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.

This dataset contains the Infant Mortality Rates (IMR) across various years, states, genders such as male and female, and regions such as urban and rural. Data for some smaller states prior to 2004 is not available due to inadequacy of samples. For some states like Kerala and Delhi, there are instances when no deaths were reported. This has been highlighted in the notes column.

This Dataset provides comprehensive demographic information on global populations from 1950 to the present. It offers insights into various aspects of population dynamics, including population counts, gender ratios, birth and death rates, life expectancy, and migration patterns.

Column Descriptions:

SortOrder: Numeric identifier for sorting.

LocID: Location identifier.

Notes: Additional notes or comments (blank in this dataset).

ISO3_code: ISO 3-character country code.

ISO2_code: ISO 2-character country code.

SDMX_code: Statistical Data and Metadata Exchange code.

LocTypeID: Location type identifier.

LocTypeName: Location type name.

ParentID: Identifier for the parent location.

Location: Name of the location.

VarID: Identifier for the variant.

Variant: Type of population variant.

Time: Year or time period.

TPopulation1Jan: Total population on January 1st.

TPopulation1July: Total population on July 1st.

TPopulationMale1July: Total male population on July 1st.

TPopulationFemale1July: Total female population on July 1st.

PopDensity: Population density (people per square kilometer).

PopSexRatio: Population sex ratio (male/female).

MedianAgePop: Median age of the population.

NatChange: Natural change in population.

NatChangeRT: Natural change rate (per 1,000 people).

PopChange: Population change.

PopGrowthRate: Population growth rate (percentage).

DoublingTime: Time for population to double (in years).

Births: Total number of births.

Births1519: Births to mothers aged 15-19.

CBR: Crude birth rate (per 1,000 people).

TFR: Total fertility rate (average number of children per woman).

NRR: Net reproduction rate.

MAC: Mean age at childbearing.

SRB: Sex ratio at birth (male/female).

Deaths: Total number of deaths.

DeathsMale: Total male deaths.

DeathsFemale: Total female deaths.

CDR: Crude death rate (per 1,000 people).

LEx: Life expectancy at birth.

LExMale: Life expectancy for males at birth.

LExFemale: Life expectancy for females at birth.

LE15: Life expectancy at age 15.

LE15Male: Life expectancy for males at age 15.

LE15Female: Life expectancy for females at age 15.

LE65: Life expectancy at age 65.

LE65Male: Life expectancy for males at age 65.

LE65Female: Life expectancy for females at age 65.

LE80: Life expectancy at age 80.

LE80Male: Life expectancy for males at age 80.

LE80Female: Life expectancy for females at age 80.

InfantDeaths: Number of infant deaths.

IMR: Infant mortality rate (per 1,000 live births).

LBsurvivingAge1: Children surviving to age 1.

Under5Deaths: Number of deaths under age 5.

NetMigrations: Net migration rate (per 1,000 people).

CNMR: Crude net migration rate.

How to Use the Dataset:

1. Researchers can analyze demographic trends, birth and death rates, and population growth over time.
2. Policymakers can use population data to inform decisions on healthcare, education, and social services.
3. Data scientists can visualize and model population dynamics for various regions.
4. Journalists can use the dataset to report on global population trends and disparities.
5. Educators can incorporate real-world population data into lessons and research.

Please upvote and show your support if you find this dataset valuable for your research or analysis. Your feedback and contributions help make this dataset more accessible to the Kaggle community. Thank you!

This dataset documents rates and trends in local hypertension-related cardiovascular disease (CVD) death rates. Specifically, this report presents county (or county equivalent) estimates of hypertension-related CVD death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (female, male). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.

