19 datasets found
  1. Philippines PH: Labour Force: Female: % of Total Labour Force

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    CEICdata.com, Philippines PH: Labour Force: Female: % of Total Labour Force [Dataset]. https://www.ceicdata.com/en/philippines/labour-force/ph-labour-force-female--of-total-labour-force
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    CEIC Data
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    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    Philippines
    Variables measured
    Labour Force
    Description

    Philippines PH: Labour Force: Female: % of Total Labour Force data was reported at 39.899 % in 2017. This records an increase from the previous number of 39.788 % for 2016. Philippines PH: Labour Force: Female: % of Total Labour Force data is updated yearly, averaging 38.052 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 39.899 % in 2017 and a record low of 37.378 % in 1990. Philippines PH: Labour Force: Female: % of Total Labour Force 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: Labour Force. Female labor force as a percentage of the total show the extent to which women are active in the labor force. Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period.; ; Derived using data from International Labour Organization, ILOSTAT database and World Bank population estimates. Labor data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections.

  2. w

    Philippines - National Demographic Survey 1993 - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Philippines - National Demographic Survey 1993 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/philippines-national-demographic-survey-1993
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    Dataset updated
    Mar 16, 2020
    License

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

    Area covered
    Philippines
    Description

    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.

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    Philippines PH: Population: Female: Ages 60-64: % of Female Population

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    Updated Jul 8, 2018
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    CEICdata.com (2018). Philippines PH: Population: Female: Ages 60-64: % of Female Population [Dataset]. https://www.ceicdata.com/en/philippines/population-and-urbanization-statistics
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    Dataset updated
    Jul 8, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    Philippines
    Variables measured
    Population
    Description

    PH: Population: Female: Ages 60-64: % of Female Population data was reported at 2.995 % in 2017. This records an increase from the previous number of 2.917 % for 2016. PH: Population: Female: Ages 60-64: % of Female Population data is updated yearly, averaging 1.930 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2.995 % in 2017 and a record low of 1.725 % in 1990. PH: Population: Female: Ages 60-64: % of Female Population 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: Population and Urbanization Statistics. Female population between the ages 60 to 64 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

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    Philippines - National Demographic and Health Survey 1998 - Dataset -...

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Philippines - National Demographic and Health Survey 1998 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/philippines-national-demographic-and-health-survey-1998
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    Dataset updated
    Mar 16, 2020
    License

