NOTES: Figures include all revisions received from the states and, therefore, may differ from those previously published. Data are provisional and are subject to monthly reporting variation. National data are calculated by summing the number of events reported by state of residence; counts are rounded to the nearest thousand (births and deaths) or hundred (infant deaths). Provisional counts may differ by approximately 2% from final counts, due to rounding and reporting variation. Additionally, the accuracy of the provisional counts may change over time. Data are estimates by state of residence. For discussion of the nature, source, and limitations of the data, see "Technical Notes" of the report, Births, Marriages, Divorces, and Deaths: Provisional Data for 2009. Available from URL: http://www.cdc.gov/nchs/data/nvsr/nvsr58/nvsr58_25.htm. Final counts of births, deaths, and infant deaths for previous years can be obtained from http://wonder.cdc.gov. SOURCE: Provisional data from the National Vital Statistics System, National Center for Health Statistics, CDC.

This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. Infant Mortality is defined as the number of deaths in infants under one year of age per 1,000 live births. Infant mortality is often used as an indicator to measure the health and well-being of a community, because factors affecting the health of entire populations can also impact the mortality rate of infants. Although California’s infant mortality rate is better than the national average, there are significant disparities, with African American babies dying at more than twice the rate of other groups. Data are from the Birth Cohort Files. The infant mortality indicator computed from the birth cohort file comprises birth certificate information on all births that occur in a calendar year (denominator) plus death certificate information linked to the birth certificate for those infants who were born in that year but subsequently died within 12 months of birth (numerator). Studies of infant mortality that are based on information from death certificates alone have been found to underestimate infant death rates for infants of all race/ethnic groups and especially for certain race/ethnic groups, due to problems such as confusion about event registration requirements, incomplete data, and transfers of newborns from one facility to another for medical care. Note there is a separate data table "Infant Mortality by Race/Ethnicity" which is based on death records only, which is more timely but less accurate than the Birth Cohort File. Single year shown to provide state-level data and county totals for the most recent year. Numerator: Infants deaths (under age 1 year). Denominator: Live births occurring to California state residents. Multiple years aggregated to allow for stratification at the county level. For this indicator, race/ethnicity is based on the birth certificate information, which records the race/ethnicity of the mother. The mother can “decline to state”; this is considered to be a valid response. These responses are not displayed on the indicator visualization.

Israel Vital Statistics: per 1000 Live Births: Infant Death Rate data was reported at 3.062 ‰ in 2017. This records a decrease from the previous number of 3.142 ‰ for 2016. Israel Vital Statistics: per 1000 Live Births: Infant Death Rate data is updated yearly, averaging 5.800 ‰ from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 15.700 ‰ in 1981 and a record low of 3.062 ‰ in 2017. Israel Vital Statistics: per 1000 Live Births: Infant Death Rate data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G002: Vital Statistics.

Vietnam Child Mortality Rate: Infant: Deaths per 1000 Live Births: Urban data was reported at 8.400 NA in 2017. This records a decrease from the previous number of 8.500 NA for 2016. Vietnam Child Mortality Rate: Infant: Deaths per 1000 Live Births: Urban data is updated yearly, averaging 9.400 NA from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 20.400 NA in 2001 and a record low of 8.400 NA in 2017. Vietnam Child Mortality Rate: Infant: Deaths per 1000 Live Births: Urban data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G058: Vital Statistics.

Graph and download economic data for Premature Death Rate for Live Oak County, TX (CDC20N2U048297) from 1999 to 2020 about Live Oak County, TX; premature; death; TX; rate; and USA.

Vietnam Child Mortality Rate: Under Five: Deaths per 1000 Live Births: Total data was reported at 21.500 NA in 2017. This records a decrease from the previous number of 21.800 NA for 2016. Vietnam Child Mortality Rate: Under Five: Deaths per 1000 Live Births: Total data is updated yearly, averaging 23.800 NA from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 45.300 NA in 2001 and a record low of 21.500 NA in 2017. Vietnam Child Mortality Rate: Under Five: Deaths per 1000 Live Births: Total data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G058: Vital Statistics.

In 2023, the infant mortality rate in deaths per 1,000 live births in Norway stood at 1.9. Between 1960 and 2023, the figure dropped by 16.5, though the decline followed an uneven course rather than a steady trajectory.

Number and percentage of live births and fetal deaths (stillbirths), by place of birth (hospital or non-hospital), 1991 to most recent year.

