Number of infant deaths and infant mortality rates, by age group (neonatal and post-neonatal), 1991 to most recent year.

Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

India IN: Probability of Dying at Age 10-14 Years: per 1000 data was reported at 2.700 Ratio in 2019. This records a decrease from the previous number of 2.800 Ratio for 2018. India IN: Probability of Dying at Age 10-14 Years: per 1000 data is updated yearly, averaging 4.950 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 6.900 Ratio in 1990 and a record low of 2.700 Ratio in 2019. India IN: Probability of Dying at Age 10-14 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Probability of dying between age 10-14 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

INTRO

This dataset covers the most recent and updated health statistics of the world (countries recognized by WHO- all), BUT the data could not be directly used as the major indicator of various subtopics in the dataset was mixed so I have filtered based on various indicators and hence, divided into subcategories. I know so many datasets seem overwhelming, but I will be giving the various categories they belong to and what they represent so do not worry!)

The dataset was filtered to increase user readability and create amazing and beautiful visualizations and EDA’s. Listed below will be the various datasets (named csv’s) and what they represent under their categories.

Also, before starting I will soon be uploading a viz for the same and this data cleaning and filtering has along with compiling has been a great task so...

Let us get started.

DATASET (CONTENTS)

Life expectancy and Healthy life expectancy

lifeExpectancyAtBirth.csv -> Life expectancy at birth, country wise mentioned in age (years). HALElifeExpectancyAtBirth.csv -> Healthy life expectancy (HALE) at birth, country wise mentioned in age(years).csv WHOregionLifeExpectancAtBirth.csv -> Life expectancy at birth, Region wise mentioned in age (years). HAleWHOregionLifeExpectancy.csv -> Healthy life expectancy at birth, region wise mentioned in age(years). %HaleInLifeExpectancy.csv -> Healthy life and life expectancy at birth with the % of HALE in life expectancy.

Maternal mortality

Data from 2014 to 2019 indicate that approximately 81% of all births globally took place in the presence of skilled health personnel, an increase from 64% in the 2000–2006 period

maternalMortalityRatio.csv-> Maternal mortality ratio per 100,000 births birthAttendedBySkilledPersonal.csv-> Births attended by skilled personals (percentile)

Newborn and child mortality

infantMortalityRate.csv-> Probability of dying between birth and age 1 per 1000 live births. neonatalMortalityRate.csv -> Probability of children dying in the first 28 days of life. under5MortalityRate.csv- > Probability of children dying below the age of 5 per 1000 live births.

Communicable Diseases

incedenceOfMalaria.csv-> Malaria incidence per 1000 population at risk incedenceOfTuberculosis.csv-> Incidence of TB per 100,000 population per year. hepatitusBsurfaceAntigen.csv -> Hepatitis B surface antigen (HBsAg) prevalence among children under 5 years) interventionAgianstNTD's.csv -> Reported number of people requiring interventions against NTDs. newHivInfections.csv ->New HIV infections per 1000 uninfected population

Noncommunicable diseases and mental health

30-70cancerChdEtc.csv -> Probability of dying between the age of 30 and exact age of 70 from any of the cardiovascular disease, cancer, diabetes, or chronic respiratory disease. crudeSuicideRates.csv -> Crude suicide rates per 100,000 population

Substance abuse

AlcoholSubstanceAbuse.csv -> Total (recorded + unrecorded) alcohol per capita (15 +) consumption’s

Road Traffic Injuries

roadTrafficDeaths.csv -> Estimated road traffic death rate per 100,000 population

Sexual and reproductive health

reproductiveAgeWomen.csv -> Married or in-union women of reproductive age who have their need for family planning satisfied with modern methods (%) adolescentBirthRate.csv -> Adolescent birth rate per 1000 women aged 15-19 years

Achieve universal health coverage (UHC) including financial risk protection

uhcCoverage.csv ->UHC index of service coverage (SCI) dataAvailibilityForUhc.csv ->Data availability of UHC index of essential service coverage (%) population10%SDG3.8.2.csv ->Population with household expenditures on health greater than 10% of total household expenditure or income (SDG indicator 3.8.2) (%) population25%SDG3.8.2.csv -> Population with household expenditures on health greater than 25% of total household expenditure or income (SDG indicator 3.8.2) (%)