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

    Area covered
    Philippines
    Description

    The 1998 Philippines National Demographic and Health Survey (NDHS). is a nationally-representative survey of 13,983 women age 15-49. The NDHS was designed to provide information on levels and trends of fertility, family planning knowledge and use, infant and child mortality, and maternal and child health. It was implemented by the National Statistics Office in collaboration with the Department of Health (DOH). Macro International Inc. of Calverton, Maryland provided technical assistance to the project, while financial assistance was provided by the U.S. Agency for International Development (USAID) and the DOH. Fieldwork for the NDHS took place from early March to early May 1998. The primary objective of the NDHS is to Provide up-to-date information on fertility levels; determinants of fertility; fertility preferences; infant and childhood mortality levels; awareness, approval, and use of family planning methods; breastfeeding practices; and maternal and child health. This information is intended to assist policy makers and program managers in evaluating and designing programs and strategies for improving health and family planning services in the country. MAIN RESULTS Survey data generally confirm patterns observed in the 1993 National Demographic Survey (NDS), showing increasing contraceptive use and declining fertility. FERTILITY Fertility Decline. The NDHS data indicate that fertility continues to decline gradually but steadily. At current levels, women will give birth an average of 3.7 children per woman during their reproductive years, a decline from the level of 4.1 recorded in the 1993 NDS. A total fertility rate of 3.7, however, is still considerably higher than the rates prevailing in neighboring Southeast Asian countries. Fertility Differentials. Survey data show that the large differential between urban and rural fertility levels is widening even further. While the total fertility rate in urban areas declined by about 15 percent over the last five years (from 3.5 to 3.0), the rate among rural women barely declined at all (from 4.8 to 4.7). Consequently, rural women give birth to almost two children more than urban women. Significant differences in fertility levels by region still exist. For example, fertility is more than twice as high in Eastern Visayas and Bicol Regions (with total fertility rates well over 5 births per woman) than in Metro Manila (with a rate of 2.5 births per woman). Fertility levels are closely related to women's education. Women with no formal education give birth to an average of 5.0 children in their lifetime, compared to 2.9 for women with at least some college education. Women with either elementary or high school education have intermediate fertility rates. Family Size Norms. One reason that fertility has not fallen more rapidly is that women in the Philippines still want moderately large families. Only one-third of women say they would ideally like to have one or two children, while another third state a desire for three children. The remaining third say they would choose four or more children. Overall, the mean ideal family size among all women is 3.2 children, identical to the mean found in 1993. Unplanned Fertility. Another reason for the relatively high fertility level is that unplanned pregnancies are still common in the Philippines. Overall, 45 percent of births in the five years prior to the survey were reported to be unplanned; 27 percent were mistimed (wanted later) and 18 percent were unwanted. If unwanted births could be eliminated altogether, the total fertility rate in the Philippines would be 2.7 births per woman instead of the actual level of 3.7. Age at First Birth. Fertility rates would be even higher if Filipino women did not have a pattem of late childbearing. The median age at first birth is 23 years in the Philippines, considerably higher than in most other countries. Another factor that holds down the overall level of fertility is the fact that about 9 or 10 percent of women never give birth, higher than the level of 3-4 percent found in most developing countries. FAMILY PLANNING Increasing Use of Contraception. A major cause of declining fertility in the Philippines has been the gradual but fairly steady increase in contraceptive use over the last three decades. The contraceptive prevalence rate has tripled since 1968, from 15 to 47 percent of married women. Although contraceptive use has increased since the 1993 NDS (from 40 to 47 percent of married women), comparison with the series of nationally representative Family Planning Surveys indicates that there has been a levelling-off in family planning use in recent years. Method Mix. Use of traditional methods of family planning has always accounted for a relatively high proportion of overall use in the Philippines, and data from the 1998 NDHS show the proportion holding steady at about 40 percent. The dominant changes in the "method mix" since 