This dataset of U.S. mortality trends since 1900 highlights childhood mortality rates by age group for age at death. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). Age groups for childhood death rates are based on age at death. SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

One in every 100 children dies before completing one year of life. Around 68 percent of infant mortality is attributed to deaths of children before completing 1 month. 15,000 children die every day – Child mortality is an everyday tragedy of enormous scale that rarely makes the headlines Child mortality rates have declined in all world regions, but the world is not on track to reach the Sustainable Development Goal for child mortality Before the Modern Revolution child mortality was very high in all societies that we have knowledge of – a quarter of all children died in the first year of life, almost half died before reaching the end of puberty Over the last two centuries all countries in the world have made very rapid progress against child mortality. From 1800 to 1950 global mortality has halved from around 43% to 22.5%. Since 1950 the mortality rate has declined five-fold to 4.5% in 2015. All countries in the world have benefitted from this progress In the past it was very common for parents to see children die, because both, child mortality rates and fertility rates were very high. In Europe in the mid 18th century parents lost on average between 3 and 4 of their children Based on this overview we are asking where the world is today – where are children dying and what are they dying from?

5.4 million children died in 2017 – Where did these children die? Pneumonia is the most common cause of death, preterm births and neonatal disorders is second, and diarrheal diseases are third – What are children today dying from? This is the basis for answering the question what can we do to make further progress against child mortality? We will extend this entry over the course of 2020.

@article{owidchildmortality, author = {Max Roser, Hannah Ritchie and Bernadeta Dadonaite}, title = {Child and Infant Mortality}, journal = {Our World in Data}, year = {2013}, note = {https://ourworldindata.org/child-mortality} }

The child mortality rate in the United States, for children under the age of five, was 462.9 deaths per thousand births in 1800. This means that for every thousand babies born in 1800, over 46 percent did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, and the rate has dropped to its lowest point ever in 2020 where it is just seven deaths per thousand births. Although the child mortality rate has decreased greatly over this 220 year period, there were two occasions where it increased; in the 1870s, as a result of the fourth cholera pandemic, smallpox outbreaks, and yellow fever, and in the late 1910s, due to the Spanish Flu pandemic.

This statistic shows the 20 countries* with the highest infant mortality rate in 2024. An estimated 101.3 infants per 1,000 live births died in the first year of life in Afghanistan in 2024. Infant and child mortality Infant mortality usually refers to the death of children younger than one year. Child mortality, which is often used synonymously with infant mortality, is the death of children younger than five. Among the main causes are pneumonia, diarrhea – which causes dehydration – and infections in newborns, with malnutrition also posing a severe problem. As can be seen above, most countries with a high infant mortality rate are developing countries or emerging countries, most of which are located in Africa. Good health care and hygiene are crucial in reducing child mortality; among the countries with the lowest infant mortality rate are exclusively developed countries, whose inhabitants usually have access to clean water and comprehensive health care. Access to vaccinations, antibiotics and a balanced nutrition also help reducing child mortality in these regions. In some countries, infants are killed if they turn out to be of a certain gender. India, for example, is known as a country where a lot of girls are aborted or killed right after birth, as they are considered to be too expensive for poorer families, who traditionally have to pay a costly dowry on the girl’s wedding day. Interestingly, the global mortality rate among boys is higher than that for girls, which could be due to the fact that more male infants are actually born than female ones. Other theories include a stronger immune system in girls, or more premature births among boys.

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

UNICEF's country profile for United States, including under-five mortality rates, child health, education and sanitation data.

this graph was created in Unicef :

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Fa8bc4d2b506665b0f83aa521d08ff955%2Fsddssddss.png?generation=1711049954454687&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F69f10de83fb767c7f68495f5283b30d8%2Fddfdfdfdf.png?generation=1711049988555838&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F09833bd9bdd657253a2c028f42ec9cdb%2Fsddssdsdsd.png?generation=1711050039213946&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F798e583b24c71664c0d40222aa9df981%2F2323wsd.png?generation=1711050080127039&alt=media" alt="">

Indicator: Child mortality rate (aged 1-4 years) 1986-2021

This year’s United Nations Inter-agency Group for Child Mortality Estimation (UN IGME)’s findings represent a noteworthy moment in the ongoing campaign to end all preventable child deaths: The annual number of under-five deaths has fallen to 4.9 (4.6–5.4) million in 2022. The report reveals that more children are surviving today than ever before, with the global under-5 mortality rate declining by 51 per cent since 2000. And several low- and lower-middle-income countries have outpaced this decline. This is a testament to the commitment of governments, organizations, local communities, health-care professionals and families to the survival of the most vulnerable members of our global community.

Yet millions of children still died before seeing their fifth birthday – a loss that serves as a crucial reminder that threats to newborn and child health and survival persist around the world, particularly among the most marginalized children. In addition to the 4.9 million lives lost before the age of 5 – nearly half of which were newborns – the lives of another 2.1 million children and youth aged 5-24 were also cut short. Most of these deaths were concentrated in sub-Saharan Africa and Southern Asia. There is still a long road ahead to end all preventable child and youth deaths.

Ending preventable child deaths in every community will require targeted investments in available, accessible quality health care, including skilled health personnel at birth, antenatal and postnatal care, care for small and sick newborns, preventive services such as vaccination, and diagnostic, preventive and curative measures to treat the key causes of childhood death. Data systems must also be strengthened to track and monitor survival by age and to help address underlying inequalities. This will enable us to move closer to achieving the Sustainable Development Goals and ensure that every child has the opportunity to thrive.