1. Database contents The Russian Short-Term Mortality Fluctuations database (RusSTMF) contains a series of standardized and crude death rates for men, women and both sexes for Russia as a whole and its regions for the period from 2000 to 2021. All the output indicators presented in the database are calculated based on data of deaths registered by the Vital Registry Office. The weekly death counts are calculated based on depersonalized individual data provided by the Russian Federal State Statistics Service (Rosstat) at the request of the HSE. Time coverage: 03.01.2000 (Week 1) – 31.12.2021 (Week 1148)
2. A brief description of the input data on deaths Date of death: date of occurrence Unit of time: week First and last days of the week: Monday – Sunday First and last week of the year: The weeks are organized according to ISO 8601:2004 guidelines. Each week of the year, including the first and last, contains 7 days. In order to get 7-day weeks, the days of previous years are included in this first week (if January 1 fell on Tuesday, Wednesday or Thursday) or in the last calendar week (if December 31 fell on Thursday, Friday or Saturday). Age groups: the entire population Sex: men, women, both sexes (men and women combined) Restrictions and data changes: data on deaths in the Pskov region were excluded for weeks 9-13 of 2012 Note: Deaths with an unknown date of occurrence (unknown year, month, or day) account for about 0.3% of all deaths and are excluded from the calculation of week-age-specific and standardized death rates.
3. Description of the week-specific mortality rates data file Week-specific standardized death rates for Russia as a whole and its regions are contained in a single data file presented in .csv format. The format of data allows its uploading into any system for statistical analysis. Each record (row) in the data file contains data for one calendar year, one week, one territory, one sex. The decimal point is dot (.) The first element of the row is the territory code ("PopCode" column), the second element is the year ("Year" column), the third element ("Week" column) is the week of the year, the fourth element ("Sex" column) is sex (F – female, M – male, B – both sexes combined). This is followed by a column "CDR" with the value of the crude death rate and "SDR" with the value of the standardized death rate. If the indicator cannot be calculated for some combination of year, sex, and territory, then the corresponding meaningful data elements in the data file are replaced with ".".

Abstract

The Health Inequality Project uses big data to measure differences in life expectancy by income across areas and identify strategies to improve health outcomes for low-income Americans.

Section 7

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution. Both race-adjusted and unadjusted estimates are reported.

Source

Section 13

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution separately by year. Both race-adjusted and unadjusted estimates are reported.

Source

Section 6

This dataset was created on 2020-01-10 18:53:00.508 by merging multiple datasets together. The source datasets for this version were:

Commuting Zone Life Expectancy Estimates by year: CZ-level by-year life expectancy estimates for men and women, by income quartile

Commuting Zone Life Expectancy: Commuting zone (CZ)-level life expectancy estimates for men and women, by income quartile

Commuting Zone Life Expectancy Trends: CZ-level estimates of trends in life expectancy for men and women, by income quartile

Commuting Zone Characteristics: CZ-level characteristics

Commuting Zone Life Expectancy for larger populations: CZ-level life expectancy estimates for men and women, by income ventile

Section 15

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by state of residence and year. Both race-adjusted and unadjusted estimates are reported.

Source

Section 11

This table reports US mortality rates by gender, age, year and household income percentile. Household incomes are measured two years prior to the mortality rate for mortality rates at ages 40-63, and at age 61 for mortality rates at ages 64-76. The “lag” variable indicates the number of years between measurement of income and mortality.

Observations with 1 or 2 deaths have been masked: all mortality rates that reflect only 1 or 2 deaths have been recoded to reflect 3 deaths

Source

Section 3

This table reports coefficients and standard errors from regressions of life expectancy estimates for men and women at age 40 for each quartile of the national income distribution on calendar year by commuting zone of residence. Only the slope coefficient, representing the average increase or decrease in life expectancy per year, is reported. Trend estimates for both race-adjusted and unadjusted life expectancies are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.

Source

Section 9

This table reports life expectancy estimates at age 40 for Males and Females for all countries. Source: World Health Organization, accessed at: http://apps.who.int/gho/athena/

Source

Section 10

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by county of residence. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for counties with populations larger than 25,000 only

Source

Section 2

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by commuting zone of residence and year. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.

Source

Section 8

This table reports US population and death counts by age, year, and sex from various sources. Counts labelled “dm1” are derived from the Social Security Administration Data Master 1 file. Counts labelled “irs” are derived from tax data. Counts labelled “cdc” are derived from NCHS life tables.

Source

Section 12

This table reports numerous county characteristics, compiled from various sources. These characteristics are described in the county life expectancy table.

Two variables constructed by the Cen

Mortality rates (qx) values from the national life tables release, presented in time series format. These statistics are for males and females for England, Wales, Scotland, Northern Ireland and the UK.