1993 have been an increase in use of injectables and traditional methods such as calendar rhythm and withdrawal and a decline in the proportions using female sterilization. Despite the decline in the latter, female sterilization still is the most widely used method, followed by the pill. Differentials in Family Planning Use. Differentials in current use of family planning in the 16 administrative regions of the country are large, ranging from 16 percent of married women in ARMM to 55 percent of those in Southern Mindanao and Central Luzon. Contraceptive use varies considerably by education of women. Only 15 percent of married women with no formal education are using a method, compared to half of those with some secondary school. The urban-rural gap in contraceptive use is moderate (51 vs. 42 percent, respectively). Knowledge of Contraception. Knowledge of contraceptive methods and supply sources has been almost universal in the Philippines for some time and the NDHS results indicate that 99 percent of currently married women age 15-49 have heard of at least one method of family planning. More than 9 in 10 married women know the pill, IUD, condom, and female sterilization, while about 8 in 10 have heard of injectables, male sterilization, rhythm, and withdrawal. Knowledge of injectables has increased far more than any other method, from 54 percent of married women in 1993 to 89 percent in 1998. Unmet Need for Family Planning. Unmet need for family planning services has declined since I993. Data from the 1993 NDS show that 26 percent of currently married women were in need of services, compared with 20 percent in the 1998 NDHS. A little under half of the unmet need is comprised of women who want to space their next birth, while just over half is for women who do not want any more children (limiters). If all women who say they want to space or limit their children were to use methods, the contraceptive prevalence rate could be increased from 47 percent to 70 percent of married women. Currently, about three-quarters of this "total demand" for family planning is being met. Discontinuation Rates. One challenge for the family planning program is to reduce the high levels of contraceptive discontinuation. NDHS data indicate that about 40 percent of contraceptive users in the Philippines stop using within 12 months of starting, almost one-third of whom stop because of an unwanted pregnancy (i.e., contraceptive failure). Discontinuation rates vary by method. Not surprisingly, the rates for the condom (60 percent), withdrawal (46 percent), and the pill (44 percent) are considerably higher than for the 1UD (14 percent). However, discontinuation rates for injectables are relatively high, considering that one dose is usually effective for three months. Fifty-two percent of injection users discontinue within one year of starting, a rate that is higher than for the pill. MATERNAL AND CHILD HEALTH Childhood Mortality. Survey results show that although the infant mortality rate remains unchanged, overall mortality of children under five has declined somewhat in recent years. Under-five mortality declined from 54 deaths per 1,000 births in 1988-92 to 48 for the period 1993-97. The infant mortality rate remained stable at about 35 per 1,000 births. Childhood Vaccination Coverage. The 1998 NDHS results show that 73 percent of children 12- 23 months are fully vaccinated by the date of the interview, almost identical to the level of 72 percent recorded in the 1993 NDS. When the data are restricted to vaccines received before the child's first birthday, however, only 65 percent of children age 12-23 months can be considered to be fully vaccinated. Childhood Health. The NDHS provides some data on childhood illness and treatment. Approximately one in four children under age five had a fever and 13 percent had respiratory illness in the two weeks before the survey. Of these, 58 percent were taken to a health facility for treatment. Seven percent of children under five were reported to have had diarrhea in the two weeks preceeding the survey. The fact that four-fifths of children with diarrhea received some type of oral rehydration therapy (fluid made from an ORS packet, recommended homemade fluid, or increased fluids) is encouraging. Breastfeeding Practices. Almost all Filipino babies (88 percent) are breastfed for some time, with a median duration of breastfeeding of 13 months. Although breastfeeding has beneficial effects on both the child and the mother, NDHS data indicate that supplementation of breastfeeding with other liquids and foods occurs too early in the Philippines. For example, among newborns less than two months of age, 19 percent were already receiving supplemental foods or liquids other than water. Maternal Health Care. NDHS data point to several areas regarding maternal health care in which improvements could be made. Although most Filipino mothers (86 percent) receive prenatal care from a doctor, nurse, or midwife, tetanus toxoid coverage is far from universal and

