Philippines PH: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data was reported at 31.500 % in 2013. This records a decrease from the previous number of 34.900 % for 2011. Philippines PH: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data is updated yearly, averaging 34.200 % from Dec 2003 (Median) to 2013, with 4 observations. The data reached an all-time high of 35.500 % in 2003 and a record low of 31.500 % in 2013. Philippines PH: Prevalence of Stunting: Height for Age: Male: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Prevalence of stunting, male, is the percentage of boys under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

This dataset is about countries in Philippines per year, featuring 4 columns: country, date, death rate, and median age. The preview is ordered by date (descending).

Philippines Population: Female: Age: 15 to 24 Years data was reported at 9,554.000 Person th in Oct 2017. This records a decrease from the previous number of 9,642.000 Person th for Jul 2017. Philippines Population: Female: Age: 15 to 24 Years data is updated quarterly, averaging 9,063.000 Person th from Jul 2004 (Median) to Oct 2017, with 54 observations. The data reached an all-time high of 9,940.000 Person th in Jan 2016 and a record low of 7,916.000 Person th in Jul 2004. Philippines Population: Female: Age: 15 to 24 Years data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G004: Labour Force Survey: Population: Age 15 and Above.

This dataset is about countries in Philippines per year, featuring 4 columns: capital city, country, date, and median age. The preview is ordered by date (descending).

