be more effecient in the conduct of household based-surveys, the PSA designed a master sample consists of randomly assigned and selected set of geographic areas with non-overlapping and discernable boundaries known as the primary sampling units (PSUs). The primary sampling unit (PSU) can be (1) the whole barangay, or (2) a portion of a large barangay, or (3) combinations of small barangays.

    Provinces and Highly Urbanized Ciities as Sampling Domain

    To provide sub-national or provincial level statistics with precise estimates the 2013 MS has 117 major domains as follows: 81 provinces (including the newly created province Davao Occidental); 33 highly urbanized cities (HUC) (including 16 citiies in the National Capital Region; and 3 other areas (Pateros, Isabela City, and Cotabato City).

    Primary Sampling Units

    In the 2013 MS design each sampling diomain(i.e., province/HUC is divided into exhaustive and non-overlapping area segments known as Primary Sampling Units (PSUs) with about 100 to 400 households. Thus, a PSU can be a barangay/Enumeration Area (EA) or a portion of a large barangay or two or more adjacent small barangays/EAs. The PSUs are then ordered according to the following: (1) North-South/West-East Geographic location; (2)decreasing proporion of households with overseas workers; and (3) decreasing wealth index.

    Replicates

    From the ordered list of PSUs, all possible systematic samples of 6 PSUs will be drawn to form a replicate for the most of the province domain i.e., 75 out of 81 provinces while all possible systemmatic sample of 8 PSUs will be drawn to form a replicate for most of the HUCs, i.e., 31 of 33 HUCs. Small province domains such as Guimaras, Siquijor, Camiguin, Apayao, and Dinagat Isalnds will have 3 PSUs per replicate. Batanes with very less PSUs formed will have 3 PSUs per replicate but will be covered twice a year only (i.e., January and July rounds only). For other HUCs, San Juan City and Lucena City will have 3 and 5 PSUs per replicate, while the other urban areas, Pateros, and City of Isabela will also have 3 PSUs per replicate while Cotabato City will be allocated with 5 PSUs per replicate.

    For instance, in Cagayan with 1008 PSUs formed, a total 1008/6 = 168 possible systematic samples of size 6 or 168 R groups or replicates can be made. The 168 replicates formed are then sorted at random so that the first 4 replicates will be in the first round, next 4 in the second round, and so on.

    Sample Allocation Scheme

    For each domain, a total of 4 sample replicates will be allotted for each survey round. However, the total number of sample SSUs will be alloted proportionately to the measure of size of the PSU. Thus, a PSU with only 100 households would have less number of samples households than PSUs with 400 households but on the average there will be 12 sample households allotted for each PSU in HUCs and an average of 16 sample households alloted for every PSUs in province domains.

    A total national sample of 42,768 sample households (rounds with Batanes sample) or 42,576 sample households (rounds without Batanes sample) will be allotted per survey round.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    ISH FORM 2 (LFS questionnaire) is a four-page, forty three-column questionnaire that is being used in the quarterly rounds of the Labor Force Survey nationwide. This questionnaire gathers data on the demographic and economic characteristics of the population.

    On the first page of the questionnaire, the particulars about the geographic location, design codes and household auxiliary information of the sample household that is being interviewed are to be recorded. Certifications by the enumerator and his supervisor regarding the manner by which the data are collected are likewise to be made on this page.

    The inside pages of the questionnaire contain the items to be determined about each member of the sample household. Columns 2 to 10 are for the demographic characteristics; columns 2 to 5A are to be ascertained of all members of the household regardless of age. Columns 6 to 7 are asked for members 5 years old and over, while column 8 is asked for members 5 to 24 years old, column 9 to 10, for 15 years old and over, while columns 11 to 15 are asked for members 5 years old and over. Columns 18 to 42 on the other hand, are the series of items that will be asked of all the members 15 years old and over to determine their labor force and employment characteristics.

    Other Relevant Information: The question on hunger experienced by any member of the family because they did not have food to eat, was asked to the head of the household. If in question A, the answer is Yes the frequency of experiencing hunger was asked in question B.

    Most of the questions have pre-coded responses. The possible answers with their corresponding codes are printed at the bottom of the page for easy reference. Only the appropriate codes need to be entered in the cells.

    Other items, however, require write-in entries such as column 14 (primary occupation) and column 16 (kind of business/industry), etc. For such items, it is required that the enumerator describes the primary occupation or kind of business/industry.

    The ISH Form 2 is provided as Technical Documents.

    Cleaning operations

    Data Processing

    Verification and review of questionnaires

    The SRs were expected to have verified the completeness of the questionnaires, correctness of the entries, consistency of the entries in the different related items, and the correctness of the codes that were entered in the boxes before the questionnaires were submitted to the Assistant Provincial Supervisor or the Provincial Supervisor. Use the list of sample barangays/EAs provided for coding the region, provinces, municipalities and barangays.