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    National Demographic and Health Survey 2022 - Philippines

    • microdata.worldbank.org
    • catalog.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://microdata.worldbank.org/index.php/catalog/5846
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    Dataset updated
    Jun 7, 2023
    Dataset authored and provided by
    Philippine Statistics Authority (PSA)
    Time period covered
    2022
    Area covered
    Philippines
    Description

    Abstract

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

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

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

    Geographic coverage

    National coverage

    Analysis unit

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

    Universe

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

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

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

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

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

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

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

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

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

    Cleaning operations

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

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

    Response rate

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

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2022 Philippines National Demographic and Health Survey (2022 NDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2022 NDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

    A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

    If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2022 NDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

    A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

    Data appraisal

    Data Quality Tables

    • Household age distribution
    • Age distribution of eligible and interviewed women
    • Age displacement at age 14/15
    • Age displacement at age 49/50
    • Pregnancy outcomes by years preceding the survey
    • Completeness of reporting
    • Observation of handwashing facility
    • School attendance by single year of age
    • Vaccination cards photographed
    • Population pyramid
    • Five-year mortality rates

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

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    Philippines PH: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49...

    • ceicdata.com
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    CEICdata.com, Philippines PH: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 [Dataset]. https://www.ceicdata.com/en/philippines/health-statistics/ph-contraceptive-prevalence-any-methods--of-women-aged-1549
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    License

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

    Time period covered
    Dec 1, 1998 - Dec 1, 2013
    Area covered
    Philippines
    Description

    Philippines PH: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 data was reported at 55.100 % in 2013. This records an increase from the previous number of 48.900 % for 2011. Philippines PH: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 data is updated yearly, averaging 48.850 % from Dec 1968 (Median) to 2013, with 20 observations. The data reached an all-time high of 55.100 % in 2013 and a record low of 15.400 % in 1968. Philippines PH: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 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. Contraceptive prevalence rate is the percentage of women who are practicing, or whose sexual partners are practicing, any form of contraception. It is usually measured for women ages 15-49 who are married or in union.; ; UNICEF's State of the World's Children and Childinfo, United Nations Population Division's World Contraceptive Use, household surveys including Demographic and Health Surveys and Multiple Indicator Cluster Surveys.; Weighted average; Contraceptive prevalence amongst women of reproductive age is an indicator of women's empowerment and is related to maternal health, HIV/AIDS, and gender equality.

  7. m

    Violence Against Women in The Philippines Based On The Ecological Framework

    • data.mendeley.com
    Updated Aug 29, 2024
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    Tia Mariatul Kibtiah (2024). Violence Against Women in The Philippines Based On The Ecological Framework [Dataset]. http://doi.org/10.17632/hj59sxn9zx.1
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    Dataset updated
    Aug 29, 2024
    Authors
    Tia Mariatul Kibtiah
    License

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

    Area covered
    Philippines
    Description

    This article is the result of a collaborative research effort with my student, who also serves as my research assistant on gender issues. Her focus is on gender issues in the ASEAN region. The gender issues related to equality and the protection of women in the ASEAN Region are still in a delicate state. Therefore, it is crucial that we continue to investigate these issues from their roots until we find a viable solution. Our research, which includes a case study from the Philippines, was conducted using a theoretical ecological framework. The data findings from our research shed light on the ecological factors at play in these gender issues.

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    Global Financial Inclusion (Global Findex) Database 2014 - Philippines

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Oct 29, 2015
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    Development Research Group, Finance and Private Sector Development Unit (2015). Global Financial Inclusion (Global Findex) Database 2014 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/2477
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    Dataset updated
    Oct 29, 2015
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2014
    Area covered
    Philippines
    Description

    Abstract

    Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

    By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

    Geographic coverage

    Sample is disproportionately allocated across the four broad regions.

    Analysis unit

    Individual

    Universe

    The target population is the civilian, non-institutionalized population 15 years and above.

    Kind of data

    Sample survey data [ssd]

    Frequency of data collection

    Triennial

    Sampling procedure

    As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

    Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.

    In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    The sample size in Philippines was 1,000 individuals.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

    Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.

  9. w

    National Demographic and Health Survey 2017 - Philippines

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Oct 4, 2018
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    Philippines Statistics Authority (PSA) (2018). National Demographic and Health Survey 2017 - Philippines [Dataset]. https://microdata.worldbank.org/index.php/catalog/3220
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    Dataset updated
    Oct 4, 2018
    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.

  10. m

    Preventing Mass Sexual Violence in Asia-Pacific

    • bridges.monash.edu
    • researchdata.edu.au
    xlsx
    Updated Sep 19, 2018
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    Sara Davies; Jacqui True (2018). Preventing Mass Sexual Violence in Asia-Pacific [Dataset]. http://doi.org/10.4225/03/5ae9925c8e8af
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    xlsxAvailable download formats
    Dataset updated
    Sep 19, 2018
    Dataset provided by
    Monash University
    Authors
    Sara Davies; Jacqui True
    License

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

    Area covered
    Asia–Pacific
    Description

    The Prevention of Sexual Violence in Asia Pacific project is concerned with understanding the relationship between endemic violence against women with widespread and systematic sexual and gender based violence. We are documenting all reports of violence against women and girls in three countries: Philippines, Myanmar and Sri Lanka. The purpose is to understand the relationship between political violence, violence against women and spikes in sexual violence atrocities against these populations. The study covers 1998-2016.List of Publications

    Davies, S.E and J. True, 2017. “When There is No Justice: The Case of Conflict-Related Sexual and Gender-based Violence in Sri Lanka” International Journal of Human Rights 21, 8: 1320-1336.

