8 datasets found
  1. Population in Metro Manila Philippines 2020, by city and municipality

    • statista.com
    Updated Jul 15, 2023
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    Statista (2023). Population in Metro Manila Philippines 2020, by city and municipality [Dataset]. https://www.statista.com/statistics/1424101/population-in-ncr-by-city-philippines/
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    Dataset updated
    Jul 15, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    Philippines
    Description

    Based on the 2020 census, Quezon City was the most populous city in Metro Manila in the Philippines, with about 2.96 million inhabitants. The capital city of Manila, on the other hand, registered about 1.85 million people in the same year. In contrast, the municipality of Pateros, which is the only remaining municipality in the region, had a population of about 65 thousand.

  2. i

    National Demographic and Health Survey 2022 - Philippines

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Jun 7, 2023
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    Philippine Statistics Authority (PSA) (2023). National Demographic and Health Survey 2022 - Philippines [Dataset]. https://catalog.ihsn.org/catalog/11340
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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.

  3. Nurse to population ratio Philippines 2024, by region

    • statista.com
    Updated Jul 30, 2025
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    Statista (2025). Nurse to population ratio Philippines 2024, by region [Dataset]. https://www.statista.com/statistics/1122083/philippines-number-of-nurses/
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    Dataset updated
    Jul 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Philippines
    Description

    In 2024, one public health nurse was serving ***** people in the Philippines. Across regions, Central Luzon registered the highest nurse-to-population ratio at *****. In contrast, there were ***** patients for every nurse in the MIMAROPA region.

  4. Most vote-rich cities Philippines 2022

    • statista.com
    Updated Aug 8, 2025
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    Statista (2025). Most vote-rich cities Philippines 2022 [Dataset]. https://www.statista.com/statistics/1308079/philippines-most-vote-rich-cities/
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    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Philippines
    Description

    For the 2022 national elections, Quezon City was the most vote-rich city in the Philippines, accounting for the highest number of registered voters at *** million. This was followed by Manila and Davao with **** million and around *** million voters, respectively.

  5. i

    Family Income and Expenditure Survey 1994 - Philippines

    • catalog.ihsn.org
    • dev.ihsn.org
    • +1more
    Updated Mar 29, 2019
    + more versions
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    National Statistics Office (2019). Family Income and Expenditure Survey 1994 - Philippines [Dataset]. https://catalog.ihsn.org/catalog/3700
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Statistics Office
    Time period covered
    1994 - 1995
    Area covered
    Philippines
    Description

    Abstract

    The 1994 Family Income and Expenditure Survey (FIES) is a nationwide survey of households undertaken by the National Statistics Office (NSO). Similar surveys were conducted in 1956-1957, 1961, 1965, 1971, 1975, 1979, 1985 and 1988. Like the previous surveys, this undertaking aims to accomplish the following primary objectives:

    1. to gather data on family income and family living expenditures and related information affecting income and expenditure levels and patterns in the Philippines;

    2. to determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families;

    3. to provide benchmark information to update weights for the estimation of consumer price index (CPI)

    Geographic coverage

    National coverage

    Analysis unit

    Household Consumption expenditure item Income by source

    Universe

    The 1994 FIES has as its target population, all households and members of households nationwide. Institutional population is not within the scope of the survey.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling design of the 1994 FIES adopts that of the Integrated Survey of Households (ISH), which uses a stratified two-stage cluster sampling design. It is prepared by the National Economic and Development Authority (NEDA) Technical Committee on Survey Design and first implemented in 1984. It is the same sampling design used in the ISH modules starting in 1986.

    The urban and rural areas of each province are the principal domains of the survey. In addition, the urban and rural areas of cities with a population of 150,000 or more as of 1990 are also made domains of the survey with rural and urban dimensions. These include the four cities and five municipalities of Metro Manila (Manila, Quezon City, Pasay and Caloocan; Valenzuela, Parañaque, Pasig, Marikina and Makati), and other key cities such as Baguio, Angeles, Cabanatuan, Olongapo, Batangas, Lipa, Lucena, San Pablo, Bacolod, Iloilo, Cebu, Mandaue, Zamboanga, Butuan, Cagayan de Oro, Davao, General Santos, and Iligan and key municipalities such as San Fernando, Pampanga and Tarlac, Tarlac.