Eurostat’s annual data collections on demographic statistics are structured as follows:

NOWCAST: Annual data collection on provisional monthly data on live births and deaths covering at least six months of the reference year (Article 4.3 of the Commission implementing regulation (EU) No 205/2014).

DEMOBAL (Demographic balance): Annual data collection on provisional data on population, total live births and total deaths at national level (Article 4.1 of the Commission implementing regulation (EU) No 205/2014).

POPSTAT (Population Statistics): The most in-depth annual national and regional demographic and migration data collection. The data relate to populations, births, deaths, immigrants, emigrants, marriages and divorces, and is broken down into several categories (Article 3 of Regulation (EU) No 1260/2013 and Article 3 of Regulation (EC) No 862/2007).

The aim is to collect annual mandatory and voluntary demographic data from the national statistical institutes. Mandatory data are those defined by the legislation listed under ‘6.1. Institutional mandate - legal acts and other agreements’.

The completeness of the demographic data collected on a voluntary basis depends on the availability and completeness of information provided by the national statistical institutes. For more information on mandatory/voluntary data collection, see 6.1. Institutional mandate - legal acts and other agreements’.

The following statistics on deaths are collected from the National Statistical Institutes:

• Deaths by month of occurrence
• Deaths by age, year of birth, sex and by:
  • Region (NUTS 2) of residence;
  • Region (NUTS 3) of residence;
  • Country of birth;
  • Country of citizenship;
  • Legal marital status;
  • Educational attainment (ISCED 2011).
• Infant deaths by age and sex;
• Infant deaths by parents' level of educational attainment (ISCED);
• Late foetal deaths by mother's age.

Statistics on mortality: based on the different breakdowns of data on deaths received, Eurostat produces the following:

• Statistics available in the online table Population change - Demographic balance and crude rates at national level (demo_gind):
  • Natural change of population, crude death rate.
• Statistics available in the online table Infant mortality rates (demo_find):
  • Infant mortality rate;
  • Neonatal mortality rate;
  • Early neonatal mortality rate;
  • Late foetal mortality rate;
  • Perinatal mortality rate.
• Life table (demo_mlifetable);
• Life expectancy by age and sex (demo_mlexpec);
• Life expectancy by age, sex and educational attainment (ISCED 2011) (demo_mlexpecedu).

https://ec.europa.eu/eurostat/cache/metadata/en/demo_r_gind3_esms.htm" target="_self">Information about statistics on deaths by NUTS regions.

Crude death rate : The ratio of the number of deaths during the year to the average population in that year. The value is expressed per 1 000 population Infant mortality rate : The ratio of the number of deaths of children under one year of age during the year to the number of live births in that year. The value is expressed per 1 000 live births. Description copied from catalog.inspire.geoportail.lu.

The number of infant deaths per 1,000 live births in Poland significantly decreased during the observed period. The highest death rate occurred in 1946 (***** per 1,000 live births). In 2023, the rate was *** deaths.

United States US: Maternal Mortality Ratio: Modeled Estimate: per 100,000 Live Births data was reported at 14.000 Ratio in 2015. This stayed constant from the previous number of 14.000 Ratio for 2014. United States US: Maternal Mortality Ratio: Modeled Estimate: per 100,000 Live Births data is updated yearly, averaging 13.000 Ratio from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 15.000 Ratio in 2009 and a record low of 11.000 Ratio in 1998. United States US: Maternal Mortality Ratio: Modeled 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 USA – Table US.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. The data are estimated with a regression model using information on the proportion of maternal deaths among non-AIDS deaths in women ages 15-49, fertility, birth attendants, and GDP.; ; WHO, UNICEF, UNFPA, World Bank Group, and the United Nations Population Division. Trends in Maternal Mortality: 1990 to 2015. Geneva, World Health Organization, 2015; Weighted average; This indicator represents the risk associated with each pregnancy and is also a Sustainable Development Goal Indicator for monitoring maternal health.

Each year Eurostat collects demographic data at regional level from EU, EFTA and Candidate countries as part of the Population Statistics data collection. POPSTAT is Eurostat’s main annual demographic data collection and aims to gather information on demography and migration at national and regional levels by various breakdowns (for the full overview see the Eurostat dedicated section). More specifically, POPSTAT collects data at regional levels on:

• population stocks;
• vital events (live births and deaths).

Each country must send the statistics for the reference year (T) to Eurostat by 31 December of the following calendar year (T+1). Eurostat then publishes the data in March of the calendar year after that (T+2).