    Davies, S.E and J. True. 2017. “Connecting the Dots: Pre-existing Patterns of Gender Inequality and the Likelihood of Mass Sexual Violence.” Global Responsibility to Protect 9, 1: 65-85.

    Davies, S.E and J. True. 2017. “The Politics of Counting and Reporting Conflict-related Sexual and Gender-based Violence.” International Feminist Journal of Politics 19, 1: 4-21.

    Davies and J. True. 2017. “Norm Entrepreneurship in International Politics: William Hague and the Prevention of Sexual Violence in Conflict”, Foreign Policy Analysis 13, 3, 1: 701–721.True, J. “Conflict in Asia and the Role of Gender-Based Violence.” In The State of Conflict and Violence in Asia. San Francisco: Asia Foundation, 2017.

    Davies, S.E, J. True and M. Tanyag. 2016. “How Women’s Silence Secures the Peace: Analysing Sexual And Gender-Based Violence in a Low Intensity Conflict. “ Gender and Development 24, 3: 459-473.

    Davies, Sara and J. True. 2015. “The Pandemic of Conflict-Related Sexual Violence and the Political Economy of Gender Inequality.” In Nicola Henry, Anastasia Powell and Asher Flynn, eds. Rape Justice: Beyond the Realm of Law, Basingstoke: Palgrave.

  11. Philippines PH: Literacy Rate: Adult Female: % of Females Aged 15 and Above

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Philippines PH: Literacy Rate: Adult Female: % of Females Aged 15 and Above [Dataset]. https://www.ceicdata.com/en/philippines/education-statistics/ph-literacy-rate-adult-female--of-females-aged-15-and-above
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 1980 - Dec 1, 2013
    Area covered
    Philippines
    Variables measured
    Education Statistics
    Description

    Philippines PH: Literacy Rate: Adult Female: % of Females Aged 15 and Above data was reported at 96.787 % in 2013. This records an increase from the previous number of 95.826 % for 2008. Philippines PH: Literacy Rate: Adult Female: % of Females Aged 15 and Above data is updated yearly, averaging 93.565 % from Dec 1980 (Median) to 2013, with 7 observations. The data reached an all-time high of 96.787 % in 2013 and a record low of 82.762 % in 1980. Philippines PH: Literacy Rate: Adult Female: % of Females Aged 15 and Above 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: Education Statistics. Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

  12. P

    Philippines PH: Prevalence of Underweight: Weight for Age: Female: % of...

    • ceicdata.com
    Updated Apr 15, 2023
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    CEICdata.com (2023). Philippines PH: Prevalence of Underweight: Weight for Age: Female: % of Children Under 5 [Dataset]. https://www.ceicdata.com/en/philippines/health-statistics/ph-prevalence-of-underweight-weight-for-age-female--of-children-under-5
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    Dataset updated
    Apr 15, 2023
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2003 - Dec 1, 2013
    Area covered
    Philippines
    Description

    Philippines PH: Prevalence of Underweight: Weight for Age: Female: % of Children Under 5 data was reported at 20.500 % in 2013. This records an increase from the previous number of 20.300 % for 2011. Philippines PH: Prevalence of Underweight: Weight for Age: Female: % of Children Under 5 data is updated yearly, averaging 20.550 % from Dec 2003 (Median) to 2013, with 4 observations. The data reached an all-time high of 21.300 % in 2003 and a record low of 20.300 % in 2011. Philippines PH: Prevalence of Underweight: Weight for Age: Female: % 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: Health Statistics. Prevalence of underweight, female, is the percentage of girls under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. 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.