    The Assistant Provincial Supervisor or the Provincial Supervisor. upon receipt of the questionnaires reviewed the forms and code the responses for occupation

  14. Average size of households Philippines 2000-2020

    • statista.com
    • ai-chatbox.pro
    Updated Nov 22, 2023
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    Statista (2023). Average size of households Philippines 2000-2020 [Dataset]. https://www.statista.com/statistics/1298672/philippines-average-household-size/
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    Dataset updated
    Nov 22, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    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.

  15. f

    Definitions of the variables used to test the hypothesis that human...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Eugenio Fonzi; Yukiko Higa; Arlene G. Bertuso; Kyoko Futami; Noboru Minakawa (2023). Definitions of the variables used to test the hypothesis that human transportation influences population structure of Ae. aegypti in the central-western Philippines. [Dataset]. http://doi.org/10.1371/journal.pntd.0003829.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS Neglected Tropical Diseases
    Authors
    Eugenio Fonzi; Yukiko Higa; Arlene G. Bertuso; Kyoko Futami; Noboru Minakawa
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Philippines
    Description

    1Originally single data for a single port, then transformed to pairwise using the formula a+b where a and b are single values for each port.2Calculated from satellite images using the "ruler" function of Google Earth.3Official data from the Philippine Statistics Authority—National Statistics Office (http://web0.psa.gov.ph/).4Official data from the Philippine Ports Authority (http://www.pdosoluz.com.ph/).Definitions of the variables used to test the hypothesis that human transportation influences population structure of Ae. aegypti in the central-western Philippines.

  16. Leading causes of death Philippines 2024, by disease

    • statista.com
    • ai-chatbox.pro
    Updated May 21, 2025
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    Statista (2025). Leading causes of death Philippines 2024, by disease [Dataset]. https://www.statista.com/statistics/1120528/philippines-leading-causes-mortality-by-disease/
    Explore at:
    Dataset updated
    May 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2024 - Sep 2024
    Area covered
    Philippines
    Description

    Preliminary figures between January to September 2024 indicated that ischaemic heart disease was the leading cause of death in the Philippines. The number of people who died from this illness was estimated at 75,500. Following this, cancer resulted in the deaths of about 43,000 people. Eating habits Heart diseases have been linked to high meat consumption, among others. In the Philippines, pork has been the most consumed meat type, followed closely by chicken. While pork meat is typically produced domestically, the country also imports pork to supplement its supply. However, plant-based food has started gaining popularity among Filipinos. In fact, a 2024 survey revealed that 69 percent of surveyed Filipinos consumed plant-based products, including meat alternatives. Common diseases in the Philippines Aside from heart and cerebrovascular diseases, the Filipino population is also exposed to infections, diabetes, skin diseases, and illnesses resulting from high meat consumption. In 2020, over 700,000 Filipinos contracted acute respiratory tract infections, followed by over 400,000 diagnosed with hypertension. In areas with high exposure to rain, dengue infections and leptospirosis have also become prevalent.

  17. Number of deployed overseas Filipino workers 2012-2024

    • statista.com
    • ai-chatbox.pro
    Updated May 20, 2025
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    Statista (2025). Number of deployed overseas Filipino workers 2012-2024 [Dataset]. https://www.statista.com/statistics/1243681/philippines-deployed-overseas-workers/
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    Dataset updated
    May 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    In 2024, preliminary figures recorded about **** million Filipinos leaving the Philippines to work overseas — a number higher than the previous year's estimates. The number of deployed overseas Filipino workers (OFWs) significantly plummeted between 2020 and 2021 due to the COVID-19 pandemic. Leading occupation of deployed OFWs  Among the newly hired land-based overseas Filipino workers in 2023, about ******* of them were domestic cleaners and helpers, followed by domestic housekeepers. Filipino domestic cleaners and housekeepers have been in demand in several countries, particularly in the Middle East and Hong Kong. These countries usually offer higher wages and better employment benefits for such jobs, in comparison to employers in the Philippines. Increasing demand for healthcare workers  Aside from domestic cleaners and housekeepers, recent years reflected a growing demand for healthcare workers, especially since the onset of the COVID-19 pandemic. In 2020, Saudi Arabia was the leading destination of deployed Filipino nurses, followed by the United Kingdom and Germany.

  18. Sheep production volume Philippines 2012-2021

    • statista.com
    Updated Feb 6, 2024
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    Statista (2024). Sheep production volume Philippines 2012-2021 [Dataset]. https://www.statista.com/statistics/661324/philippines-sheep-production/
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    Dataset updated
    Feb 6, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    The production volume of sheep in the Philippines has consistently been three thousand heads since 2012. Meanwhile, sheep meat consumption per capita was estimated to also be compatible, with slight forecast growth until 2031.

  19. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Philippine Statistics Authority (PSA) (2023). National Demographic and Health Survey 2022 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/5846

National Demographic and Health Survey 2022 - Philippines

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Dataset updated
Jun 7, 2023
Dataset authored and provided by
Philippine Statistics Authority (PSA)
Time period covered
2022
Area covered
Philippines
Description

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.

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