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

Collective data of Japan's birth-related statistics from 1899 to 2022. Some data are missing between the years 1944 and 1946 due to records lost during World War II.

For use case and analysis reference, please take a look at this notebook Japan Birth Demographics Analysis

Feature Descriptions

• year: The year.
• birth_total: The total number of births.
• birth_male: The total number of male births.
• birth_female: The total number of female births.
• birth_rate: The birth rate. Equation is birth_total / population_total * 1,000
• birth_gender_ratio: The birth gender ratio. Equation is birth_male / birth_female * 1,000
• total_fertility_rate: The average number of children that are born to a woman over her lifetime.
• population_total: The total population.
• population_male: The total male population.
• population_female: The total female population.
• infant_death_total: The total infant deaths.
• infant_death_male: The total male infant deaths.
• infant_death_female: The total female infant deaths.
• infant_death_unknown_gender: The total unknown gender infant deaths.
• infant_death_rate: The infant death rate. Equation is infant_death_total / birth_total * 1,000
• infant_death_gender_ratio: The infant death gender ratio. Equation is infant_death_male / infant_death_female * 1,000
• infant_deaths_in_total_deaths: The infant death ratio among other deaths.
• stillbirth_total: The total number of stillbirths (dead born).
• stillbirth_male: The total number of male stillbirths.
• stillbirth_female: The total number of female stillbirths.
• stillbirth_unknown_gender: The total number of unknown gender stillbirths.
• stillbirth_rate: The stillbirth rate. Equation is stillbirth_total / (birth_total + stillbirth_total) * 1,000
• stillbirth_gender_ratio: The stillbirth gender ratio. Equation is stillbirth_male / stillbirth_female * 1,000
• firstborn: The number of firstborns.
• secondborn: The number of secondborns.
• thirdborn: The number of thirdborns.
• forthborn: The number of forthborns.
• fifthborn_and_above: The number of fifthborns and above.
• weeks_under_28: The number of births occurred under week 28. Early terms.
• weeks_28-31: The number of births occurred between weeks 28 and 31. Early terms.
• weeks_32-36: The number of births occurred between weeks 32 and 36. Early terms.
• weeks_37-41: The number of births occurred between weeks 37 and 41. Full terms.
• weeks_over_42: The number of births occurred over week 42. Late terms.
• mother_age_avg: The mother's average age.
• mother_age_firstborn: The mother's average age of the firstborn.
• mother_age_secondborn: The mother's average age of the secondborn.
• mother_age_thirdborn: The mother's average age of the thirdborn.
• mother_age_under_19: The number of births by mothers under age 19.
• mother_age_20-24: The number of births by mothers between age 20 and 24.
• mother_age_25-29: The number of births by mothers between age 25 and 29.
• mother_age_30-34: The number of births by mothers between age 30 and 34.
• mother_age_35-39: The number of births by mothers between age 35 and 39.
• mother_age_40-44: The number of births by mothers between age 40 and 44.
• mother_age_over_45: The number of births by mothers over 45.
• father_age_avg: The father's average age.
• father_age_firstborn: The father's average age of the firstborn.
• father_age_secondborn: The father's average age of the secondborn.
• father_age_thirdborn: The father's average age of the thirdborn.
• legitimate_child: The Number of births under married parents.
• illegitimate_child: The number of births under non-married parents.

Acknowledgement

E-Stat Demographic Survey

Note: Note: Starting October 10th, 2025 this dataset is deprecated and is no longer being updated. As of April 27, 2023 updates changed from daily to weekly. Summary The cumulative number of probable COVID-19 deaths among Maryland residents by gender: Female; Male; Unknown. Description The MD COVID-19 - Probable Deaths by Gender Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by gender. A death is classified as probable if the person's death certificate notes COVID-19 to be a probable, suspect or presumed cause or condition. Probable deaths are not yet been confirmed by a laboratory test. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Confirmed deaths are available from the MD COVID-19 - Confirmed Deaths by Gender Distribution data layer. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

Age-Adjusted Death Rates

Death Rates and Life Expectancy in the United States, 2011-2013

By Health [source]

About this dataset

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How to use the dataset

In order to use this dataset, start by selecting a particular set of variables to investigate. You can choose from Measure Names (e.g., Death Rates or Life Expectancy), Race (e.g., All Races), Sex (Male/Female) and Year (2011-2013). Once you have selected your desired variables, you can begin analyzing the data by looking at mortality rates and life expectancy averages amongst different populations in the United States over time.