Mortality from environment pollution

airPollutionDeathRate.csv -> Ambient and household air pollution attributable death rate per 100,00 population and the same data with age-standardized. mortalityRateUnsafeWash.csv -> Mortality rate attributed to exposure to unsafe WASH services per 100,000 population SDG3.9.2 mortalityRatePoisoning.csv -> Mortality rate attributed to unintentional poisoning per 100,000 population

Tobacco control

tobaccoAge15.csv ->Prevalence of current tobacco use among persons aged 15 years and older (age- standardized rate)

Health Workforce

medicalDoctors.csv -> Medical doctors per 10,000 population. nursingAndMidwife.csv -> Nursing and midwifery personnel per 10,000 ...

Number of deaths and age-specific mortality rates for selected grouped causes, by age group and sex, 2000 to most recent year.

The 2008 National Demographic and Health Survey (2008 NDHS) is a nationally representative survey of 13,594 women age 15-49 from 12,469 households successfully interviewed, covering 794 enumeration areas (clusters) throughout the Philippines. This survey is the ninth in a series of demographic and health surveys conducted to assess the demographic and health situation in the country. The survey obtained detailed information on fertility levels, marriage, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood mortality, maternal and child health, and knowledge and attitudes regarding HIV/AIDS and tuberculosis. Also, for the first time, the Philippines NDHS gathered information on violence against women. The 2008 NDHS was conducted by the Philippine National Statistics Office (NSO). Technical assistance was provided by ICF Macro through the MEASURE DHS program. Funding for the survey was mainly provided by the Government of the Philippines. Financial support for some preparatory and processing phases of the survey was provided by the U.S. Agency for International Development (USAID). Like previous Demographic and Health Surveys (DHS) conducted in the Philippines, the 2008 National Demographic and Health Survey (NDHS) was primarily designed to provide information on population, family planning, and health to be used in evaluating and designing policies, programs, and strategies for improving health and family planning services in the country. The 2008 NDHS also included questions on domestic violence. Specifically, the 2008 NDHS had the following objectives: Collect data at the national level that will allow the estimation of demographic rates, particularly, fertility rates by urban-rural residence and region, and under-five mortality rates at the national level. Analyze the direct and indirect factors which determine the levels and patterns of fertility. Measure the level of contraceptive knowledge and practice by method, urban-rural residence, and region. Collect data on family health: immunizations, prenatal and postnatal checkups, assistance at delivery, breastfeeding, and prevalence and treatment of diarrhea, fever, and acute respiratory infections among children under five years. Collect data on environmental health, utilization of health facilities, prevalence of common noncommunicable and infectious diseases, and membership in health insurance plans. Collect data on awareness of tuberculosis. Determine women's knowledge about HIV/AIDS and access to HIV testing. Determine the extent of violence against women. MAIN RESULTS FERTILITY Fertility Levels and Trends. There has been a steady decline in fertility in the Philippines in the past 36 years. From 6.0 children per woman in 1970, the total fertility rate (TFR) in the Philippines declined to 3.3 children per woman in 2006. The current fertility level in the country is relatively high compared with other countries in Southeast Asia, such as Thailand, Singapore and Indonesia, where the TFR is below 2 children per woman. Fertility Differentials. Fertility varies substantially across subgroups of women. Urban women have, on average, 2.8 children compared with 3.8 children per woman in rural areas. The level of fertility has a negative relationship with education; the fertility rate of women who have attended college (2.3 children per woman) is about half that of women who have been to elementary school (4.5 children per woman). Fertility also decreases with household wealth: women in wealthier households have fewer children than those in poorer households. FAMILY PLANNING Knowledge of Contraception. Knowledge of family planning is universal in the Philippines- almost all women know at least one method of fam-ily planning. At least 90 percent of currently married women have heard of the pill, male condoms, injectables, and female sterilization, while 87 percent know about the IUD and 68 percent know about male sterilization. On average, currently married women know eight methods of family planning. Unmet Need for Family Planning. Unmet need for family planning is defined as the percentage of currently married women who either do not want any more children or want to wait before having their next birth, but are not using any method of family planning. The 2008 NDHS data show that the total unmet need for family planning in the Philippines is 22 percent, of which 13 percent is limiting and 9 percent is for spacing. The level of unmet need has increased from 17 percent