  13. Philippines PH: Maternal Mortality Ratio: National Estimate: per 100,000...

    • ceicdata.com
    Updated Jul 8, 2018
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    CEICdata.com (2018). Philippines PH: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births [Dataset]. https://www.ceicdata.com/en/philippines/health-statistics
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    Dataset updated
    Jul 8, 2018
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 1990 - Dec 1, 2011
    Area covered
    Philippines
    Description

    PH: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data was reported at 220.000 Ratio in 2011. This records an increase from the previous number of 160.000 Ratio for 2006. PH: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births data is updated yearly, averaging 190.500 Ratio from Dec 1990 (Median) to 2011, with 6 observations. The data reached an all-time high of 517.000 Ratio in 1993 and a record low of 160.000 Ratio in 2006. PH: Maternal Mortality Ratio: National Estimate: per 100,000 Live Births 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: Health Statistics. Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births.; ; UNICEF, State of the World's Children, Childinfo, and Demographic and Health Surveys.; ;

  14. P

    Philippines PH: Prevalence of Overweight: Weight for Height: Female: % of...

    • ceicdata.com
    Updated Mar 15, 2018
    + more versions
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    CEICdata.com (2018). Philippines PH: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 [Dataset]. https://www.ceicdata.com/en/philippines/health-statistics/ph-prevalence-of-overweight-weight-for-height-female--of-children-under-5
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    Dataset updated
    Mar 15, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2003 - Dec 1, 2013
    Area covered
    Philippines
    Description

    Philippines PH: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data was reported at 4.600 % in 2013. This records an increase from the previous number of 3.900 % for 2011. Philippines PH: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data is updated yearly, averaging 3.400 % from Dec 2003 (Median) to 2013, with 4 observations. The data reached an all-time high of 4.600 % in 2013 and a record low of 2.200 % in 2003. Philippines PH: Prevalence of Overweight: Weight for Height: Female: % 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: Health Statistics. Prevalence of overweight, female, is the percentage of girls under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by 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; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues

  15. Philippines PH: Suicide Mortality Rate: Female

    • ceicdata.com
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    CEICdata.com, Philippines PH: Suicide Mortality Rate: Female [Dataset]. https://www.ceicdata.com/en/philippines/health-statistics/ph-suicide-mortality-rate-female
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2000 - Dec 1, 2016
    Area covered
    Philippines
    Description

    Philippines PH: Suicide Mortality Rate: Female data was reported at 2.000 NA in 2016. This stayed constant from the previous number of 2.000 NA for 2015. Philippines PH: Suicide Mortality Rate: Female data is updated yearly, averaging 1.900 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 2.000 NA in 2016 and a record low of 1.500 NA in 2005. Philippines PH: Suicide Mortality Rate: Female 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. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

  16. Philippines PH: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24

    • ceicdata.com
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    CEICdata.com, Philippines PH: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 [Dataset]. https://www.ceicdata.com/en/philippines/education-statistics
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    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 1980 - Dec 1, 2013
    Area covered
    Philippines
    Variables measured
    Education Statistics
    Description

    PH: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 data was reported at 1.014 Ratio in 2013. This records a decrease from the previous number of 1.015 Ratio for 2008. PH: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 data is updated yearly, averaging 1.014 Ratio from Dec 1980 (Median) to 2013, with 7 observations. The data reached an all-time high of 1.032 Ratio in 2003 and a record low of 1.005 Ratio in 1994. PH: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 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: Education Statistics. Gender parity index for youth literacy rate is the ratio of females to males ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

  17. P

    Philippines PH: Labour Force With Basic Education: Female: % of Female...