You may also wish to perform more detailed analyses such as identifying trends or examining correlations between features, regional disparities in mortality rates or changes in average life expectancies over time. If so, you can do so by creating line graphs plotted against one or more independent variables such as Race and Sex to see how demographics impact these statistics overall and on a yearly basis using the Year variable computed from July 1st 2010 estimates

Research Ideas

• Analyzing mortality and life expectancy trends among certain races and sexes over time.
• Examining the effects of different socioeconomic factors on death rates and life expectancies.
• Making predictions about future mortality rates and average life expectancies with machine learning algorithms

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: rows.csv | Column name | Description | |:----------------------------|:----------------------------------------------------------------------| | Measure Names | The type of measure being reported. (String) | | Race | The race of the population being reported. (String) | | Sex | The gender of the population being reported. (String) | | Year | The year the data was collected. (Integer) | | Average Life Expectancy | The average life expectancy of the population being reported. (Float) | | Mortality | The mortality rate of the population being reported. (Float) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Health.

This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

10-year mortality among men and women in unadjusted and adjusted models.

Abbreviations: PCI = percutaneous coronary intervention; STEMI = ST- elevation myocardial infarction; NSTEMI = non-STEMI.*Odds ratio of female vs male and 95% CI obtained through logistic regression including the following covariates: Age, smoking, diabetes, hypertension, new onset of angina, prior history of heart failure, renal failure.†Odds ratio of female vs male and 95% CI obtained through logistic regression including the following covariates: Age, smoking, diabetes, hypertension, new onset of angina, prior history of heart failure, renal failure and Killip class.

Deaths by local authority of usual residence, numbers and standardised mortality ratios (SMRs) by sex. SMR measures whether the population of an area has a higher or lower number of deaths than expected based on the age profile of the population (more deaths are expected in older populations). The SMR is defined as follows: SMR = (Observed no. of deaths per year)/(Expected no. of deaths per year). SMRs are calculated using the previous year's mid-year population estimates. Live birth figures are used for calculations involving deaths under 1 year. The age-standardised mortality rates in this release are directly age-standardised to the European Standard Population, which cover all ages and allows comparisons between populations with different age structures, including between males and females and over time. Note: SMR and deaths by sex data only available since 2001. Download from ONS website

This dataset presents the top 10 causes of death among infants (aged up to 29 days and upto 1 year), disaggregated by year, region (urban, rural, and total), gender (male, female, and persons), and age group.

A dataset providing total mortality figures by ward broken down by gender. Further information For further information on public health related matters visit: http://www.leeds.gov.uk/phrc/Pages/default.aspx

Presents data on death projections at the following levels: geography: Alberta, Alberta Health Services (AHS) continuum zone, subzone, aggregate area, and local area; sex: male, female, and both, groups and combined ages; sex: male, female, and both. Historical population estimates (actuals) are included on the file for comparison/reference.

This table contains 70641 series, with data for years 1997 - 1997 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (167 items: Canada; Health and Community Services Eastern Region; Newfoundland and Labrador; Newfoundland and Labrador; Health and Community Services St. John's Region; Newfoundland and Labrador ...), Sex (3 items: Both sexes; Males; Females ...), Selected causes of death (ICD-9) (17 items: Total; all causes of death; All malignant neoplasms (cancers);Lung cancer; Colorectal cancer ...), Characteristics (9 items: Number of deaths; Low 95% confidence interval; number of deaths; Mortality; High 95% confidence interval; number of deaths ...).

Abbreviations: PCI = percutaneous coronary intervention; STEMI = ST- elevation myocardial infarction; NSTEMI = non-STEMI.*Odds ratio of female vs male and 95% CI obtained through logistic regression including the following covariates: Age, smoking, diabetes, hypertension, new onset of angina, prior history of heart failure, renal failure.†Odds ratio of female vs male and 95% CI obtained through logistic regression including the following covariates: Age, smoking, diabetes, hypertension, new onset of angina, prior history of heart failure, renal failure and Killip class.