Philippines Population: NCR: Quezon City data was reported at 2,936.116 Person th in 2015. This records an increase from the previous number of 2,761.720 Person th for 2010. Philippines Population: NCR: Quezon City data is updated yearly, averaging 2,081.625 Person th from Dec 1975 (Median) to 2015, with 8 observations. The data reached an all-time high of 2,936.116 Person th in 2015 and a record low of 956.864 Person th in 1975. Philippines Population: NCR: Quezon City data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G001: Population: Census 2010.

Philippines Population Density: NCR: Quezon City data was reported at 17,099.000 Person/sq km in 2015. This records an increase from the previous number of 16,084.000 Person/sq km for 2010. Philippines Population Density: NCR: Quezon City data is updated yearly, averaging 12,123.000 Person/sq km from Dec 1975 (Median) to 2015, with 8 observations. The data reached an all-time high of 17,099.000 Person/sq km in 2015 and a record low of 5,572.883 Person/sq km in 1975. Philippines Population Density: NCR: Quezon City data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G005: Population Density.

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.

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.

Abstract

The Labor Force Survey is a nationwide survey of households conducted regularly 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 in the country.

The Labor Force Survey aims to provide a quantitative framework for the preparation of plans and formulation of policies affecting the labor market.

Geographic coverage

National coverage, the sample design has been drawn in such a way that accurate lower level classification would be possible. The 74 provinces, 24 cities and eight key municipalities are covered.

Analysis unit

• Person/ individual

Universe

The survey covered all persons 10 years old and over. Persons who reside in institutions are not covered.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the Labor Force Survey adopts that of the Integrated Survey of Households (ISH), which uses a stratified two-stage sampling design. It is prepared by the 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 urban and rural dimensions. These include the four cities and five municipalities of Metro Manila (Manila, Quezon City, Pasay and Caloocan; Valenzuela, Paranaque, 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.

The rest of Metro Manila, i.e., the remaining municipalities are treated as separate domains. In the case of Makati, six exclusive villages are identified and samples are selected using a different scheme. These villages are Forbes Park, Bel-Air, Dasmarinas, San Lorenzo, Urdaneta and Magallanes.

Because of the creation of the Autonomous Region of Muslim Mindanao (ARMM), this, defining its areas of coverage, Marawi City and Cotabato Cfity are likewises treated as domains.

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.

Secondary sampling units are selected systematiclally with a random start.

Sampling deviation

Replacement of non-responding or transferred sample households is allowed although it is still possible to have non-response cases due to critical peace and order situation or inaccessibility of the selected sample households. If there are unenumerated barangays or sample households, non-response adjustments are utilized.

Mode of data collection

Face-to-face [f2f]

Research instrument

The items of information presented in the July 1991 Quarterly Labor Force Survey questionnaire were derived from a structured questionnaire covering the demographic and economic characteristics of individuals. The demographic characteristics include age, sex, relationship to household head, marital status, and highest grade completed. The economic characteristics include employment status, occupation, industry, nomal working hours, total hours worked, class of worker, etc.

Cleaning operations

Data processing involves two stages: manual processing and machine processing. Manual processing refers to the manual editing and coding of questionnaires. This was done prior to machine processing which entailed code validation, consistency checks as well as tabulation.

Enumeration is a very complex operation and may happen that accomplished questionnaires may have some omissions and implausible or inconsistent entries. Editing is meant to correct these errors.

For purposes of operational convenience, field editing was done. The interviewers were required to review the entries at the end of each interview. Blank items, which were applicable to the respondents, were verified and filled out. Before being transmitted to the regional office, all questionnaires were edited in the field offices.

Coding, the transformation of information from the questionnaire to machine readable form, was likewise done in the field offices.

Machine processing involved all operations that were done with the use of a computer and/or its accessories, that is, from data encoding to tabulation. Coded data are usually in such media as tapes and diskettes. Machine editing is preferred to ensure correctness of encoded information. Except for sample completeness check and verification of geographic identification which are the responsibility of the subject matter division, some imputations and corrections of entries are done mechanically.

Response rate

The response rate for January 1992 LFS was 99.94 percent. The non-response rate of 0.06 percent was due to crticial peace and order situation or inaccessibility of the selected sample or sample households.