    Sampling Units and Sampling Frame The primary sampling units (PSUs) under the sample design are the barangays and the households within each sample barangay comprise the secondary sampling units (SSUs).

    The frame from which the sample barangays are drawn is obtained from the 1990 Census of Population and Housing (CPH). Hence, all the approximately 40,000 barangays covered in the 1990 CPH are part of the primary sampling frame.

    The sampling frame for the SSUs, that is, the households, is prepared by listing all households in each of the selected sample barangays. The listing operation is conducted regularly in the sample barangays to update the secondary sampling frame from where the sample households are selected.

    Sample Size and Sampling Fraction The size of the sample is envisioned to meet the demand for fairly adequate statistics at the domain level. Taking this need into account and considering cost constraints as well, the decision reached is for a national sample of about 26,000 households.

    In general, the sample design results in self-weighting samples within domains, with a uniform sampling fraction of 1:400 for urban and 1:600 for rural areas. However, special areas are assigned different sampling fractions so as to obtain "adequate" samples for each. Special areas refer to the urban and rural areas of a province or large city which are small relative to their counterparts.

    Selection of Samples For the purpose of selecting PSUs, the barangay in each domain are arranged by population size (as of the 1990 Census of Population) in descending order and then grouped into strata of approximately equal sizes. Four independent PSUs are drawn with probability proportional to size with complete replacement.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire has five main parts consisting of the following: Part I. Identification and Other Information (Geographic Identification, Other Information and Particulars about the Family)

    Part II. Expenditures and Other Disbursements Section A. Food, Alcoholic Beverages and Tobacco Section B. Fuel, Light and Water, Transportation and Communication, Household Operations Section C. Personal Care and Effects, Clothing Footwear and Other Wear Section D. Education, Recreation, and Medical Care Section E. Furnishings and Equipment Section F. Taxes Section G. Housing, House Maintenance and Minor Repairs Section H. Miscellaneous Expenditures Section I. Other Disbursements

    Part III. Income Section A. Salaries and Wages from Employment Section B. Net Share of Crops, Fruits and Vegetables Produced and/or Livestock and Poultry Raised by Other Households Section C. Other Sources of Income Section D. Other Receipts Section F. Family Sustenance Activities

    Part IV. Entrepreneurial Activities Section A1. Crop Farming and Gardening Section A2. Livestock and Poultry Raising Section A3. Fishing Section A4. Forestry and Hunting Section A5. Wholesale and Retail Section A6. Manufacturing Section A7. Community, Social, Recreational and Personal Services Section A8. Transportation, Storage and Communication Services Section A9. Mining and Quarrying Section A10. Construction Section A11. Entrepreneurial Activities Not Elsewhere Classified

    Part V: Health - Care Section A. Health - care Expenditures Section B. Health Insurance

    Cleaning operations

    The 1994 FIES questionnaire contains about 800 data items and a guide for comparing income and expenditures and internal consistency.

    Upon submission of the data diskettes containing first and second visit data, a summary file was extracted from the entire file through a computer program.

    The questionnaires were further subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency. Items failing any of the edit checks were either corrected automatically by the computer on the basis of pre-determined specifications or, when needed, examined in a clerical error-reconciliation operation.

    The electronic data-processing (EDP) system developed by the NSO Data Processing Staff and used in the 1985 and 1988 FIES was generally adopted in processing the 1991 FIES with few modifications. There are thirteen (13) major steps in the machine processing of the 1991 FIES and these are as follows: 1. Data entry and verification 2. Structural editing (minor edit) 3. Edit list verification/correction 4. Update 5. Completeness check 6. Completeness check list verification/correction 7. Identification verification 8. Extraction of summary file for preliminary results 9. Matching of visit records (big edit) 10. Internal consistency checks (big edit) 11. Reject lists verification/correction 12. Update 13. Expansion 14. Tabulation 15. Generation of CPI weight tables 16. Variance analysis

    Steps 1 to 8 were performed right after each visit while the remaining steps were carried out upon completion of the data collection for the first and second visits. Steps 1 to 7 were implemented at the regional offices. In addition, except for NCR, Region 3, 6, 7 and the province of Basilan, Sulu, Tawi-tawi and Zamboanga City which were handled by the Central Office. Steps 10 and 11 were likewise undertaken in the regional offices. The first passes of reject listings were sent to the regional offices for verification and correction/updates are sent back to the Central Office for data file updating. Meanwhile, steps 8, 9 and all the concluding steps were handles by the Central Office.