Demographic data at regional level include statistics on the population at the end of the calendar year and on live births and deaths during that year, according to the official classification for statistics at regional level (NUTS - nomenclature of territorial units for statistics) in force in the year. These data are broken down by NUTS 2 and 3 levels for EU countries. For more information on the NUTS classification and its versions please refer to the Eurostat dedicated pages. For EFTA and Candidate countries the data are collected according to the agreed statistical regions that have been coded in a way that resembles NUTS.

The breakdown of demographic data collected at regional level varies depending on the NUTS/statistical region level. These breakdowns are summarised below, along with the link to the corresponding online table:

NUTS 2 level

• Population by sex, age and region of residence — demo_r_d2jan
• Population on 1 January by age group, sex and region of residence — demo_r_pjangroup
• Live births by mother's age, mother's year of birth and mother's region of residence — demo_r_fagec
• Deaths by sex, age, and region of residence — demo_r_magec

NUTS 3 level

• Population on 1 January by sex, age group and region of residence — demo_r_pjangrp3
• Population on 1 January by broad age group, sex and region of residence — demo_r_pjanaggr3
• Live births (total) by region of residence — demo_r_births
• Live births by five-year age group of the mothers and region of residence — demo_r_fagec3
• Deaths (total) by region of residence — demo_r_deaths
• Deaths by five-year age group, sex and region of residence — demo_r_magec3

This more detailed breakdown (by five-year age group) of the data collected at NUTS 3 level started with the reference year 2013 and is in accordance with the European laws on demographic statistics. In addition to the regional codes set out in the NUTS classification in force, these online tables include few additional codes that are meant to cover data on persons and events that cannot be allocated to any official NUTS region. These codes are denoted as CCX/CCXX/CCXXX (Not regionalised/Unknown level 1/2/3; CC stands for country code) and are available only for France, Hungary, North Macedonia and Albania, reflecting the raw data as transmitted to Eurostat.

For the reference years from 1990 to 2012 all countries sent to Eurostat all the data on a voluntary basis, therefore the completeness of the tables and the length of time series reflect the level of data received from the responsible National Statistical Institutes’ (NSIs) data provider. As a general remark, a lower data breakdown is available at NUTS 3 level as detailed:

• population data are broken down by sex and broad age groups (0-14, 15-64 and 65 or more). The data have this disaggregation since the reference year 2007 for all countries, and even longer for some — demo_r_pjanaggr3
• vital events (live births and deaths) data are available only as totals, without any further breakdown — demo_r_births and demo_r_deaths

Demographic indicators are calculated by Eurostat based on the above raw data using a common methodology for all countries and regions. The regional demographic indicators computed by NUTS level and the corresponding online tables are summarised below:

NUTS 2 level

• Population structure indicators by region of residence (shares of various population age groups, dependency ratios and median age) — demo_r_pjanind2
• Fertility indicators by region of residence — demo_r_find2
• Fertility rates by age and region of residence — demo_r_frate2
• Life table by age, sex and region of residence — demo_r_mlife
• Life expectancy by age, sex and region of residence — demo_r_mlifexp
• Infant mortality rates by region of residence — demo_r_minfind

NUTS 3 level

• Population change - Demographic balance and crude rates at regional level — demo_r_gind3
• Population density by region — demo_r_d3dens
• Population structure indicators by region of residence (shares of various population age groups, dependency ratios and median age) — demo_r_pjanind3
• Fertility indicators by region of residence (total fertility rate, mean age of woman at childbirth and median age of woman at childbirth) — demo_r_find3

Notes:

1) All the indicators are computed for all lower NUTS regions included in the tables (e.g. data included in a table at NUTS 3 level will include also the data for NUTS 2, 1 and country levels).

2) Demographic indicators computed by NUTS 2 and 3 levels are calculated using input data that have different age breakdown. Therefore, minor differences can be noted between the values corresponding to the same indicator of the same region classified as NUTS 2, 1 or country level.

3) Since the reference year 2015, Eurostat has stopped collecting data on area; therefore, the table 'Area by NUTS 3 region (demo_r_d3area)' includes data up to the year 2015 included.

4) Starting with the reference year 2016, the population density indicator is computed using the new data on area 'Area by NUTS 3 region (reg_area3).

Kaggle Dataset Description

Title: Mortality Rate (Under-5, Per 1000 Live Births)
Subtitle: Exploring global trends in child survival and health advancements.

Detailed Description:
This dataset contains the under-5 mortality rate, measured as the number of deaths per 1,000 live births for children under five years of age. Sourced from the World Bank, it highlights progress in child survival and health outcomes globally over decades.