The child mortality rate in the United Kingdom, for children under the age of five, was 329 deaths per thousand births in 1800. This means that approximately one in every three children born in 1800 did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, particularly in the first half of the twentieth century, and the rate has dropped to its lowest point ever in 2020 where it is just four deaths per thousand births.

PLEASE WRITE CODE FOR THIS:

I need help with the analysis of these datasets and to reveal insights from them as follows:

The initial observations from the exploration of these datasets are as follows: • The data contains some missing values • The data mostly contains numeric values which may not be properly formatted • The data contains relatively few features • Both datasets seem to cover different ranges of years.

Use relevant Machine Learning (ML) techniques (supervised, unsupervised, etc.) and AI search or optimisation techniques. You are expected to present a robust model which must follow the guidelines presented below:

**1. Preprocess the datasets to create a single dataset which contains the needed information to predict mortality rates for different years for each country. NOTE: THERE ARE FIVE DIFFERENT FILES WITH DIFFERENT COUNTRIES MORTALITY RATES SO USE ALL THESE FILES AND MERGE THEM BY USING CODING IN JUPYTER PANDAS. ** 2. Use AI search or optimisation techniques (whichever is appropriate) to align the year periods for each country across all the datasets. 3. Based on the dataset you have created, build a supervised or unsupervised ML model to predict the mortality rates for each country for the different years possible. 4. Justify your design decisions for tasks 1, 2 & 3. 5. Critically evaluate the learning model you have built 6. Evaluate the robustness of your model by applying appropriate validation techniques (and identifying a suitable subset of data for validation).

While setting the parameters of the search or optimisation method, pay special attention to selecting appropriate metrics (evaluation criteria). The chosen metrics will play a critical role in the relative success or failure of the potential solution(s) and in setting the direction of the search or optimisation.

The average for 2022 based on 187 countries was 25 deaths per 1000 births. The highest value was in Niger: 117 deaths per 1000 births and the lowest value was in Estonia: 2 deaths per 1000 births. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

UNICEF's country profile for India, including under-five mortality rates, child health, education and sanitation data.

Mexico: Deaths of children five to fourteen years of age per 1000 live births: The latest value from 2022 is 1 deaths per 1000 births, unchanged from 1 deaths per 1000 births in 2021. In comparison, the world average is 3 deaths per 1000 births, based on data from 187 countries. Historically, the average for Mexico from 1990 to 2022 is 1 deaths per 1000 births. The minimum value, 1 deaths per 1000 births, was reached in 2003 while the maximum of 3 deaths per 1000 births was recorded in 1990.

The Mortality - Infant Deaths (from Linked Birth / Infant Death Records) online databases on CDC WONDER provide counts and rates for deaths of children under 1 year of age, occuring within the United States to U.S. residents. Information from death certificates has been linked to corresponding birth certificates. Data are available by county of mother's residence, child's age, underlying cause of death, sex, birth weight, birth plurality, birth order, gestational age at birth, period of prenatal care, maternal race and ethnicity, maternal age, maternal education and marital status. Data are available since 1995. The data are produced by the National Center for Health Statistics.

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

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.

UNICEF's country profile for Bangladesh, including under-five mortality rates, child health, education and sanitation data.

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!

The Demographic and Health Surveys (DHS) are a major source for many demographic and health indicators in developing countries. Although these indicators are well defined in the literature, using survey data to calculate some of these indicators has never been an easy task for data users. This paper presents the DHS.rates software, a user-friendly R package developed to calculate fertility indicators, such as the total fertility rate, general fertility rate, and age-specific fertility rates, and childhood mortality indicators, such as the neonatal mortality rate, post-neonatal mortality rate, infant mortality rate, child mortality rate, and under-5 mortality rate, from the DHS data. The package allows for national and subnational indicators. In addition, the package calculates sampling error indicators such as standard error, design effect, relative standard error, and confidence interval for each demographic indicator. The package can also be used to calculate the same indicators from other population surveys such as the Multiple Indicator Cluster Survey (MICS).

China: Deaths of children five to fourteen years of age per 1000 live births: The latest value from 2022 is 1 deaths per 1000 births, unchanged from 1 deaths per 1000 births in 2021. In comparison, the world average is 3 deaths per 1000 births, based on data from 187 countries. Historically, the average for China from 1990 to 2022 is 2 deaths per 1000 births. The minimum value, 1 deaths per 1000 births, was reached in 2009 while the maximum of 4 deaths per 1000 births was recorded in 1990.

In 2023, the leading causes of death for children aged one to four years in the United States were unintentional injuries and congenital malformations, deformations, and chromosomal abnormalities. At that time, around 31 percent of all deaths among these children were caused by unintentional injuries. Differences in causes of death among children by age Just as unintentional injuries are the leading cause of death among children aged one to four, it is also the leading cause of death for the age groups five to nine and 10 to 14. However, congenital malformations, deformations, and chromosomal abnormalities account for fewer deaths as children become older, while the share of deaths caused by cancer is higher among those aged five to nine and 10 to 14. In fact, cancer is the second leading cause of death among five to nine-year-olds, accounting for around 16 percent of all deaths. Sadly, the second leading cause of death among children aged 10 to 14 is intentional self-harm, with 14 percent of all deaths among those in this age group caused by suicide. Leading causes of death in the United States The leading causes of death in the United States are heart disease and malignant neoplasms. Together, these two diseases accounted for around 42 percent of all deaths in the United States in 2023. In 2023, the lifetime odds that the average person in the United States would die from heart disease was one in six, while the odds for cancer were one in seven.