    For data entry, IMPS (Integrated Microcomputer Processing System) was used.

    Response rate

    The response rate is the ratio of the total responding households to the total number of eligible households. Eligible households include households who were completely interviewed, refused to be interviewed or were temporarily away or not at home or on vacation during the survey period.

    Sampling error estimates

    As in all surveys, two types of non-response were encountered in the 1994 FIES: interview non-response and item non-response. Interview non-response refers to a sample household that could not be interviewed. Since the survey requires that the sample households be interviewed in both visits, households that transferred to another dwelling unit, temporarily away, on vacation, not at home, household unit demolished, destroyed by fire/typhoon and refusal to be interviewed in the second visit contributed to the number of interview non-response cases.

    Item non-response, or the failure to obtain responses to particular survey items, resulted from factors such as respondents being unaware of the answer to a particular question, unwilling to provide the requested information or ENs' omission of questions during the interview. Deterministic imputation was done to address item nonresponse. This imputation is a process in which proper entry for a particular missing item was deduced from other items of the questionnaire where the non-response item was observed. Notes and remarks indicated in the questionnaire were likewise used as basis for imputation.

  6. i

    National Demographic and Health Survey 2013 - Philippines

    • catalog.ihsn.org
    • microdata.worldbank.org
    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/catalog/5449
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    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.

  7. Major cases of coronavirus (COVID-19) in the Philippines 2023, by province...

    • statista.com
    Updated Jul 13, 2023
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    Statista (2023). Major cases of coronavirus (COVID-19) in the Philippines 2023, by province or city [Dataset]. https://www.statista.com/statistics/1103623/philippines-coronavirus-covid-19-cases-by-residence/
    Explore at:
    Dataset updated
    Jul 13, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    The coronavirus COVID-19, which originated in Wuhan, China, has spread worldwide. Across the different regions in the world, the number of cases is continuously increasing. As of May 3, 2023, Quezon City reported over 277 thousand cases of COVID-19 – the highest among other cities and provinces in the Philippines.

    Lesser restrictions in major cities Despite having the highest number of COVID-19 cases among cities and provinces nationwide, Quezon City was placed under Alert Level 1 for the month of June 2022 – the lowest alert level status for the pandemic. This meant freer movements across populations and full capacity of most establishments. The alert level status will be updated depending on the possible rise of new cases. The lowering down of restriction level was implemented after the vaccination target of 71 million was met. As of July 2022, over 71 million people have already been fully vaccinated from COVID, with over 15 million having received a booster dose.

    Unmasking
    The possibility of lifting the mandatory wearing of face masks in the country towards the end of 2022 was raised if the government successfully vaccinates 90 million of its 110 million population. In addition, the Philippine government will also start encouraging its population to take the booster shot, in efforts to control the spread of the Omicron subvariant. As of July 2022, the National Capital Region accounted for the highest share of the population with booster shots.

  8. i

    National Demographic and Health Survey 2017 - Philippines

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Mar 29, 2019
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    Philippines Statistics Authority (PSA) (2019). National Demographic and Health Survey 2017 - Philippines [Dataset]. https://catalog.ihsn.org/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.

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Statista (2023). Population in Metro Manila Philippines 2020, by city and municipality [Dataset]. https://www.statista.com/statistics/1424101/population-in-ncr-by-city-philippines/
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Population in Metro Manila Philippines 2020, by city and municipality

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Dataset updated
Jul 15, 2023
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2020
Area covered
Philippines
Description

Based on the 2020 census, Quezon City was the most populous city in Metro Manila in the Philippines, with about 2.96 million inhabitants. The capital city of Manila, on the other hand, registered about 1.85 million people in the same year. In contrast, the municipality of Pateros, which is the only remaining municipality in the region, had a population of about 65 thousand.

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