Key Highlights: - Annual data for countries worldwide. - Metric: Mortality rate (under-5, per 1000 live births). - Use cases: Analyze trends, compare regional disparities, and correlate mortality rates with health and economic indicators.

4. Exploratory Data Analysis (EDA)

Notebook Ideas

1. Data Cleaning:

   • Handle missing or inconsistent data.
   • Normalize data for comparison across regions.
   • Add calculated fields like regional averages or year-over-year changes.

2. Visualizations:

   • Line Graph: Trends in under-5 mortality rates over time for selected countries.
   • Heatmap: Mortality rates by region and year.
   • Scatterplot: Correlation between mortality rates and healthcare expenditure or GDP per capita.
   • Bar Chart: Top and bottom countries by under-5 mortality for a specific year.

3. Descriptive Analysis:

   • Highlight countries with the most significant reductions in mortality.
   • Analyze regional improvements over decades (e.g., Sub-Saharan Africa vs. South Asia).

5. Predictive Analysis (Optional)

• Use time-series forecasting (e.g., ARIMA or Prophet) to predict future mortality rates for specific countries or regions.
• Explore regression models to analyze the impact of factors like healthcare expenditure on mortality reduction.

6. Kaggle Notebook

Create a Kaggle notebook with: 1. Data Cleaning: Show how missing or inconsistent values are handled. 2. EDA: Include visualizations like heatmaps, scatterplots, and line charts. 3. Insights: Highlight significant findings, such as countries with notable improvements in child survival. 4. Optional Predictive Modeling: Use regression or time-series models to project future trends.

7. Call to Action

For GitHub:

• Share the GitHub repository link on LinkedIn, Twitter, and forums like Reddit (e.g., r/datascience).
• Invite collaboration:
  • "Fork this repository to add your analyses or insights!"

GitHub Link: https://github.com/yourusername/Under5_Mortality_Trends

For Kaggle:

• Encourage upvotes:
  • "If this dataset helps you, consider upvoting it to help others discover it!"
• Include questions to engage users:
  • "Which regions have made the most progress in reducing child mortality?"
  • "What correlations can be drawn between healthcare expenditure and mortality rates?"

Kaggle Link: https://www.kaggle.com/datasets/yourusername/under5-mortality-rate

8. LinkedIn Post

Post Title:
📉 Global Trends in Under-5 Mortality Rates 🌍

Post Body:
I’m excited to share my latest dataset on under-5 mortality rates (per 1,000 live births), sourced from the World Bank. This dataset highlights progress in global health and child survival, spanning decades and covering countries worldwide.

📂 Explore the Dataset:
- GitHub Repository: https://github.com/yourusername/Under5_Mortality_Trends
- Kaggle Dataset: https://www.kaggle.com/datasets/yourusername/under5-mortality-rate

Why It Matters:

Child survival is a fundamental measure of global health progress. This dataset is ideal for:
- Trend Analysis: Explore how under-5 mortality rates have evolved globally.
- Regional Comparisons: Identify disparities in child survival rates across regions.
- Correlations: Study the relationship between mortality rates and economic indicators like healthcare expenditure or GDP per capita.

📈 Get Involved:
- Use the dataset for your own analyses and visualizations.
- Share your insights and findings.
- Upvote the Kaggle dataset to help others discover it!

❓ What trends or correlations do you find in the data?
- Which country or region has shown the most improvement?
- What factors would you analyze further?

Let me know your thoughts, and feel free to share this resource with others who might benefit! 🌟

DataScience #ChildHealth #MortalityRates #WorldBankData #DataVisualization #GitHub #Kaggle #HealthAnalysis

Let me know if you'd like assistance with EDA or visualization templates!