in 2003. Overall, the total demand for family planning in the Philippines is 73 percent, of which 69 percent has been satisfied. If all of need were satisfied, a contraceptive prevalence rate of about 73 percent could, theoretically, be expected. Comparison with the 2003 NDHS indicates that the percentage of demand satisfied has declined from 75 percent. MATERNAL HEALTH Antenatal Care. Nine in ten Filipino mothers received some antenatal care (ANC) from a medical professional, either a nurse or midwife (52 percent) or a doctor (39 percent). Most women have at least four antenatal care visits. More than half (54 percent) of women had an antenatal care visit during the first trimester of pregnancy, as recommended. While more than 90 percent of women who received antenatal care had their blood pressure monitored and weight measured, only 54 percent had their urine sample taken and 47 percent had their blood sample taken. About seven in ten women were informed of pregnancy complications. Three in four births in the Philippines are protected against neonatal tetanus. Delivery and Postnatal Care. Only 44 percent of births in the Philippines occur in health facilities-27 percent in a public facility and 18 percent in a private facility. More than half (56 percent) of births are still delivered at home. Sixty-two percent of births are assisted by a health professional-35 percent by a doctor and 27 percent by a midwife or nurse. Thirty-six percent are assisted by a traditional birth attendant or hilot. About 10 percent of births are delivered by C-section. The Department of Health (DOH) recommends that mothers receive a postpartum check within 48 hours of delivery. A majority of women (77 percent) had a postnatal checkup within two days of delivery; 14 percent had a postnatal checkup 3 to 41 days after delivery. CHILD HEALTH Childhood Mortality. Childhood mortality continues to decline in the Philippines. Currently, about one in every 30 children in the Philippines dies before his or her fifth birthday. The infant mortality rate for the five years before the survey (roughly 2004-2008) is 25 deaths per 1,000 live births and the under-five mortality rate is 34 deaths per 1,000 live births. This is lower than the rates of 29 and 40 reported in 2003, respectively. The neonatal mortality rate, representing death in the first month of life, is 16 deaths per 1,000 live births. Under-five mortality decreases as household wealth increases; children from the poorest families are three times more likely to die before the age of five as those from the wealthiest families. There is a strong association between under-five mortality and mother's education. It ranges from 47 deaths per 1,000 live births among children of women with elementary education to 18 deaths per 1,000 live births among children of women who attended college. As in the 2003 NDHS, the highest level of under-five mortality is observed in ARMM (94 deaths per 1,000 live births), while the lowest is observed in NCR (24 deaths per 1,000 live births). NUTRITION Breastfeeding Practices. Eighty-eight percent of children born in the Philippines are breastfed. There has been no change in this practice since 1993. In addition, the median durations of any breastfeeding and of exclusive breastfeeding have remained at 14 months and less than one month, respectively. Although it is recommended that infants should not be given anything other than breast milk until six months of age, only one-third of Filipino children under six months are exclusively breastfed. Complementary foods should be introduced when a child is six months old to reduce the risk of malnutrition. More than half of children ages 6-9 months are eating complementary foods in addition to being breastfed. The Infant and Young Child Feeding (IYCF) guidelines contain specific recommendations for the number of times that young children in various age groups should be fed each day as well as the number of food groups from which they should be fed. NDHS data indicate that just over half of children age 6-23 months (55 percent) were fed according to the IYCF guidelines. HIV/AIDS Awareness of HIV/AIDS. While over 94 percent of women have heard of AIDS, only 53 percent know the two major methods for preventing transmission of HIV (using condoms and limiting sex to one uninfected partner). Only 45 percent of young women age 15-49 know these two methods for preventing HIV transmission. Knowledge of prevention methods is higher in urban areas than in rural areas and increases dramatically with education and wealth. For example, only 16 percent of women with no education know that using condoms limits the risk of HIV infection compared with 69 percent of those who have attended college. TUBERCULOSIS Knowledge of TB. While awareness of tuberculosis (TB) is high, knowledge of its causes and symptoms is less common. Only 1 in 4 women know that TB is caused by microbes, germs or bacteria. Instead, respondents tend to say that TB is caused by smoking or drinking alcohol, or that it is inherited. Symptoms associated with TB are better recognized. Over half of the respondents cited coughing, while 39 percent mentioned weight loss, 35 percent mentioned blood in sputum, and 30 percent cited coughing with sputum. WOMEN'S STATUS Women's Status and Employment.