    • ceicdata.com
    Updated Apr 15, 2023
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    CEICdata.com (2023). Philippines PH: Labour Force With Basic Education: Female: % of Female Working-age Population [Dataset]. https://www.ceicdata.com/en/philippines/labour-force/ph-labour-force-with-basic-education-female--of-female-workingage-population
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    Dataset updated
    Apr 15, 2023
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2009 - Dec 1, 2016
    Area covered
    Philippines
    Variables measured
    Labour Force
    Description

    Philippines PH: Labour Force With Basic Education: Female: % of Female Working-age Population data was reported at 79.140 % in 2016. This records an increase from the previous number of 78.970 % for 2015. Philippines PH: Labour Force With Basic Education: Female: % of Female Working-age Population data is updated yearly, averaging 80.190 % from Dec 2009 (Median) to 2016, with 7 observations. The data reached an all-time high of 80.840 % in 2011 and a record low of 78.970 % in 2015. Philippines PH: Labour Force With Basic Education: Female: % of Female Working-age Population 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: Labour Force. The percentage of the working age population with a basic level of education who are in the labor force. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average;

  18. P

    Philippines PH: Unemployment with Advance Education: Female: % of Female...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Philippines PH: Unemployment with Advance Education: Female: % of Female Labour Force [Dataset]. https://www.ceicdata.com/en/philippines/employment-and-unemployment/ph-unemployment-with-advance-education-female--of-female-labour-force
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2004 - Dec 1, 2016
    Area covered
    Philippines
    Variables measured
    Employment
    Description

    Philippines PH: Unemployment with Advance Education: Female: % of Female Labour Force data was reported at 8.520 % in 2016. This records a decrease from the previous number of 9.670 % for 2015. Philippines PH: Unemployment with Advance Education: Female: % of Female Labour Force data is updated yearly, averaging 11.170 % from Dec 2004 (Median) to 2016, with 11 observations. The data reached an all-time high of 16.040 % in 2004 and a record low of 8.520 % in 2016. Philippines PH: Unemployment with Advance Education: Female: % of Female Labour Force 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: Employment and Unemployment. The percentage of the labor force with an advanced level of education who are unemployed. Advanced education comprises short-cycle tertiary education, a bachelor’s degree or equivalent education level, a master’s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average;

  19. Philippines PH: Labour Force Participation Rate: National Estimate: Female:...

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Philippines PH: Labour Force Participation Rate: National Estimate: Female: % of Female Population Aged 15+ [Dataset]. https://www.ceicdata.com/en/philippines/labour-force/ph-labour-force-participation-rate-national-estimate-female--of-female-population-aged-15
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Philippines
    Variables measured
    Labour Force
    Description

    Philippines PH: Labour Force Participation Rate: National Estimate: Female: % of Female Population Aged 15+ data was reported at 44.917 % in 2017. This records a decrease from the previous number of 47.993 % for 2016. Philippines PH: Labour Force Participation Rate: National Estimate: Female: % of Female Population Aged 15+ data is updated yearly, averaging 47.774 % from Dec 1960 (Median) to 2017, with 38 observations. The data reached an all-time high of 51.700 % in 2002 and a record low of 13.650 % in 1980. Philippines PH: Labour Force Participation Rate: National Estimate: Female: % of Female Population Aged 15+ 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: Labour Force. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

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CEICdata.com, Philippines PH: Labour Force: Female: % of Total Labour Force [Dataset]. https://www.ceicdata.com/en/philippines/labour-force/ph-labour-force-female--of-total-labour-force
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Philippines PH: Labour Force: Female: % of Total Labour Force

Explore at:
Dataset provided by
CEIC Data
License

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

Time period covered
Dec 1, 2006 - Dec 1, 2017
Area covered
Philippines
Variables measured
Labour Force
Description

Philippines PH: Labour Force: Female: % of Total Labour Force data was reported at 39.899 % in 2017. This records an increase from the previous number of 39.788 % for 2016. Philippines PH: Labour Force: Female: % of Total Labour Force data is updated yearly, averaging 38.052 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 39.899 % in 2017 and a record low of 37.378 % in 1990. Philippines PH: Labour Force: Female: % of Total Labour Force 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: Labour Force. Female labor force as a percentage of the total show the extent to which women are active in the labor force. Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period.; ; Derived using data from International Labour Organization, ILOSTAT database and World Bank population estimates. Labor data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections.

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