Sampling error estimates

Standard Error (SE) and Coefficient of Variation (CV) for the selected variables of the Labor Force Survey (LFS) for July 1991 survey round was computed using the statistical package IMPS. The selected variables referred to include the employment, unemployment and labor force population levels and rates.

A sampling error is usually measured in terms of the standard error for a particular statistic. A standard error is a measure of dispersion of an estimate from the expected value.

The SE can be used to calculate confidence intervals within which the true value for the population can be estimated, while the CV is a measure of relative variability that is commonly used to assess the precision of survey estimates.

The CV is defined as the ratio of the standard error and the estimate. An estimate with CV value of less than 10 percent is considered precise.

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.

Abstract

The Labor Force Survey is a nationwide survey of households conducted regularly 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 in the country.

The Labor Force Survey aims to provide a quantitative framework for the preparation of plans and formulation of policies affecting the labor market.

Geographic coverage

National coverage, the sample design has been drawn in such a way that accurate lower level classification would be possible. The 73 provinces, 14 cities of the Philippines are covered.

Analysis unit

• Person/ individual

Universe

The survey covered all persons 10 years old and over. Persons who reside in institutions are not covered.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the Labor Force Survey adopts that of the Integrated Survey of Households (ISH), which uses a stratified two-stage sampling design. It is prepared by the 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 1980 are also made domains of the survey. These cities are the four cities in Metro Manila (Manila, Quezon City, Pasay and Caloocan); and the cities of Angeles, Olongapo,, Bacolod, Iloilo, Cebu, Zamboanga, Butuan, Cagayan de Oro, Davao, and Iligan.

The rest of Metro Manila, i.e., Pasig, Makati and the 11 other municipalities, are treated as three separate domains. In the case of Makati, six exclusive villages are identified and samples are selected using a different scheme. These villages are Forbes Park, Bel-Air, Dasmarinas, San Lorenzo, Urdaneta and Magallanes.

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 1980 Census of Population and Housing (CPH). Hence, all the approximately 40,000 barangays covered in the 1980 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 20,000 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 1980 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.

Secondary sampling units are selected systematiclally with a random start.

Sampling deviation

Replacement of non-responding or transferred sample households is allowed although it is still possible to have non-response cases due to critical peace and order situation or inaccessibility of the selected sample households. If there are unenumerated barangays or sample households, non-response adjustments are utilized.

Mode of data collection

Face-to-face [f2f]

Research instrument

The items of information presented in the April 1991 Quarterly Labor Force Survey questionnaire were derived from a structured questionnaire covering the demographic and economic characteristics of individuals. The demographic characteristics include age, sex, relationship to household head, marital status, and highest grade completed. The economic characteristics include employment status, occupation, industry, nomal working hours, total hours worked, class of worker, etc.

Cleaning operations

Data processing involves two stages: manual processing and machine processing. Manual processing refers to the manual editing and coding of questionnaires. This was done prior to machine processing which entailed code validation, consistency checks as well as tabulation.

Enumeration is a very complex operation and may happen that accomplished questionnaires may have some omissions and implausible or inconsistent entries. Editing is meant to correct these errors.

For purposes of operational convenience, field editing was done. The interviewers were required to review the entries at the end of each interview. Blank items, which were applicable to the respondents, were verified and filled out. Before being transmitted to the regional office, all questionnaires were edited in the field offices.

Coding, the transformation of information from the questionnaire to machine readable form, was likewise done in the field offices.

Machine processing involved all operations that were done with the use of a computer and/or its accessories, that is, from data encoding to tabulation. Coded data are usually in such media as tapes and diskettes. Machine editing is preferred to ensure correctness of encoded information. Except for sample completeness check and verification of geographic identification which are the responsibility of the subject matter division, some imputations and corrections of entries are done mechanically.

Response rate

The response rate for April 1991 LFS was 99.86 percent. The non-response rate of 0.14 percent was due to crticial peace and order situation or inaccessibility of the selected sample or sample households.