THIS DATASET WAS LAST UPDATED AT 7:11 AM EASTERN ON DEC. 1

OVERVIEW

2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

A total of 229 people died in mass killings in 2019.

The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

One-third of the offenders died at the scene of the killing or soon after, half from suicides.

About this Dataset

The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

This data will be updated periodically and can be used as an ongoing resource to help cover these events.

Using this Dataset

To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

Mass killings by year

Mass shootings by year

To get these counts just for your state:

Filter killings by state

Definition of "mass murder"

Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

Methodology

Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

This project started at USA TODAY in 2012.

Contacts

Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

About this dataset

Context

The dataset tabulates the data for the Trumbull County, OH population pyramid, which represents the Trumbull County population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Trumbull County, OH, is 27.4.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Trumbull County, OH, is 36.0.
• Total dependency ratio for Trumbull County, OH is 63.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Trumbull County, OH is 2.8.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Trumbull County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Trumbull County for the selected age group is shown in the following column.
• Population (Female): The female population in the Trumbull County for the selected age group is shown in the following column.
• Total Population: The total population of the Trumbull County for the selected age group is shown in the following column.

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 Trumbull County Population by Age. You can refer the same here

This data originates from the Public Health Outcomes tool currently presents data for available indicators for upper tier local authority levels, collated by Public Health England (PHE). The data currently published here are the baselines for the Public Health Outcomes Framework, together with more recent data where these are available. The baseline period is 2010 or equivalent, unless these data are unavailable or not deemed to be of sufficient quality. The first data were published in this tool as an official statistics release in November 2012. Future official statistics updates will be published as part of a quarterly update cycle in August, November, February and May. The definition, rationale, source information, and methodology for each indicator can be found within the spreadsheet. Data included in the spreadsheet: 0.1i - Healthy life expectancy at birth0.1ii - Life Expectancy at 650.1ii - Life Expectancy at birth0.2i - Slope index of inequality in life expectancy at birth based on national deprivation deciles within England0.2ii - Number of upper tier local authorities for which the local slope index of inequality in life expectancy (as defined in 0.2iii) has decreased0.2iii - Slope index of inequality in life expectancy at birth within English local authorities, based on local deprivation deciles within each area0.2iv - Gap in life expectancy at birth between each local authority and England as a whole0.2v - Slope index of inequality in healthy life expectancy at birth based on national deprivation deciles within England0.2vii - Slope index of inequality in life expectancy at birth within English regions, based on regional deprivation deciles within each area1.01i - Children in poverty (all dependent children under 20)1.01ii - Children in poverty (under 16s)1.02i - School Readiness: The percentage of children achieving a good level of development at the end of reception1.02i - School Readiness: The percentage of children with free school meal status achieving a good level of development at the end of reception1.02ii - School Readiness: The percentage of Year 1 pupils achieving the expected level in the phonics screening check1.02ii - School Readiness: The percentage of Year 1 pupils with free school meal status achieving the expected level in the phonics screening check1.03 - Pupil absence1.04 - First time entrants to the youth justice system1.05 - 16-18 year olds not in education employment or training1.06i - Adults with a learning disability who live in stable and appropriate accommodation1.06ii - % of adults in contact with secondary mental health services who live in stable and appropriate accommodation1.07 - People in prison who have a mental illness or a significant mental illness1.08i - Gap in the employment rate between those with a long-term health condition and the overall employment rate1.08ii - Gap in the employment rate between those with a learning disability and the overall employment rate1.08iii - Gap in the employment rate for those in contact with secondary mental health services and the overall employment rate1.09i - Sickness absence - The percentage of employees who had at least one day off in the previous week1.09ii - Sickness absence - The percent of working days lost due to sickness absence1.10 - Killed and seriously injured (KSI) casualties on England's roads1.11 - Domestic Abuse1.12i - Violent crime (including sexual violence) - hospital admissions for violence1.12ii - Violent crime (including sexual violence) - violence offences per 1,000 population1.12iii- Violent crime (including sexual violence) - Rate of sexual offences per 1,000 population1.13i - Re-offending levels - percentage of offenders who re-offend1.13ii - Re-offending levels - average number of re-offences per offender1.14i - The rate of complaints about noise1.14ii - The percentage of the population exposed to road, rail and air transport noise of 65dB(A) or more, during the daytime1.14iii - The percentage of the population