The 1993 National Demographic Survey (NDS) is a nationally representative sample survey of women age 15-49 designed to collect information on fertility; family planning; infant, child and maternal mortality; and maternal and child health. The survey was conducted between April and June 1993. The 1993 NDS was carried out by the National Statistics Office in collaboration with the Department of Health, the University of the Philippines Population Institute, and other agencies concerned with population, health and family planning issues. Funding for the 1993 NDS was provided by the U.S. Agency for International Development through the Demographic and Health Surveys Program. Close to 13,000 households throughout the country were visited during the survey and more than 15,000 women age 15-49 were interviewed. The results show that fertility in the Philippines continues its gradual decline. At current levels, Filipino women will give birth on average to 4.1 children during their reproductive years, 0.2 children less than that recorded in 1988. However, the total fertility rate in the Philippines remains high in comparison to the level achieved in the neighboring Southeast Asian countries. The primary objective of the 1993 NDS is to provide up-to-date inform ation on fertility and mortality levels; nuptiality; fertility preferences; awareness, approval, and use of family planning methods; breastfeeding practices; and maternal and child health. This information is intended to assist policymakers and administrators in evaluating and designing programs and strategies for improving health and family planning services in 'the country. MAIN RESULTS Fertility varies significantly by region and socioeconomic characteristics. Urban women have on average 1.3 children less than rural women, and uneducated women have one child more than women with college education. Women in Bicol have on average 3 more children than women living in Metropolitan Manila. Virtually all women know of a family planning method; the pill, female sterilization, IUD and condom are known to over 90 percent of women. Four in 10 married women are currently using contraception. The most popular method is female sterilization ( 12 percent), followed by the piU (9 percent), and natural family planning and withdrawal, both used by 7 percent of married women. Contraceptive use is highest in Northern Mindanao, Central Visayas and Southern Mindanao, in urban areas, and among women with higher than secondary education. The contraceptive prevalence rate in the Philippines is markedly lower than in the neighboring Southeast Asian countries; the percentage of married women who were using family planning in Thailand was 66 percent in 1987, and 50 percent in Indonesia in 199l. The majority of contraceptive users obtain their methods from a public service provider (70 percent). Government health facilities mainly provide permanent methods, while barangay health stations or health centers are the main sources for the pill, IUD and condom. Although Filipino women already marry at a relatively higher age, they continue to delay the age at which they first married. Half of Filipino women marry at age 21.6. Most women have their first sexual intercourse after marriage. Half of married women say that they want no more children, and 12 percent have been sterilized. An additional 19 percent want to wait at least two years before having another child. Almost two thirds of women in the Philippines express a preference for having 3 or less children. Results from the survey indicate that if all unwanted births were avoided, the total fertility rate would be 2.9 children, which is almost 30 percent less than the observed rate, More than one quarter of married women in the Philippines are not using any contraceptive method, but want to delay their next birth for two years or more (12 percent), or want to stop childbearing (14 percent). If the potential demand for family planning is satisfied, the contraceptive prevalence rate could increase to 69 percent. The demand for stopping childbearing is about twice the level for spacing (45 and 23 percent, respectively). Information on various aspects of maternal and child health-antenatal care, vaccination, breastfeeding and food supplementation, and illness was collected in the 1993 NDS on births in the five years preceding the survey. The findings show that 8 in 10 children under five were bom to mothers who received antenatal care from either midwives or nurses (45 percent) or doctors (38 percent). Delivery by a medical personnel is received by more than half of children born in the five years preceding the survey. However, the majority of deliveries occurred at home. Tetanus, a leading cause of infant deaths, can be prevented by immunization of the mother during pregnancy. In the Philippines, two thirds of bitlhs in the five years preceding the survey were to mothers who received a tetanus toxoid injection during pregnancy. Based on reports of mothers and information obtained from health cards, 90 percent of children aged 12-23 months have received shots of the BCG as well as the first doses of DPT and polio, and 81 percent have received immunization from measles. Immunization coverage declines with doses; the drop out rate is 3 to 5 percent for children receiving the full dose series of DPT and polio. Overall, 7 in 10 children age 12-23 months have received immunization against the six principal childhood diseases-polio, diphtheria, ~rtussis, tetanus, measles and tuberculosis. During the two weeks preceding the survey, 1 in 10 children under 5 had diarrhea. Four in ten of these children were not treated. Among those who were treated, 27 percent were given oral rehydration salts, 36 percent were given recommended home solution or increased fluids. Breasffeeding is less common in the Philippines than in many other developing countries. Overall, a total of 13 percent of children born in the 5 years preceding the survey were not breastfed at all. On the other hand, bottle feeding, a widely discouraged practice, is relatively common in the Philippines. Children are weaned at an early age; one in four children age 2-3 months were exclusively breastfed, and the mean duration of breastfeeding is less than 3 months. Infant and child mortality in the Philippines have declined significantly in the past two decades. For every 1,000 live births, 34 infants died before their first birthday. Childhood mortality varies significantly by mother's residence and education. The mortality of urban infants is about 40 percent lower than that of rural infants. The probability of dying among infants whose mother had no formal schooling is twice as high as infants whose mother have secondary or higher education. Children of mothers who are too young or too old when they give birth, have too many prior births, or give birth at short intervals have an elevated mortality risk. Mortality risk is highest for children born to mothers under age 19. The 1993 NDS also collected information necessary for the calculation of adult and maternal mortality using the sisterhood method. For both males and females, at all ages, male mortality is higher than that of females. Matemal mortality ratio for the 1980-1986 is estimated at 213 per 100,000 births, and for the 1987-1993 period 209 per 100,000 births. However, due to the small number of sibling deaths reported in the survey, age-specific rates should be used with caution. Information on health and family planning services available to the residents of the 1993 NDS barangay was collected from a group of respondents in each location. Distance and time to reach a family planning service provider has insignificant association with whether a woman uses contraception or the choice of contraception being used. On the other hand, being close to a hospital increases the likelihood that antenatal care and births are to respondents who receive ANC and are delivered by a medical personnel or delivered in a health facility.