Sampling error estimates

Standard Error (SE) and Coefficient of Variation (CV) for the selected variables of the Labor Force Survey (LFS) for April 1991 survey round was computed using the statistical package IMPS. The selected variables referred to include the employment, unemployment and labor force population levels and rates.

A sampling error is usually measured in terms of the standard error for a particular statistic. A standard error is a measure of dispersion of an estimate from the expected value.

The SE can be used to calculate confidence intervals within which the true value for the population can be estimated, while the CV is a measure of relative variability that is commonly used to assess the precision of survey estimates.

The CV is defined as the ratio of the standard error and the estimate. An estimate with CV value of less than 10 percent is considered precise.

人口：人口普查2010：NCR：奎松市在12-01-2015达2,936.116千人，相较于12-01-2010的2,761.720千人有所增长。人口：人口普查2010：NCR：奎松市数据按年更新，12-01-1975至12-01-2015期间平均值为2,081.625千人，共8份观测结果。该数据的历史最高值出现于12-01-2015，达2,936.116千人，而历史最低值则出现于12-01-1975，为956.864千人。CEIC提供的人口：人口普查2010：NCR：奎松市数据处于定期更新的状态，数据来源于Philippine Statistics Authority，数据归类于全球数据库的菲律宾 – 表 PH.G001：人口：人口普查2010。

In 2023, one public health nurse was serving ***** people in the Philippines. Across regions, CALABARZON accounted for the highest nurse-to-population ratio at *****, followed by the Central Luzon Region (Region 3). In contrast, there were ***** people for every nurse in the CAR.

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.

Abstract

The 1991 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 1991 FIES has as its target population, all households and members of households nationwide. A household is defined as an aggregate of persons, generally but not necessarily bound by ties of kinship, who live together under the same roof and eat together or share in common the household food. Household membership comprises the head of the household, relatives living with him such as his/her spouse, children, parent, brother/sister, son-in-law/daughter-in-law, grandson/granddaughter and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

Institutional population is not within the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the 1991 Family Income and Expenditures Survey (FIES) adopts that of the Integrated Survey of Households (ISH), of the National Statistics Office (NSO) which uses a stratified two-stage cluster sampling design with the population size of the barangay as the stratifying variable.

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 1980 are also made domains of the survey. These cities are the 4 cities in Metro Manila (Manila, Quezon City, Pasay and Caloocan), and the cities of Angeles, Olongapo, Bacolod, Iloilo, Cebu, Zamboanga, Butuan, Cagayan de Oro, Davao and IIigan.

The rest of Metro Manila, i.e., Makati, Pasig and the 11 other municipalities are treated as three separate domains. In the case of Makati, six exclusive villages are identified and samples are selected using a different scheme. These villages are Forbes Park, Bel-Air, Dasmarinas, San Lorenzo, Urdaneta and Magallanes.

In general, the sample design results in a self-weighting samples within domains, with a uniform sampling fraction of 1:400 for urban areas and 1:6000 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 or rural areas of a province or large city which are small relative to their counterparts. T

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). For the purpose of selecting the PSUs, the barangay in each domain are arranged by population size (as of the 1980 Census of Population) in descending equal sizes. Four independent PSUs are drawn with probability proportional to size with complete replacement.

Within each PSU selected at the first stage, a pre-determined number of households (i.e. SSU's) is selected at the second stage using a systematic selection procedure with a random start. The number of households chosen from the ith PSU takes into account the probability of selecting the PSU at the first stage such that each household within the domain has the same over-all probability of selection for the survey (i.e. the sample was self-weighting within domains).

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 and Other Receipts Section A. Salaries and Wages from Employment Section B. Net Share of Crops, Fruits and Vegetables Produced or Livestock and Poultry Raised by Other Households Section C. Other Sources of Income Section D. Other Receipts Section E. Check List for 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

Cleaning operations

The 1991 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. This summary file provided the basis for the generation of the preliminary results in August of 1992.

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-reconcillation 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 7. Identification verification 8. Extraction of summary file for preliminary results 9. Matching of visit records (big edit) 10. Expansion 11. Tabulation 12. Generation of CPI weight tables 13. 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 office while the concluding steps were handled 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 1991 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.

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 1.4 million. This was followed by Manila and Davao with 1.13 million and around one million voters, respectively.