This data presents national-level provisional maternal mortality rates based on a current flow of mortality and natality data in the National Vital Statistics System. Provisional rates which are an early estimate of the number of maternal deaths per 100,000 live births, are shown as of the date specified and may not include all deaths and births that occurred during a given time period (see Technical Notes). A maternal death is the death of a woman while pregnant or within 42 days of termination of pregnancy irrespective of the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes. In this data visualization, maternal deaths are those deaths with an underlying cause of death assigned to International Statistical Classification of Diseases, 10th Revision (ICD-10) code numbers A34, O00–O95, and O98–O99. The provisional data include reported 12 month-ending provisional maternal mortality rates overall, by age, and by race and Hispanic origin. Provisional maternal mortality rates presented in this data visualization are for “12-month ending periods,” defined as the number of maternal deaths per 100,000 live births occurring in the 12-month period ending in the month indicated. For example, the 12-month ending period in June 2020 would include deaths and births occurring from July 1, 2019, through June 30, 2020. Evaluation of trends over time should compare estimates from year to year (June 2020 and June 2021), rather than month to month, to avoid overlapping time periods. In the visualization and in the accompanying data file, rates based on death counts less than 20 are suppressed in accordance with current NCHS standards of reliability for rates. Death counts between 1-9 in the data file are suppressed in accordance with National Center for Health Statistics (NCHS) confidentiality standards. Provisional data presented on this page will be updated on a quarterly basis as additional records are received. Previously released estimates are revised to include data and record updates received since the previous release. As a result, the reliability of estimates for a 12-month period ending with a specific month will improve with each quarterly release and estimates for previous time periods may change as new data and updates are received.

The dataset contains information on various demographic and health indicators for different countries. It is organized into several columns, each providing essential information about these countries. Here's a description of each column:

1. Country: This column represents the names of different countries or regions included in the dataset. Each row corresponds to a specific country or region, and this column serves as the identifier for each entry.

2. Life Expectancy Males: This column contains data on the average life expectancy of males in each of the listed countries. Life expectancy is a crucial health indicator and provides an estimate of the average number of years a male can expect to live, given current mortality rates and health conditions.

3. Life Expectancy Females: Similar to the "Life Expectancy Males" column, this column provides data on the average life expectancy of females in the same countries. It reflects the average number of years a female can expect to live, considering the prevailing health and mortality conditions.

4. Birth Rate: The "Birth Rate" column contains information about the birth rate in each country. Birth rate is a demographic indicator that represents the number of live births per 1,000 people in a given population over a specific period, usually a year. It can provide insights into a country's population growth or decline.

5. Death Rate: This column presents data on the death rate in each of the listed countries. The death rate is another crucial demographic indicator and represents the number of deaths per 1,000 people in a population over a specific period, often a year. It helps gauge the overall health and mortality conditions within a country.

Actual value and historical data chart for United States Mortality Rate Infant Male Per 1000 Live Births

Vietnam Child Mortality Rate: Under Five: Deaths per 1000 Live Births: Rural data was reported at 26.000 NA in 2017. This records a decrease from the previous number of 26.400 NA for 2016. Vietnam Child Mortality Rate: Under Five: Deaths per 1000 Live Births: Rural data is updated yearly, averaging 27.500 NA from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 50.100 NA in 2001 and a record low of 22.500 NA in 2008. Vietnam Child Mortality Rate: Under Five: Deaths per 1000 Live Births: Rural data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G058: Vital Statistics.

The infant mortality rate is defined as the number of deaths of children under one year of age, expressed per 1 000 live births. Some of the international variation in infant mortality rates is due to variations among countries in registering practices for premature infants. The United States and Canada are two countries which register a much higher proportion of babies weighing less than 500g, with low odds of survival, resulting in higher reported infant mortality. In Europe, several countries apply a minimum gestational age of 22 weeks (or a birth weight threshold of 500g) for babies to be registered as live births. This indicator is measured in terms of deaths per 1 000 live births.

This indicator is a summary measure of premature mortality, providing an explicit way of weighting deaths occurring at younger ages, which may be preventable. The calculation of Potential Years of Life Lost (PYLL) involves summing up deaths occurring at each age and multiplying this with the number of remaining years to live up to a selected age limit (age 75 is used in OECD Health Statistics). In order to assure cross-country and trend comparison, the PYLL are standardised, for each country and each year. The total OECD population in 2010 is taken as the reference population for age standardisation. This indicator is presented as a total and per gender. It is measured in years lost per 100 000 inhabitants (total), per 100 000 men and per 100 000 women, aged 0-69.

Life expectancy at birth is defined as how long, on average, a newborn can expect to live, if current death rates do not change. However, the actual age-specific death rate of any particular birth cohort cannot be known in advance. If rates are falling, actual life spans will be higher than life expectancy calculated using current death rates. Life expectancy at birth is one of the most frequently used health status indicators. Gains in life expectancy at birth can be attributed to a number of factors, including rising living standards, improved lifestyle and better education, as well as greater access to quality health services. This indicator is presented as a total and per gender and is measured in years.

Decrease the rate of infant deaths per 1,000 live births from 7.5 in 2012 to 6.5 by 2018.