exposed to road, rail and air transport noise of 55 dB(A) or more during the night-time1.15i - Statutory homelessness - homelessness acceptances1.15ii - Statutory homelessness - households in temporary accommodation1.16 - Utilisation of outdoor space for exercise/health reasons1.17 - Fuel Poverty1.18i - Social Isolation: % of adult social care users who have as much social contact as they would like1.18ii - Social Isolation: % of adult carers who have as much social contact as they would like1.19i - Older people's perception of community safety - safe in local area during the day1.19ii - Older people's perception of community safety - safe in local area after dark1.19iii - Older people's perception of community safety - safe in own home at night2.01 - Low birth weight of term babies2.02i - Breastfeeding - Breastfeeding initiation2.02ii - Breastfeeding - Breastfeeding prevalence at 6-8 weeks after birth2.03 - Smoking status at time of delivery2.04 - Under 18 conceptions2.04 - Under 18 conceptions: conceptions in those aged under 162.06i - Excess weight in 4-5 and 10-11 year olds - 4-5 year olds2.06ii - Excess weight in 4-5 and 10-11 year olds - 10-11 year olds2.07i - Hospital admissions caused by unintentional and deliberate injuries in children (aged 0-14 years)2.07i - Hospital admissions caused by unintentional and deliberate injuries in children (aged 0-4 years)2.07ii - Hospital admissions caused by unintentional and deliberate injuries in young people (aged 15-24)2.08 - Emotional well-being of looked after children2.09i - Smoking prevalence at age 15 - current smokers (WAY survey)2.09ii - Smoking prevalence at age 15 - regular smokers (WAY survey)2.09iii - Smoking prevalence at age 15 - occasional smokers (WAY survey)2.09iv - Smoking prevalence at age 15 years - regular smokers (SDD survey)2.09v - Smoking prevalence at age 15 years - occasional smokers (SDD survey)2.12 - Excess Weight in Adults2.13i - Percentage of physically active and inactive adults - active adults2.13ii - Percentage of physically active and inactive adults - inactive adults2.14 - Smoking Prevalence2.14 - Smoking prevalence - routine & manual2.15i - Successful completion of drug treatment - opiate users2.15ii - Successful completion of drug treatment - non-opiate users2.16 - People entering prison with substance dependence issues who are previously not known to community treatment2.17 - Recorded diabetes2.18 - Admission episodes for alcohol-related conditions - narrow definition2.19 - Cancer diagnosed at early stage (Experimental Statistics)2.20i - Cancer screening coverage - breast cancer2.20ii - Cancer screening coverage - cervical cancer2.21i - Antenatal infectious disease screening – HIV coverage2.21iii - Antenatal Sickle Cell and Thalassaemia Screening - coverage2.21iv - Newborn bloodspot screening - coverage2.21v - Newborn Hearing screening - Coverage2.21vii - Access to non-cancer screening programmes - diabetic retinopathy2.21viii - Abdominal Aortic Aneurysm Screening2.22iii - Cumulative % of the eligible population aged 40-74 offered an NHS Health Check2.22iv - Cumulative % of the eligible population aged 40-74 offered an NHS Health Check who received an NHS Health Check2.22v - Cumulative % of the eligible population aged 40-74 who received an NHS Health check2.23i - Self-reported well-being - people with a low satisfaction score2.23ii - Self-reported well-being - people with a low worthwhile score2.23iii - Self-reported well-being - people with a low happiness score2.23iv - Self-reported well-being - people with a high anxiety score2.23v - Average Warwick-Edinburgh Mental Well-Being Scale (WEMWBS) score2.24i - Injuries due to falls in people aged 65 and over2.24ii - Injuries due to falls in people aged 65 and over - aged 65-792.24iii - Injuries due to falls in people aged 65 and over - aged 80+3.01 - Fraction of mortality attributable to particulate air pollution3.02 - Chlamydia detection rate (15-24 year olds)3.02 - Chlamydia detection rate (15-24 year olds)3.03i - Population vaccination coverage - Hepatitis B (1 year old)3.03i - Population vaccination coverage - Hepatitis B (2 years old)3.03iii - Population vaccination coverage - Dtap / IPV / Hib (1 year old)3.03iii - Population vaccination coverage - Dtap / IPV / Hib (2 years old)3.03iv - Population vaccination coverage - MenC3.03ix - Population vaccination coverage - MMR for one dose (5 years old)3.03v - Population vaccination coverage - PCV3.03vi - Population vaccination coverage - Hib / Men C booster (5 years)3.03vi - Population vaccination coverage - Hib / MenC booster (2 years old)3.03vii - Population vaccination coverage - PCV booster3.03viii - Population vaccination coverage - MMR for one dose (2 years old)3.03x - Population vaccination coverage - MMR for two doses (5 years old)3.03xii - Population vaccination coverage - HPV3.03xiii - Population vaccination coverage - PPV3.03xiv - Population vaccination coverage - Flu (aged 65+)3.03xv - Population vaccination coverage - Flu (at risk individuals)3.04 - People presenting with HIV at a late stage of infection3.05i - Treatment completion for TB3.05ii - Incidence of TB3.06 - NHS organisations with a board approved sustainable development management plan3.07 - Comprehensive, agreed inter-agency plans for responding to health protection incidents and emergencies4.01 - Infant mortality4.02 - Tooth decay in children aged 54.03 - Mortality rate from causes considered preventable4.04i - Under 75 mortality rate from all cardiovascular diseases4.04ii - Under 75 mortality rate from cardiovascular diseases considered preventable4.05i - Under 75 mortality rate from cancer4.05ii - Under 75 mortality rate from cancer considered preventable4.06i - Under 75 mortality rate from liver disease4.06ii - Under 75 mortality rate from liver disease considered preventable4.07i - Under 75 mortality rate from respiratory disease4.07ii - Under 75 mortality rate from respiratory disease considered preventable4.08 - Mortality