This paper evaluates a Filipino policy that expanded health insurance coverage of its senior citizens, aged 60 and older, in 2014. We employ an instrumental variables estimator in which the first stage is a difference-in-differences specification that exploits the age discontinuity at age 60, along with data from before and after the policy. First stage results show the expansion increased insurance coverage by approximately 16 percentage points. The compliers, those induced by the policy to obtain insurance, were disproportionately female and largely from the middle of the socioeconomic distribution. Second stage regressions indicate that out-of-pocket medical expenditures more than doubled among the compliers. We argue that this is most likely driven by an outward shift in the medical demand curve.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Manila. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Manila. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in Manila, the median household income stands at $153,028 for householders within the 25 to 44 years age group, followed by $63,815 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $39,951.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Manila median household income by age. You can refer the same here

This dataset is about countries in Philippines per year, featuring 4 columns: country, date, electricity production from hydroelectric sources, and median age. The preview is ordered by date (descending).

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Philippines: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

This data is about the number of workers by major occupation category and age group.

Philippines Population: 15 Years & Over: Region VII: Central Visayas data was reported at 5,264.000 Person th in Apr 2018. This records a decrease from the previous number of 5,280.000 Person th for Jan 2018. Philippines Population: 15 Years & Over: Region VII: Central Visayas data is updated quarterly, averaging 4,689.500 Person th from Jul 2004 (Median) to Apr 2018, with 56 observations. The data reached an all-time high of 5,280.000 Person th in Jan 2018 and a record low of 3,852.000 Person th in Oct 2004. Philippines Population: 15 Years & Over: Region VII: Central Visayas data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G004: Labour Force Survey: Population: Age 15 and Above.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

A description of the modelling methods used for age and sex structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

Philippines Population: Female: Age: 45 to 54 Years data was reported at 5,033.000 Person th in Oct 2017. This records an increase from the previous number of 4,984.000 Person th for Jul 2017. Philippines Population: Female: Age: 45 to 54 Years data is updated quarterly, averaging 4,247.500 Person th from Jul 2004 (Median) to Oct 2017, with 54 observations. The data reached an all-time high of 5,033.000 Person th in Oct 2017 and a record low of 3,457.000 Person th in Jul 2004. Philippines Population: Female: Age: 45 to 54 Years data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G004: Labour Force Survey: Population: Age 15 and Above.

Philippines administrative level 0-2 sex and age disaggregated 2022, 2023, 2024, and 2025 population statistics

REFERENCE YEAR: 2022 (and 2023, 2024, 2025)

These CSV population statistics files are suitable for database or ArcGIS joins to the Philippines - Subnational Administrative Boundaries.

See caveats.

Introduction

Welcome to the Filipino Call Center Speech Dataset for the Telecom domain designed to enhance the development of call center speech recognition models specifically for the Telecom industry. This dataset is meticulously curated to support advanced speech recognition, natural language processing, conversational AI, and generative voice AI algorithms.

Speech Data

This training dataset comprises 30 Hours of call center audio recordings covering various topics and scenarios related to the Telecom domain, designed to build robust and accurate customer service speech technology.

Topic Diversity

This dataset offers a diverse range of conversation topics, call types, and outcomes, including both inbound and outbound calls with positive, neutral, and negative outcomes.

This extensive coverage ensures the dataset includes realistic call center scenarios, which is essential for developing effective customer support speech recognition models.

Transcription

To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. These transcriptions feature:

These ready-to-use transcriptions accelerate the development of the Telecom domain call center conversational AI and ASR models for the Filipino language.

Metadata

The dataset provides comprehensive metadata for each conversation and participant:

Philippines recorded a government budget surplus of 68362 PHP Million in January of 2025. This dataset provides the latest reported value for - Philippines Government Budget Value - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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

Philippines administrative levels:

(0) Country

(1) Region (Filipino: rehiyon)

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

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

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

The Gross Domestic Product per capita in Philippines was last recorded at 3745.65 US dollars in 2023. The GDP per Capita in Philippines is equivalent to 30 percent of the world's average. This dataset provides - Philippines GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

Core Consumer Prices in Philippines increased to 127.50 points in February from 127.30 points in January of 2025. This dataset provides the latest reported value for - Philippines Core Consumer Prices - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.