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

This dataset contains counts of live births for California counties based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

Indonesia ID: Probability of Dying at Age 10-14 Years: per 1000 data was reported at 2.000 Ratio in 2019. This stayed constant from the previous number of 2.000 Ratio for 2018. Indonesia ID: Probability of Dying at Age 10-14 Years: per 1000 data is updated yearly, averaging 3.100 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 6.500 Ratio in 2004 and a record low of 2.000 Ratio in 2019. Indonesia ID: Probability of Dying at Age 10-14 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Indonesia – Table ID.World Bank.WDI: Health Statistics. Probability of dying between age 10-14 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Families of tax filers; Census families with children by age of children and children by age groups (final T1 Family File; T1FF).

About this dataset

Context

The dataset tabulates the data for the San Angelo, TX population pyramid, which represents the San Angelo population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for San Angelo, TX, is 30.1.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for San Angelo, TX, is 25.0.
• Total dependency ratio for San Angelo, TX is 55.1.
• Potential support ratio, which is the number of youth (working age population) per elderly, for San Angelo, TX is 4.0.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the San Angelo population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the San Angelo for the selected age group is shown in the following column.
• Population (Female): The female population in the San Angelo for the selected age group is shown in the following column.
• Total Population: The total population of the San Angelo for the selected age group is shown in the following column.

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 San Angelo Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Stanton town population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Stanton town. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 550 (63.07% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Stanton town population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Stanton town is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Stanton town is shown in the following column.

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 Stanton town Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Grantville, GA population pyramid, which represents the Grantville population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Grantville, GA, is 27.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Grantville, GA, is 14.5.
• Total dependency ratio for Grantville, GA is 41.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Grantville, GA is 6.9.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Grantville population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Grantville for the selected age group is shown in the following column.
• Population (Female): The female population in the Grantville for the selected age group is shown in the following column.
• Total Population: The total population of the Grantville for the selected age group is shown in the following column.

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 Grantville Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Macomb population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Macomb. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 10 (71.43% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Macomb population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Macomb is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Macomb is shown in the following column.

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 Macomb Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the San Mateo, CA population pyramid, which represents the San Mateo population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for San Mateo, CA, is 24.8.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for San Mateo, CA, is 24.4.
• Total dependency ratio for San Mateo, CA is 49.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for San Mateo, CA is 4.1.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the San Mateo population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the San Mateo for the selected age group is shown in the following column.
• Population (Female): The female population in the San Mateo for the selected age group is shown in the following column.
• Total Population: The total population of the San Mateo for the selected age group is shown in the following column.

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 San Mateo Population by Age. You can refer the same here